Aeolian Desertification: Disaster with Visual Impact in Semi-arid Regions of Andhra Pradesh, South India [1 ed.] 9789819967285, 9789819967292

Table of contents :
Contents
Abbreviations
List of Figures
List of Tables
List of Plates
1 Introduction
1.1 Introduction
1.2 Review of Literature
1.2.1 Desertification
1.2.2 Land Degradation
1.2.3 Aeolian Desertification
1.3 Aeolian Desertification: Processes and Impacts
1.4 Quantifying Aeolian Desertification
1.5 Mitigation Strategies
1.5.1 Aeolian Process
1.6 Geo-environment
1.7 Remote Sensing and GIS
1.7.1 Remote Sensing Techniques for Aeolian Desertification
1.7.2 GIS Applications for Aeolian Desertification
1.8 Conclusion
References
2 Land Degradation and Desertification
2.1 Introduction
2.2 Land Degradation
2.2.1 Causes of Land Degradation
2.2.2 Consequences of Land Degradation
2.3 Desertification
2.3.1 Causes of Desertification
2.3.2 Effects of Desertification
2.4 Land Degradation Leads to Desertification
2.5 Semi-arid Regions of Andhra Pradesh
2.6 Selection of the Study Area
2.6.1 Selection of the District
2.7 Selection of the Study Area Boundary for Research
2.8 Land Degradation and Desertification in the Semi-arid Region of Anantapur
2.9 Geo-environment
2.9.1 Geology
2.9.2 Geomorphology
2.9.3 Soils
2.9.4 Slope
2.9.5 Hill Shade
2.9.6 Lineaments
2.9.7 Drainage or Hydrology
2.10 Atmospheric Conditions
2.10.1 Climate
2.10.2 Air Temperature
2.10.3 Relative Humidity (RH)
2.10.4 Mean Atmospheric Pressure and Vapor Pressure
2.10.5 Cloudiness
2.10.6 Sunshine
2.10.7 Wind Speeds
2.10.8 Rainfall
2.11 Human Factors
2.12 Land Use Land Cover Types
2.13 Cropping Pattern
2.14 Population Profile
2.15 Conclusion
References
3 Process of Aeolian Action
3.1 Introduction
3.2 Suspension, Saltation, and Surface Creep in Aeolian Process
3.2.1 Suspension
3.2.2 Saltation
3.2.3 Surface Creep
3.3 Wind Direction and Speeds in the Study Area
3.4 Sand Dune Formation
3.5 Ripple Marks
3.5.1 Symmetrical Ripple Marks
3.5.2 Asymmetrical Ripple Marks
3.5.3 Unidirectional Asymmetrical Ripple Marks in the Study Area
3.6 Sand Dunes Present in the Study Area
3.6.1 Barchan Dunes
3.6.2 Parabolic Dunes
3.6.3 Nebkha or Coppice Dunes
3.7 Impact of Aeolian Weathering in Semi-arid Lands
3.8 Conclusion
References
4 Surface Micromorphology of Aeolian Sand Grains
4.1 Introduction
4.2 SEM and EDAX Studies for Visual Disaster of Aeolian Desertification
4.3 SEM and EDAX Analytical Procedure
4.3.1 Sample Preparation
4.3.2 SEM Imaging
4.3.3 EDAX Analysis
4.3.4 Interpretation and Analysis
4.3.5 Reporting
4.4 Sand Sample Collection
4.4.1 SEM/EDAX Analysis for Sand Samples
4.5 Image Snapper for SEM
4.6 EDAX
4.7 Micromorphology of Sand Grains (SEM/EDAX)
4.7.1 SEM Analysis of Sand Grains
4.7.2 Elemental Analysis for Sand Grains (EDAX)
4.8 Conclusion
References
5 Source of Sand for Aeolian Sand Migration
5.1 Introduction
5.2 Source of Sand for Aeolian Sand Migration in Semi-arid Regions
5.2.1 Geological Factors
5.2.2 Climate Factors
5.2.3 Topography Factors
5.2.4 Vegetation Factors
5.2.5 Human Factors
5.3 Sand Migration in the Study Area
5.4 Source of Sand in the Study Area
5.5 Conclusion
References
6 Impact of Desertification in Semi-arid Regions
6.1 Introduction
6.2 Impact of Desertification on Soil
6.3 Impact of Desertification on Biodiversity
6.4 Impact of Desertification on Water Resources
6.5 Impact of Desertification on Agriculture
6.6 Impact of Desertification on Health
6.7 Impact of Desertification in Semi-arid Regions Agriculture
6.8 Impact of Desertification on Agriculture
6.8.1 Soil Degradation
6.8.2 Water Scarcity
6.8.3 Loss of Biodiversity
6.8.4 Visual Hazard of Desertification in Agricultural Lands
6.9 Conclusion
References
7 Long-Term Temporal Analysis of Desertification
7.1 Introduction
7.2 Land Use
7.3 Land Cover
7.4 Land Use and Land Cover Mapping
7.4.1 Data Acquisition
7.4.2 Preprocessing
7.4.3 Image Interpretation
7.4.4 Classification
7.4.5 Validation
7.4.6 Mapping and Reporting
7.5 Importance of Land Use and Land Cover
7.5.1 Urban Planning
7.5.2 Environmental Management
7.5.3 Agriculture and Forestry
7.5.4 Natural Resource Management
7.5.5 Disaster Management
7.5.6 Climate Change Studies
7.5.7 Infrastructure Development
7.5.8 Policy Development
7.6 Remote Sensing Approaches for Land Use and Land Cover Mapping in Desertified Regions
7.6.1 Multispectral Imagery
7.6.2 Hyperspectral Imaging
7.6.3 Thermal Infrared (TIR) Imaging
7.6.4 Synthetic Aperture Radar (SAR)
7.6.5 Light Detection and Ranging (LiDAR)
7.6.6 Change Detection Techniques
7.7 Image Classification Techniques
7.7.1 Supervised Classification Technique
7.7.2 Unsupervised Classification Technique
7.8 Sand Migration and Desertification Status Along the Hagari River Using LULC Technique
7.8.1 Satellite Data Used
7.8.2 Software’s Used
7.8.3 ArcGIS 10.8
7.8.4 Erdas Imagine 2014
7.9 Methodology Adopted
7.10 LULC by Supervised Classification Technique
7.11 Land Use and Land Cover (LULC) Changes Along the Hagari River
7.12 Change Detection Analysis for the Preparation of Sand Migration and Desertification Status Maps (SMDSM)
7.13 Accuracy Assessment
7.14 Conclusion
References
8 Controlling Measures for a Visual Disaster
8.1 Introduction
8.2 Controlling Measures
8.3 Soil Conservation
8.4 Water Conservation
8.5 Reforestation
8.6 Sustainable Agriculture
8.7 Education and Awareness
8.8 Policy and Governance
References

Citation preview

Advances in Geographical and Environmental Sciences

Pradeep Kumar Badapalli Raghu Babu Kottala Padma Sree Pujari

Aeolian Desertification Disaster with Visual Impact in Semi-arid Regions of Andhra Pradesh, South India

Advances in Geographical and Environmental Sciences Series Editors Yukio Himiyama, Hokkaido University of Education, Asahikawa, Hokkaido, Japan Subhash Anand, Department of Geography, University of Delhi, Delhi, India

Advances in Geographical and Environmental Sciences synthesizes series diagnostigation and prognostication of earth environment, incorporating challenging interactive areas within ecological envelope of geosphere, biosphere, hydrosphere, atmosphere and cryosphere. It deals with land use land cover change (LUCC), urbanization, energy flux, land-ocean fluxes, climate, food security, ecohydrology, biodiversity, natural hazards and disasters, human health and their mutual interaction and feedback mechanism in order to contribute towards sustainable future. The geosciences methods range from traditional field techniques and conventional data collection, use of remote sensing and geographical information system, computer aided technique to advance geostatistical and dynamic modeling. The series integrate past, present and future of geospheric attributes incorporating biophysical and human dimensions in spatio-temporal perspectives. The geosciences, encompassing land-ocean-atmosphere interaction is considered as a vital component in the context of environmental issues, especially in observation and prediction of air and water pollution, global warming and urban heat islands. It is important to communicate the advances in geosciences to increase resilience of society through capacity building for mitigating the impact of natural hazards and disasters. Sustainability of human society depends strongly on the earth environment, and thus the development of geosciences is critical for a better understanding of our living environment, and its sustainable development. Geoscience also has the responsibility to not confine itself to addressing current problems but it is also developing a framework to address future issues. In order to build a ‘Future Earth Model’ for understanding and predicting the functioning of the whole climatic system, collaboration of experts in the traditional earth disciplines as well as in ecology, information technology, instrumentation and complex system is essential, through initiatives from human geoscientists. Thus human geoscience is emerging as key policy science for contributing towards sustainability/survivality science together with future earth initiative. Advances in Geographical and Environmental Sciences series publishes books that contain novel approaches in tackling issues of human geoscience in its broadest sense—books in the series should focus on true progress in a particular area or region. The series includes monographs and edited volumes without any limitations in the page numbers.

Pradeep Kumar Badapalli · Raghu Babu Kottala · Padma Sree Pujari

Aeolian Desertification Disaster with Visual Impact in Semi-arid Regions of Andhra Pradesh, South India

Pradeep Kumar Badapalli Department of Geology Yogi Vemana University Kadapa, Andhra Pradesh, India

Raghu Babu Kottala Department of Geology Yogi Vemana University Kadapa, Andhra Pradesh, India

Padma Sree Pujari Department of Geology Government College (Autonomous) Anantapur, Andhra Pradesh, India

ISSN 2198-3542 ISSN 2198-3550 (electronic) Advances in Geographical and Environmental Sciences ISBN 978-981-99-6728-5 ISBN 978-981-99-6729-2 (eBook) https://doi.org/10.1007/978-981-99-6729-2 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore Paper in this product is recyclable.

Contents

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Review of Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.1 Desertification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.2 Land Degradation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.3 Aeolian Desertification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Aeolian Desertification: Processes and Impacts . . . . . . . . . . . . . . . . 1.4 Quantifying Aeolian Desertification . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 Mitigation Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5.1 Aeolian Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 Geo-environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7 Remote Sensing and GIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7.1 Remote Sensing Techniques for Aeolian Desertification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7.2 GIS Applications for Aeolian Desertification . . . . . . . . . . . 1.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 1 2 2 4 5 6 6 7 7 8 9 9 10 10 11

2 Land Degradation and Desertification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Land Degradation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Causes of Land Degradation . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 Consequences of Land Degradation . . . . . . . . . . . . . . . . . . 2.3 Desertification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1 Causes of Desertification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2 Effects of Desertification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Land Degradation Leads to Desertification . . . . . . . . . . . . . . . . . . . . 2.5 Semi-arid Regions of Andhra Pradesh . . . . . . . . . . . . . . . . . . . . . . . . 2.6 Selection of the Study Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6.1 Selection of the District . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 Selection of the Study Area Boundary for Research . . . . . . . . . . . .

13 13 14 15 15 16 16 17 17 18 19 20 21

v

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2.8

Land Degradation and Desertification in the Semi-arid Region of Anantapur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9 Geo-environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9.1 Geology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9.2 Geomorphology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9.3 Soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9.4 Slope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9.5 Hill Shade . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9.6 Lineaments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9.7 Drainage or Hydrology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.10 Atmospheric Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.10.1 Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.10.2 Air Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.10.3 Relative Humidity (RH) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.10.4 Mean Atmospheric Pressure and Vapor Pressure . . . . . . . . 2.10.5 Cloudiness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.10.6 Sunshine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.10.7 Wind Speeds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.10.8 Rainfall . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.11 Human Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.12 Land Use Land Cover Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.13 Cropping Pattern . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.14 Population Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.15 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Process of Aeolian Action . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Suspension, Saltation, and Surface Creep in Aeolian Process . . . . 3.2.1 Suspension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2 Saltation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.3 Surface Creep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Wind Direction and Speeds in the Study Area . . . . . . . . . . . . . . . . . 3.4 Sand Dune Formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Ripple Marks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.1 Symmetrical Ripple Marks . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.2 Asymmetrical Ripple Marks . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.3 Unidirectional Asymmetrical Ripple Marks in the Study Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 Sand Dunes Present in the Study Area . . . . . . . . . . . . . . . . . . . . . . . . 3.6.1 Barchan Dunes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6.2 Parabolic Dunes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6.3 Nebkha or Coppice Dunes . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 Impact of Aeolian Weathering in Semi-arid Lands . . . . . . . . . . . . . . 3.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

22 23 24 27 30 33 35 35 36 38 38 39 39 39 40 40 40 40 42 42 43 44 44 46 51 51 53 53 54 54 56 58 61 61 61 62 62 64 66 69 69 70 71

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4 Surface Micromorphology of Aeolian Sand Grains . . . . . . . . . . . . . . . . 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 SEM and EDAX Studies for Visual Disaster of Aeolian Desertification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 SEM and EDAX Analytical Procedure . . . . . . . . . . . . . . . . . . . . . . . 4.3.1 Sample Preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.2 SEM Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.3 EDAX Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.4 Interpretation and Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.5 Reporting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Sand Sample Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.1 SEM/EDAX Analysis for Sand Samples . . . . . . . . . . . . . . 4.5 Image Snapper for SEM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 EDAX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7 Micromorphology of Sand Grains (SEM/EDAX) . . . . . . . . . . . . . . . 4.7.1 SEM Analysis of Sand Grains . . . . . . . . . . . . . . . . . . . . . . . 4.7.2 Elemental Analysis for Sand Grains (EDAX) . . . . . . . . . . 4.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

73 73

5 Source of Sand for Aeolian Sand Migration . . . . . . . . . . . . . . . . . . . . . . . 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Source of Sand for Aeolian Sand Migration in Semi-arid Regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.1 Geological Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.2 Climate Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.3 Topography Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.4 Vegetation Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.5 Human Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Sand Migration in the Study Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 Source of Sand in the Study Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

87 87

6 Impact of Desertification in Semi-arid Regions . . . . . . . . . . . . . . . . . . . . 6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Impact of Desertification on Soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Impact of Desertification on Biodiversity . . . . . . . . . . . . . . . . . . . . . 6.4 Impact of Desertification on Water Resources . . . . . . . . . . . . . . . . . 6.5 Impact of Desertification on Agriculture . . . . . . . . . . . . . . . . . . . . . . 6.6 Impact of Desertification on Health . . . . . . . . . . . . . . . . . . . . . . . . . . 6.7 Impact of Desertification in Semi-arid Regions Agriculture . . . . . . 6.8 Impact of Desertification on Agriculture . . . . . . . . . . . . . . . . . . . . . . 6.8.1 Soil Degradation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.8.2 Water Scarcity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.8.3 Loss of Biodiversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

95 95 96 96 96 96 97 97 97 97 98 98

74 75 76 76 76 76 77 77 77 78 78 78 79 84 85 85

88 88 89 89 90 90 91 91 92 93

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Contents

6.8.4

Visual Hazard of Desertification in Agricultural Lands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.9 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Long-Term Temporal Analysis of Desertification . . . . . . . . . . . . . . . . . . 7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Land Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Land Cover . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 Land Use and Land Cover Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4.1 Data Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4.2 Preprocessing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4.3 Image Interpretation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4.4 Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4.5 Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4.6 Mapping and Reporting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5 Importance of Land Use and Land Cover . . . . . . . . . . . . . . . . . . . . . 7.5.1 Urban Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5.2 Environmental Management . . . . . . . . . . . . . . . . . . . . . . . . . 7.5.3 Agriculture and Forestry . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5.4 Natural Resource Management . . . . . . . . . . . . . . . . . . . . . . 7.5.5 Disaster Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5.6 Climate Change Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5.7 Infrastructure Development . . . . . . . . . . . . . . . . . . . . . . . . . 7.5.8 Policy Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6 Remote Sensing Approaches for Land Use and Land Cover Mapping in Desertified Regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6.1 Multispectral Imagery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6.2 Hyperspectral Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6.3 Thermal Infrared (TIR) Imaging . . . . . . . . . . . . . . . . . . . . . 7.6.4 Synthetic Aperture Radar (SAR) . . . . . . . . . . . . . . . . . . . . . 7.6.5 Light Detection and Ranging (LiDAR) . . . . . . . . . . . . . . . . 7.6.6 Change Detection Techniques . . . . . . . . . . . . . . . . . . . . . . . 7.7 Image Classification Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.7.1 Supervised Classification Technique . . . . . . . . . . . . . . . . . . 7.7.2 Unsupervised Classification Technique . . . . . . . . . . . . . . . . 7.8 Sand Migration and Desertification Status Along the Hagari River Using LULC Technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.8.1 Satellite Data Used . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.8.2 Software’s Used . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.8.3 ArcGIS 10.8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.8.4 Erdas Imagine 2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.9 Methodology Adopted . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.10 LULC by Supervised Classification Technique . . . . . . . . . . . . . . . . .

98 99 99 101 101 102 102 103 103 103 103 104 104 104 104 104 105 105 105 105 105 106 106 106 106 107 107 107 107 108 108 108 109 110 110 112 112 113 113 113

Contents

7.11 Land Use and Land Cover (LULC) Changes Along the Hagari River . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.12 Change Detection Analysis for the Preparation of Sand Migration and Desertification Status Maps (SMDSM) . . . . . . . . . . 7.13 Accuracy Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.14 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Controlling Measures for a Visual Disaster . . . . . . . . . . . . . . . . . . . . . . . 8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Controlling Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 Soil Conservation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4 Water Conservation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5 Reforestation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.6 Sustainable Agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.7 Education and Awareness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.8 Policy and Governance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

ix

115 116 118 120 120 123 123 124 126 127 128 129 131 132 133

Abbreviations

AHP ASTER CI DEM DN DSM EDAX ESRI ETM ETM+ FAO GE GeoTIFF GIS GM GPS GSI IIRS ISRO LD LSA LST LULC MCDM NASA NBSS & LUP NDBI NDSI NDVI NDWI NRSA

Analytic Hierarchy Process Advanced Space Borne Thermal Emission and Reflection Consistency Index Digital Elevation Model Digital Number Desertification Status Map Energy Dispersive X-Ray Analysis Environmental Systems Research Institute Enhanced Thematic Mapper Enhanced Thematic Mapper Plus Food and Agriculture Organization Geology Geographic Tagged Image File Format Geographical Information System Geomorphology Global Positing System Geological Survey of India Indian Institute of Remote Sensing Indian Space Research Organization Land Degradation Land Suitability Analysis Land Surface Temperature Land Use Land Cover Multiple Criteria Decision-Making National Aeronautics and Space Administration National Bureau of Soil Survey and Land Use Planning Normalized Difference Buildup Index Normalized Difference Salinity Index Normalized Difference Vegetation Index Normalized Difference Water Index National Remote Sensing Agency xi

xii

NRSC OLI RI RS SAVI SEM SL SOI SOM SPI Sq Km TGSI TIRS TM TPN UNCCD UNDP UNEP UNFCCC USGS WAD

Abbreviations

National Remote Sensing Center Operational Land Imager Random Index Remote Sensing Soil Adjusted Vegetation Index Scanning Electron Microscope Slope Survey of India Soil Organic Matter Standardized Precipitation Index Square Kilometers Topsoil Grain Size Index Thermal Infrared Sensor Thematic Mapper Thematic Program Network United Nations Convention to Combat desertification United Nations Development Program United Nations Environment Program United Nations Framework Convention on Climate Change United State Geological Survey World Atlas of Desertification

List of Figures

Fig. 2.1 Fig. 2.2 Fig. 2.3 Fig. 2.4 Fig. 2.5 Fig. 2.6 Fig. 2.7 Fig. 2.8 Fig. 2.9 Fig. 2.10 Fig. 2.11 Fig. 2.12 Fig. 3.1 Fig. 3.2 Fig. 3.3 Fig. 3.4 Fig. 3.5 Fig. 3.6 Fig. 3.7 Fig. 4.1 Fig. 4.2

Location map of the study area . . . . . . . . . . . . . . . . . . . . . . . . . . . Geology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Geomorphology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Soil types in the study area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Slope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hill shade . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lineaments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Drainage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rainfall from 1990 to 2020 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Monthly average rainfall for the past three decades of the study area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LULC of the study area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Population density map of the study area . . . . . . . . . . . . . . . . . . . Aeolian desertification happening along the Hagari River in the semi-arid regions of Andhra Pradesh, India . . . . . . . . . . . . Aeolian transportation process . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anemometer readings for wind speeds along the Hagari River . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spatial distribution of wind speeds in the study region . . . . . . . . Sand dune formation process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sand dune moment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Symmetrical and asymmetrical ripple marks . . . . . . . . . . . . . . . . SEM/EDAX equipment. a and b smart coater and specimen chamber . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . High-resolution SEM panoramic image of sand samples. a, b, c, and d: are the 500 µm magnification SEM imageries. Desert varnish can be seen in the samples. d: Quartz, feldspar, and tourmaline sand grains . . . . . . . . . . . . . .

22 26 28 32 34 36 37 38 41 42 43 45 52 55 56 59 60 60 61 75

80

xiii

xiv

Fig. 4.3

Fig. 4.4

Fig. 4.5

Fig. 5.1

Fig. 7.1 Fig. 7.2 Fig. 7.3 Fig. 7.4 Fig. 7.5 Fig. 7.6 Fig. 7.7

Fig. 7.8

List of Figures

High-resolution SEM panoramic image of sand samples with 200 and 100 µm. a, b show oval to semi-oval-shaped sand grains. c: Quartz grain with an oval shape with a conchoidal fracture. d: V-shaped sand grain dominants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . High-resolution SEM panoramic image of sand samples with 100 µm. a: Well-rounded quartz grain with high relief. b: Rounded quartz grain with a conchoidal fracture. c: Subrounded sand grain with less relief d: Subrounded silica dissolution during the transportation . . . . . . . . . . . . . . . . . . High-resolution SEM panoramic image of sand samples with 20, 50, 5 µm. a: Irregular depressions on the sand grain. b: Smooth surface of a sand grain. c: Mechanical disintegrated surface on sand grain. d: Dissolute surfaces with irregular pit shapes on sand grains . . . . . . . . . . . . . . . . . . . . . Satellite images showing prominent locations (arrows) of sand exposures (light-colored) on the right bank of River Hagari in March 1990 and April 2020 . . . . . . . . . . . . . . . . . . . . . . Landsat 4–5 TM/MSS bands, wavelength, and spatial resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Landsat 7 ETM+ bands, wavelength, and spatial resolution . . . . Landsat 8 OLI and TIRS bands, wavelength, and spatial resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Methodology flowchart for the sand desertification along the Hagari River . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ground signatures of Landsat imageries . . . . . . . . . . . . . . . . . . . . SMDSM for the years 1990, 2000, 2010, and 2020 . . . . . . . . . . . Sand migration and desertification status along the Hagari River. a Hagari River b Sand migration into agricultural fields and desertified entire agricultural field c Sand dune formation in the agricultural lands d Vegetation cover filled with migrated sands e Sand dune encroachment f Roads are filled with migrated sands by the action of wind g Hagari/Vedavathi Cannel flows along the Hagari River h Reduction of sand dune encroachment along the Hagari River by DWAMA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Newspaper articles on sand migration and desertification happening in the semi-arid regions of Anantapur district of southern India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

81

83

84

92 111 111 112 114 115 117

117

119

List of Tables

Table 2.1 Table 2.2 Table 2.3 Table 2.4 Table 3.1 Table 4.1 Table 4.2 Table 4.3 Table 7.1

Geological succession of Anantapur district . . . . . . . . . . . . . . . . . Geology of the study area (Ramam 1988) . . . . . . . . . . . . . . . . . . Geomorphology of the study area . . . . . . . . . . . . . . . . . . . . . . . . . Soils of the study area (Kale et al. 2020) . . . . . . . . . . . . . . . . . . . GPS locations, elevation, and anemometer wind speeds . . . . . . . Sand sample locations and migration happening in villages in the study area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Surface micromorphology and rate of sand migration and desertification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . EDAX analysis of sand grains . . . . . . . . . . . . . . . . . . . . . . . . . . . . Change detection analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

25 27 28 30 58 79 82 85 118

xv

List of Plates

Plate 3.1 Plate 3.2 Plate 3.3 Plate 3.4 Plate 3.5 Plate 3.6 Plate 3.7 Plate 3.8 Plate 3.9 Plate 3.10 Plate 3.11 Plate 3.12 Plate 3.13

Anemometer readings collection in the field, along the Hagari River . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wind direction and ripple formation in the study area . . . . . . . . Unidirectional asymmetrical ripple marks in the study area . . . Ripple marks along the Hagari River . . . . . . . . . . . . . . . . . . . . . . Sand migration in the form of ripple marks to the agricultural field in the study region . . . . . . . . . . . . . . . . . Asymmetrical ripple forms in the study region . . . . . . . . . . . . . . Asymmetrical ripple migrated to agricultural field and formed desert environment in the study area . . . . . . . . . . . . Asymmetrical ripple marks observation in the field . . . . . . . . . . Small-sized unidirectional asymmetrical ripple marks in the study area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Barchan sand dune in the study area . . . . . . . . . . . . . . . . . . . . . . Height mound Barchan sand dunes in the study area . . . . . . . . . Parabolic sand field in the study area . . . . . . . . . . . . . . . . . . . . . . Nebkha sand dunes with plant cover sand sheets in the study area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

57 62 63 63 64 64 65 66 67 68 68 69 70

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Chapter 1

Introduction

Abstract This chapter provides an extensive review of the literature on a variety of topics, including aeolian processes, the geo-environment, land degradation, and the use of remote sensing and Geographic Information System (GIS) technology. Ecosystems and civilizations are faced with serious difficulties as a result of land degradation, which includes a variety of processes such as soil erosion, deforestation, and desertification. Land degradation is exacerbated in arid and semi-arid locations by the aeolian process, which is fueled by wind erosion and sediment movement. GIS and remote sensing are useful tools for tracking and evaluating aeolian processes and land degradation. This review focuses on applications and developments in remote sensing and GIS for efficient land management and conservation techniques. It examines major research that has advanced our understanding of these linked phenomena. Keywords Geo-environment · Aeolian · Land degradation · Desertification

1.1 Introduction An important environmental problem, land degradation has an impact on ecosystems and communities all over the world. It describes the decline in the productivity and ecological capabilities of the land brought on by a number of factors, such as soil erosion, deforestation, desertification, and pollution of the environment. For sustainable land management and ecosystem protection, it is essential to comprehend the dynamics of land degradation and its effects on the geo-environment. In especially in arid and semi-arid environments, the aeolian process—driven by wind erosion and sediment transport—plays a crucial role in land degradation. Desertification, or the conversion of formerly fruitful land into desert-like environments, is a result of aeolian processes. Effective land management and mitigation methods depend on the assessment and monitoring of aeolian processes and their effects.

This chapter deals with the previous literature on the visual hazard of land degradation and desertification. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 P. K. Badapalli et al., Aeolian Desertification, Advances in Geographical and Environmental Sciences, https://doi.org/10.1007/978-981-99-6729-2_1

1

2

1 Introduction

Innovations in remote sensing and Geographic Information Systems (GIS) have become effective instruments for researching aeolian processes, the geoenvironment, and land degradation. With the use of these technologies, geographical data can be collected, analyzed, and visualized, revealing important details on the degree and patterns of land degradation. The linkages between land degradation, the geo-environmental, and aeolian processes, and the use of remote sensing and GIS in monitoring and controlling these environmental phenomena are examined in this literature review. We want to improve our knowledge of the intricate dynamics involved in land degradation and inform sustainable land management practices by reviewing important works in these domains.

1.2 Review of Literature A review of literature helps us to understand the research topic. We attempt the understanding of methodology after a brief study of the many researchers related to the present work. These reviews of the literature will aid researchers in their development and accessibility for doing reliable research. For this study, all literatures relating to land degradation, drought, dryness, desertification, environment, climate, remote sensing, and GIS were pursued.

1.2.1 Desertification A natural component of an ecosystem is land. Soil, water, flora and fauna, microclimate, and physiography are some of the factors that may be described in terms of physical characteristics. Humankind uses the land for a variety of things, including agriculture, the development of forests and pastures, and infrastructure. In addition to these so-called economic applications, the land also serves ecological (environmental regulatory) purposes. Both of these have to do with reducing global warming and serving as a sink for several hazardous substances. Since soil is a part of the land, its uses and functions are included in those that are attributed to land. Land degradation in arid, semi-arid, and dry subhumid environments brought on by climate changes and human activity is known as desertification. There are several ways to perceive desertification. The literature has more than 100 formal definitions of desertification. These definitions encompass a wide range of topics, several spatial and chronological ranges of issues, and frequently imply contradictory interpretations. In general, the emphasis placed on the three separate aspects of the issue—ecological, climatic, and human—differs in these diverse definitions of desertification (Reynolds et al. 2011). The French scientist and explorer Louis Lavauden originally used the word “desertification” in 1927, and the French forester Andre Aubreville first popularized it in 1949. The latter is typically regarded as the term’s originator. In order to illustrate

1.2 Review of Literature

3

desertification, early specialists popularized the concept of the “advancing desert,” “moving desert,” or “encroaching desert.” The end result of this “expansion of the desert” idea was Lamprey’s claim that the Sahara was moving at a speed of 5.5 km/ year. According to the UNCOD definition of desertification accepted in 1977, it is “the decrease or loss of the biological capacity of the land and can eventually result in desert-like conditions”. It is a symptom of general ecosystem degradation and has reduced or eliminated biological potential, or plant and animal production, for many uses at a time when productivity must increase to sustain expanding populations seeking development. The target region of application of the teer desertification was not specifically stated in the UNCOD description. In other words, no mention of the climate zones where desertification occurs was made (Kannan 2012; Rechkemmer 2004). According to 1990 UNEP Committee meeting on global evolution of desertification a new concept was evaluated that produced a new definition that equated desertification with land degradation and specified the climate zones to which the term applies. It suggests new definition: Desertification is land degradation in arid, semi-arid, and dry subhumid areas resulting from adverse human impact (Dregne 2020). Desertification is defined as a long-term state of land degradation in which the area is no longer suitable for vegetation production, and it is primarily caused by climatic variables, human intrusion, and long-term geological processes. Because of the disastrous consequences on the soil and plants, the event has gained international attention over the past decades. Desertification happens continuously. Desertification is defined as the reduction in the biological capacity of the land, which might result in a desert-like situation, according to the United Nations conference on Desertification (UNCOD) addressing in Nairobi. The most often-used definition of desertification is “land degradation due to climatic variations and human activities in arid, semi-arid, and dry subhumid areas”. Arid and semi-arid environments are frequently characterized by drought and desertification. The world’s dryland can be categorized as either dry (based on climate) or desert (based on surface physical features, such as vegetation and landforms). We shall continue to employ the climatic categorization that UNESCO introduced in 1979 for the purposes of this study. Thus, deserts can be classified as semi-arid when they get less than 550 mm of precipitation, arid when they receive less than 250 mm, and hyper-arid when they receive less than 25 mm. One of the main causes of land degradation that is occurring worldwide is desertification, which has emerged as a serious conservation concern (Reynolds et al. 2011). Desertification emerges as one of the most pressing environmental and developmental challenges of the twenty-first century. The world’s drylands, inhabited by approximately two billion people, face a grave threat to their biological productivity due to the progressive degradation of soils and other natural resources. This process sets in motion a vicious cycle of geo-environmental deterioration, impoverishment,

4

1 Introduction

migration, and conflicts, often destabilizing the political landscape of affected countries and regions. It is alarming to note that nearly half of all armed conflicts in existence exhibit environmental causal factors specific to drylands. Desertification represents a detrimental phenomenon characterized by the gradual and inconspicuous decline in the land’s ability to sustain productivity over the course of several years. Ultimately, it leads to the creation of barren wastelands devoid of any practical utility. The United Nations Convention to Combat Desertification (UNCCD) states that “desertification emerges through complex interactions among physical, biological, political, social, cultural, and economic variables, rather than from a single, identifiable cause. It is thought that the signs and causes of desertification differ from place to location, depending on the meteorological and social settings. Even while it happens everywhere, its effects are most severe in poor nations in the world’s arid and semi-arid regions.

1.2.2 Land Degradation Drylands encompass approximately 228.3 million hectares, constituting about 69.6% of India’s total land area. Among these, land degradation affects an estimated 105.48 million hectares, which accounts for approximately 32.07% of the country’s entire land area. Moreover, desertification affects an area of 81.45 million hectares, equivalent to around 24.78% of India’s geographical expanse (Centre 2005). The degradation of delicate drylands has far-reaching consequences, impacting 25% of the Earth’s land area and jeopardizing the livelihoods of 900 million individuals across one hundred nations. Within these drylands, desertification disproportionately affects one-sixth of the global population, leaving 800 million people without sufficient access to food resources. India, in particular, experiences the brunt of this problem. However, the exclusive focus on soil and water conservation as the singular solution to address dryland degradation is limiting the potential of national efforts in combating this issue. Drylands are found on all continents and makeup approximately half of the world’s landmass, according to UNEP. However, these drylands are not distributed equally across wealthy and poor nations: just 28% of the world’s dryland area is found in industrial nations, while 72% is in developing ones. Similar to how the percentage of drylands populated by developing nations rises as an area becomes arider (from dry subhumid to hyper-arid), reaching over 100% in the instance of hyper-arid regions. In other words, nearly 100% of hyper-arid areas are in developing countries, and for arid regions, it is more than 90%. Consequently, the majority of dryland people live in developing countries. According to UNCCD, land degradation refers to a decline in the biological or economic productivity and complexity of rangelands, pastures, forests, and woods as well as irrigated or rainfed farmland. Food insecurity and poverty are frequently related to land degradation in a cause-and-effect manner.

1.2 Review of Literature

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According to UNEP, the distinction between “soil” and “land” is unclear, and the terms “land degradation” and “desertification” lack clear differences. Land degradation primarily occurs in arid, semi-arid, and subhumid regions as a result of human activities, ultimately leading to desertification. However, the definition of desertification is too limited, as significant land degradation caused by human activities can also take place in temperate humid regions and the humid tropics. In reality, desertification is not a distinct form of land degradation, but rather the culmination of various degradation processes that have negatively impacted the land. The term “desertification” evokes an emotional response, suggesting the encroachment of desert sand dunes onto neighboring areas, which rarely occurs in practice. According to FAO (1979) (Food and Agriculture Organization), “Land degradation is a process which lowers the current or potential capability of soils to produce (quantitatively and/or qualitatively) goods or services.” According to UNEP “Land degradation implies reduction of resource potential by a combination of processes acting on land.” Land degradation is becoming a major issue in both developing and developed countries. There is a prevalent assumption that poverty causes (and is caused by) land degradation. As a result of this nexus, land continues to be degraded, while people grow increasingly destitute. This tendency will continue until their resistance is destroyed, leaving them with slight choice except to migrate within their own countries to places with greater prospects or to migrate to developed countries. The possibility of widespread migration as a result of land degradation was considered during the Algiers Desertification Conference. Soil degradation refers to the deterioration in the productive capacity of the soil caused by soil erosion and alterations in its hydrological, biological, chemical, and physical properties. It is defined as a process that diminishes the present and/or future ability of the soil to produce goods or services, both in terms of quantity and quality (FAO 1979). The study conducted by FAO, UNEP, and UNESCO (FAO 1979) identified six distinct categories of soil degradation processes: water erosion, wind erosion, waterlogging and excessive salt accumulation, chemical degradation, physical degradation, and biological degradation. Land degradation and desertification are one of the worst threats to the southcentral part of Anantapur district in Andhra Pradesh state of India. Climatic data for the period 1990–2020 indicated that no significant changes occurred in the longterm annual rainfall in the study region, whereas significant increase in the longterm surface temperature was found. This mainly contributed to the desertification processes.

1.2.3 Aeolian Desertification A significant environmental problem that affects dry and semi-arid regions worldwide is aeolian desertification, also known as wind-induced desertification. This literature review aims to present a thorough overview of the aeolian process and its

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contribution to desertification, highlighting significant research that has advanced our knowledge of this phenomenon. This study emphasizes the significance of tackling this environmental concern by looking at the aeolian desertification processes, repercussions, and potential mitigation techniques.

1.3 Aeolian Desertification: Processes and Impacts A variety of phenomena, such as wind erosion, sand migration, and land deterioration, are included in aeolian desertification. In-depth research on the mechanisms behind aeolian desertification was undertaken by Zhang and Huisingh (2018), with a focus on the connections between wind erosion, sand transport, and the ensuing land degradation. Their study clarified the negative effects of aeolian desertification on the local ecosystems, plant cover, and soil fertility. It is essential to know the geomorphological features of aeolian desertification in order to fully appreciate its wider ramifications. In areas that are prone to desertification, Dong et al. (2017) concentrated on aeolian processes and landforms. Their analysis emphasized how wind erosion produces aeolian landforms like sand sheets and dunes. Dong et al. shed important light on the morphological aspects of aeolian desertification by describing the origin and evolution of these characteristics.

1.4 Quantifying Aeolian Desertification Aeolian desertification must be accurately quantified in order to be tracked, its severity to be determined, and effective mitigating measures to be developed. In a thorough review, Li et al. (2016) examined remote sensing and Geographic Information System (GIS)-based quantification methodologies. Their study showed how satellite imagery and spatial analysis may be used to map impacted regions, monitor desertification processes, and determine the geographical extent and severity of aeolian desertification. Wang et al. (2015) conducted a detailed assessment on measuring the environmental effects of aeolian desertification as part of a related study. They looked at several evaluation techniques to gauge how wind erosion affects the pace of soil erosion, the health of the plants, and dust emissions. Researchers and decisionmakers can better understand the severity of aeolian desertification and develop effective strategies to lessen its consequences by measuring these impacts.

1.5 Mitigation Strategies

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1.5 Mitigation Strategies Effective mitigation measures that reduce wind erosion and restore damaged landscapes are needed to address aeolian desertification. Various mitigation strategies based on sustainable land management techniques were presented by Zhang and Huisingh (2018). Their analysis emphasized the need of planting trees, building windbreaks, and restoring vegetation in order to lessen wind erosion, stabilize soils, and encourage ecosystem recovery. Additionally, it is essential to counteract aeolian desertification by implementing sensible land use regulations and management practices. Rotational grazing, terracing, and contour plowing are examples of sustainable land management techniques that can improve soil conservation and reduce wind erosion. Studies have looked at these practices, with Zhang and Huisingh (2018) highlighting the need of implementing all-encompassing strategies to stop aeolian desertification.

1.5.1 Aeolian Process Aeolian processes occur in a range of settings, including coastlines, semi-arid regions, dry regions, and agricultural fields, and involve erosion, movement, and deposition of sediment by the wind. A lack of vegetation, a supply of fine material (clay, silt, and sand size), and high winds are all common aspects of these habitats. The emission and/or mobilization of dust, as well as the development of sand dunes, are caused by aeolian processes. Despite the claims of many early researchers, wind erosion of bedrock is not a substantial process in most areas. There is limited vegetation in dry and semi-arid regions due to little rainfall and high rates of evaporation. In these regions, fragile ecosystems that coexist with the dry environment’s natural processes are made up of interconnected sediments, flora, and animals. The most important aeolian processes are those caused by wind action on exposed surface sediments, which include erosion, movement, and sediment deposition. The amplitude of these processes is influenced by the wind speed, the size of the surface sediments, the surface protection (such as plants or pavement in the desert), and the contour of the terrain. In semi-arid deserts, running surface water no longer plays a substantial role in sediment movement and deposition. Aeolian activity, in which wind is the primary agent of erosion, movement, and sedimentation, is often dominant in deserts. Particulate material comes from the breakdown of rock caused by both mechanical and chemical weathering in this environment. The particles are exposed to erosion agents as a result of the disintegration, which causes additional loosening of the particles from the rock.

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1.6 Geo-environment The lithosphere, hydrosphere, and atmosphere make up the Earth system. Aside from these, the biosphere is a fourth component that completes the Earth system. Landforms are an essential component of the lithosphere, and they have a significant impact on both man and the environment. As a result, landform investigations have been the geo-principal science’s activity since its establishment. Geomorphology, on the other hand, is a relatively new discipline that studies the genesis and evolution of landforms. When the physical features of the environment, such as land, water, soil, and so on, are regarded as a system to comprehend interrelationships and interconnections among them, as well as their entire effect on man and the environment, it is referred to as “geo-environment.” It focuses on the geohazard issue in particular. Geohazards are, in reality, a component of an area’s geo-environment. Furthermore, as the problem of geohazards grows, posing a significant threat to both man and the environment, geoscientists have grown increasingly interested in geo-environmental research. Geologists and environmentalists are responsible for studying the environment and its link to development and planning. The environment is the source of all resources and the foundation of all living forms. Man is a major contributor to environmental change and harm, which frequently results in environmental degradation. However, knowledge of the “geo-environment” is required to comprehend the importance and function of the environment in planning and development. Because “geo-environment” is inextricably linked to the study of geomorphology, geomorphologists have recently begun to take a strong interest in its assessment, notably in applied geomorphology and, more specifically, in environmental geomorphology. Although the word geo-environment is new, the holistic approach of seeing the physical world as a system (one entity) is not. Landforms (with all of their properties), rocks, soil, hydrology, and flora are all part of the geo-environment (as manifestation of the first four elements, and climate). Geo-environment is the environment that is directly generated by the Earth (geo) and its properties, or by the land-bound aspects of the environment, as the case may be. Actually, the word “geo-environment” has its origins in the term “landscape ecology,” which was coined by German geographer– ecologist Troll (1968). He expanded on this notion to propose another well-known concept known as geo-ecology, which focuses on the geo-environmental variables that influence the environment and, in turn, man. According to Badapalli et al. (2022), “Geo-environment study includes two aspects: (i) assessment, mapping, and combating various geological and geomorphological hazards, and (ii) conversion of landscape for optimum benefits. Not all of these initiatives can be completed until the geo-environment of a location is considered, which adds a holistic dimension to the study of natural landscapes, where landforms are the most important and fundamental component.”

1.7 Remote Sensing and GIS

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1.7 Remote Sensing and GIS In hot and semi-arid regions, aeolian desertification—a process driven by wind erosion and soil degradation—poses serious environmental problems. Technologies for remote sensing and Geographic Information System (GIS) have become effective instruments for tracking and evaluating aeolian desertification. In order to map impacted regions, assess the severity of aeolian desertification, and analyze the spatial and temporal patterns of aeolian processes, this literature review seeks to offer an overview of the uses of remote sensing and GIS. We illustrate the efficiency of these technologies in comprehending and addressing this complicated environmental issue by looking at significant research in the field (Arya 2014; Aubréville 1949; Chen et al. 2006; Hilmi and Sedahmad 2014; Lillesand et al. 2015; Mainguet and Mainguet 1994; Xiao et al. 2006).

1.7.1 Remote Sensing Techniques for Aeolian Desertification Remote sensing offers a unique vantage point for studying aeolian processes and their impacts on land degradation. Various remote sensing techniques, including satellite imagery and aerial photography, have been employed to monitor and analyze the spatial and temporal dynamics of aeolian desertification. 1.7.1a Satellite Imagery: Satellite imagery provides a comprehensive view of aeolian desertification at different scales. Li et al. (2016) reviewed the use of satellite imagery, such as Landsat and MODIS data, for mapping and monitoring aeolian processes. These sensors capture multispectral information, allowing researchers to detect changes in land cover, vegetation density, and soil properties. By analyzing different spectral bands, vegetation indices, and surface temperature, researchers can assess the severity of aeolian desertification. 1.7.1b Unmanned Aerial Vehicles (UAVs): UAVs, commonly known as drones, have gained popularity in recent years for their ability to collect high-resolution imagery. UAVs equipped with optical or thermal sensors can capture detailed data of aeolian landforms, such as sand dunes and erosion features. These datasets enable researchers to study the morphological characteristics of aeolian landforms and their temporal changes with greater precision. 1.7.1c LiDAR (Light Detection and Ranging): LiDAR technology utilizes laser pulses to measure the distance between the sensor and the Earth’s surface. LiDAR data provides highly accurate and detailed elevation information, enabling the characterization of aeolian landforms and their three-dimensional analysis. LiDAR has been employed to study dune migration rates, erosion rates, and the volume of sediment transport.

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1.7.2 GIS Applications for Aeolian Desertification Geographic Information System (GIS) technology complements remote sensing data by providing spatial analysis and modeling capabilities. GIS has been extensively used to integrate remote sensing data, field measurements, and ancillary information for aeolian desertification mapping and analysis. 1.7.2a Land Cover Mapping and Change Detection: GIS makes it easier to categorize and map the changes in land use and cover brought on by aeolian desertification. GIS enables the identification and measurement of regions impacted by aeolian processes by incorporating satellite images. The ability to detect temporal changes in land cover and identify regions vulnerable to aeolian desertification is made possible by change detection methods like post-classification comparison and image differencing (Gao et al. 2020). 1.7.2b Spatial Analysis of Aeolian Processes: Spatial investigation of aeolian processes, such as wind erosion, sediment transport, and dune migration, is made possible by GIS. Researchers may predict wind erosion susceptibility, identify places prone to erosion, and evaluate the possible effects of aeolian processes on ecosystems and infrastructure by combining meteorological data, topographical parameters, and land cover information (Wang et al. 2021). 1.7.2c Spatial Modeling and Decision Support Systems: In the management and planning of aeolian desertification, geographical modeling and decision support systems based on GIS are essential. These models mimic and forecast the possible spread of aeolian desertification by taking into account a variety of variables, including geography, land cover, wind patterns, and soil characteristics. Using decision support systems, one may locate appropriate areas to carry out preventative actions like windbreak building and vegetation regeneration (Chen et al. 2020).

1.8 Conclusion A score of researchers have reflected their thoughts on untold miseries of land degradation and desertification and they are applied to Anantapur, Andhra Pradesh’s semiarid region, which has been the typical subject area for significant understanding of topics related to degradation, desertification, geo-environment, and atmospheric conditions. The research by the authors has emphasized the negative consequences of unsustainable farming methods, deforestation, and excessive water resource use, which result in soil erosion, loss of plant cover, and reduced biodiversity. A major issue, desertification has an effect on socioeconomic circumstances, water availability, and agricultural output. To lessen the hazards of desertification, researchers have stressed the significance of sustainable land management practices, afforestation, and water conservation techniques. To comprehend how they affect hydrology

References

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and soil composition, the geo-environmental aspects, including geological formations and landforms, have been investigated thoroughly. The need for climate change adaptation measures has been emphasized by studies that have examined the region’s rainfall patterns, temperature changes, and implications of climate change. Promoting sustainability and resilience in the semi-arid areas of Anantapur would need to move forward with the implementation of these study findings through workable policies and initiatives. There are umpteen number of references related to this natural disaster, and they are used in appropriate places in the text of this monograph.

References Arya VS (2014) Desertification change analysis in Siwalik hills of Haryana using geo-informatics Aubréville A (1949) Climats, forêts et désertification de l’Afrique tropicale. Société d’éditions géographiques, maritimes et coloniales, Paris Badapalli PK, Nakkala AB, Kottala RB, Gugulothu S (2022) Geo environmental green growth towards sustainable development in semi-arid regions using physicochemical and geospatial approaches. Environ Sci Pollut Res 1–18 Chen XL, Zhao HM, Li PX, Yin ZY (2006) Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sens Environ 104(2):133–146 Chen X, Qi Z, Gui D, Sima MW, Zeng F, Li L, Gu Z et al (2020) Evaluation of a new irrigation decision support system in improving cotton yield and water productivity in an arid climate. Agric Water Manag 234:106139 Dong Z, Hu G, Qian G, Lu J, Zhang Z, Luo W, Lyu P (2017) High-altitude aeolian research on the Tibetan Plateau. Rev Geophys 55(4):864–901 Dregne HE (2020) Desertification assessment. In: Methods for assessment of soil degradation. CRC Press, pp 441–458 FAO (1979) 1978 FAO production yearbook 32. Food and Agriculture Organisation, Rome Gao L, Wang X, Johnson BA, Tian Q, Wang Y, Verrelst J, Gu X et al (2020) Remote sensing algorithms for estimation of fractional vegetation cover using pure vegetation index values: a review. ISPRS J Photogrammetry Remote Sens 159:364–377 Hilmi HSM, Sedahmad SA (2014) Land use land cover change detection: a case study: Khartoum state, Sudan, 1972–2006. Glob J Environ Sci Technol 3(1):088–094 Kannan A (2012) Global environmental governance and desertification: a study of Gulf Cooperation Council countries. Concept Publishing Company Li Q, Zhang C, Shen Y, Jia W, Li J (2016) Quantitative assessment of the relative roles of climate change and human activities in desertification processes on the Qinghai-Tibet Plateau based on net primary productivity. CATENA 147:789–796 Lillesand T, Kiefer RW, Chipman J (2015) Remote sensing and image interpretation. Wiley Mainguet M, Mainguet M (1994) New developments in desertification (September 1993). Desertification Nat Background Hum Mismanag 286–293 Rechkemmer A (2004) Postmodern global governance: the United Nations convention to combat desertification, vol 71. Nomos Verlagsgesellschaft Mbh & Company Reynolds JF, Grainger A, Stafford Smith DM, Bastin G, Garcia-Barrios L, Fernández RJ, Zdruli P et al (2011) Scientific concepts for an integrated analysis of desertification. Land Degradation Dev 22(2):166–183 Troll C (1968) Geo-ecology of the mountainous regions of the tropical Americas Wang T, Xue X, Zhou L, Guo J (2015) Combating aeolian desertification in northern China. Land Degrad Dev 26(2):118–132

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Wang X, Li X, Cai D, Lou J, Li D, Liu F (2021) Salinification and salt transports under aeolian processes in potential desertification regions of China. Sci Total Environ 782:146832 Xiao J, Shen Y, Ge J, Tateishi R, Tang C, Liang Y, Huang Z (2006) Evaluating urban expansion and land use change in Shijiazhuang, China, by using GIS and remote sensing. Landsc Urban Plan 75(1–2):69–80 Zhang Z, Huisingh D (2018) Combating desertification in China: monitoring, control, management and revegetation. J Clean Prod 182:765–775

Chapter 2

Land Degradation and Desertification

Abstract Land degradation and desertification are significant environmental challenges that affect many parts of the world, particularly in arid and semi-arid regions. Land degradation refers to the deterioration of land quality due to human activities and natural processes, while desertification refers to the process of land degradation that results in the transformation of productive land into arid or desert-like landscapes. The causes of land degradation and desertification are complex, including unsustainable land use practices, climate change, and natural disasters. The impacts of these processes are significant, including declining agricultural productivity, loss of biodiversity, food insecurity, and poverty. Addressing these challenges requires a multidisciplinary approach, incorporating sustainable land management practices, water conservation and management, and climate change adaptation measures. Through the development of innovative solutions and sustainable management practices, it is possible to mitigate the negative impacts of land degradation and desertification and promote a healthier and more resilient planet. Keywords Semi-arid · Landscape · Climate change · Sustainable

2.1 Introduction Land degradation and desertification are significant environmental challenges that affect many parts of the world, particularly in arid and semi-arid regions. These regions are characterized by low and unpredictable rainfall, high temperatures, and fragile ecosystems that are highly susceptible to environmental changes. The semi-arid regions of the world, including the Indian subcontinent, are particularly vulnerable to land degradation and desertification due to unsustainable land use practices, population growth, and climate change (Abdi et al. 2013; Kumar et al. 2022; Briassoulis 2019). In the chapter, we select an area in the semi-arid district of the Andhra Pradesh state, India. Where land degradation leads to desertification. We discuss the study area’s geo-environmental background. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 P. K. Badapalli et al., Aeolian Desertification, Advances in Geographical and Environmental Sciences, https://doi.org/10.1007/978-981-99-6729-2_2

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In India, the semi-arid regions of Andhra Pradesh, including the Anantapur district, are facing significant challenges related to land degradation and desertification. These areas are home to a large population, including many small and marginal farmers, who rely heavily on agriculture for their livelihoods. However, over the years, unsustainable land use practices such as overgrazing, deforestation, and intensive agriculture have led to soil erosion, loss of soil fertility, and declining agricultural productivity (Gowda et al. 2013; Dharumarajan et al. 2016; Badapalli et al. 2022). As a result, the semi-arid regions of Andhra Pradesh are experiencing severe land degradation and desertification, with significant impacts on the local economy, food security, and environmental sustainability. These challenges are exacerbated by climate change, which is leading to increased temperatures, changing precipitation patterns, and more frequent droughts and floods (Dave et al. 2019; Rajasekhar et al. 2021). Addressing the challenges of land degradation and desertification in semi-arid regions like Andhra Pradesh requires a multidisciplinary approach, incorporating sustainable land management practices, water conservation and management, and climate change adaptation measures. This includes promoting soil conservation measures, such as terrace farming, agroforestry, and the use of organic fertilizers. It also involves developing innovative water conservation and management practices, including rainwater harvesting, groundwater recharge, and efficient irrigation systems (Bruins and Lithwick 1998; Afrasinei 2016; Dharumarajan et al. 2022). Through the development and implementation of these sustainable management practices, it is possible to mitigate the negative impacts of land degradation and desertification and promote a healthier and more resilient environment in semi-arid regions. This requires the collaboration of policymakers, researchers, and local communities to develop effective solutions that are tailored to the unique challenges of each region.

2.2 Land Degradation Land degradation refers to the process by which land loses its natural productivity and ability to sustain plant and animal life due to a combination of natural and human-induced factors. It is one of the most pressing environmental challenges facing humanity today, with profound implications for food security, water resources, and biodiversity conservation. Land degradation can take many forms, including soil erosion, desertification, deforestation, and loss of topsoil nutrients. In this essay, we will discuss the causes, consequences, and possible solutions to land degradation.

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2.2.1 Causes of Land Degradation Land degradation is a complex phenomenon that is caused by a variety of natural and human-induced factors. Some of the most common causes of land degradation are: 2.2.1a Deforestation: The indiscriminate felling of trees for commercial purposes, agriculture, or urbanization is a major cause of land degradation. Deforestation leads to soil erosion, loss of soil nutrients, and changes in the hydrological cycle, which affects local and regional climate patterns. Soil erosion: Soil erosion is the process by which soil particles are removed by wind or water, leading to loss of topsoil and soil nutrients. Soil erosion is often exacerbated by overgrazing, improper land use practices, and construction activities. 2.2.1b Desertification: Desertification is the process by which fertile land becomes desert due to a combination of natural and human-induced factors, such as drought, soil erosion, overgrazing, and deforestation. Overgrazing: Overgrazing occurs when the carrying capacity of rangelands is exceeded by livestock, leading to soil compaction, soil erosion, and loss of vegetation cover. 2.2.1c Land use change: Land use change is the conversion of natural ecosystems, such as forests or grasslands, into agricultural or urban areas. Land use change often leads to soil degradation, loss of biodiversity, and changes in the hydrological cycle. 2.2.1d Climate change: Climate change is a major cause of land degradation, as it affects the distribution and intensity of rainfall, leading to soil erosion, desertification, and loss of soil nutrients.

2.2.2 Consequences of Land Degradation The consequences of land degradation are far-reaching and affect the social, economic, and environmental well-being of communities. Some of the most significant consequences of land degradation are: 2.2.2a Food insecurity: Land degradation reduces the productivity of agricultural land, leading to decreased crop yields and food shortages. This is particularly devastating in developing countries, where agriculture is the main source of livelihood for many people. 2.2.2b Water scarcity: Land degradation affects the hydrological cycle, leading to decreased water availability and quality. This affects not only human populations but also ecosystems that depend on water, such as wetlands and rivers.

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2.2.2c Biodiversity loss: Land degradation leads to habitat destruction, fragmentation, and loss of biodiversity. This has significant implications for ecosystem functioning and services, such as pollination, pest control, and carbon sequestration. 2.2.2d Climate change: Land degradation contributes to climate change by releasing carbon into the atmosphere and reducing the ability of ecosystems to sequester carbon. This exacerbates the already significant challenges posed by climate change, such as sea-level rise and increased frequency and intensity of extreme weather events. 2.2.2e Soil degradation: Land degradation leads to loss of soil nutrients and organic matter, reducing soil fertility and productivity. This makes it more difficult to grow crops and sustain agricultural livelihoods.

2.3 Desertification Desertification is a process of land degradation that results in the loss of productivity and vegetation cover, leading to barren lands. It occurs in arid, semi-arid, and dry subhumid regions, affecting the livelihoods of millions of people who depend on agriculture and pastoralism. Desertification is a significant environmental problem that has far-reaching implications for the ecosystem, society, and the economy (Malagnoux 2007; Mulinge et al. 2016; Yusuf et al. 2020).

2.3.1 Causes of Desertification Desertification is caused by a combination of natural and human factors. Some of the natural factors include drought, low rainfall, and soil erosion. Human factors that contribute to desertification include overgrazing, deforestation, agricultural practices, and land use changes. Overgrazing is a significant problem in many semi-arid regions, as livestock grazing pressure exceeds the carrying capacity of the land, leading to soil erosion and vegetation loss. Deforestation is also a significant problem, as trees play a crucial role in maintaining soil fertility and moisture, and their removal can lead to soil degradation (Thomas 1997; Danfeng et al. 2006; Geist 2017). Agricultural practices, such as monoculture farming, excessive use of agrochemicals, and poor soil management, also contribute to desertification. These practices reduce soil fertility, leading to reduced crop yields and eventual abandonment of the land. Land use changes, such as the conversion of natural vegetation to cropland or urban development, also contribute to desertification, as they alter the natural balance of the ecosystem (Asmah et al. 2017; Geist 2017; Becerril-Piña and Mastachi-Loza 2021).

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2.3.2 Effects of Desertification Desertification has far-reaching effects on the environment, society, and the economy. The following are some of the major effects of desertification: 2.3.2a Loss of biodiversity: Desertification leads to the loss of biodiversity, as vegetation cover is reduced and habitats are destroyed. This has significant implications for ecosystem functioning and services, such as pollination, pest control, and carbon sequestration. The loss of biodiversity also affects the survival of plant and animal species that are adapted to this harsh environment. 2.3.2b Soil erosion: Desertification leads to increased soil erosion, as the limited vegetation cover and high-intensity rainfall events make the soil particularly vulnerable to erosion. Soil erosion leads to loss of topsoil and soil nutrients, reducing the productivity of the land. Soil erosion also contributes to sedimentation in rivers, which can lead to the loss of aquatic habitats and biodiversity. 2.3.2c Water scarcity: Desertification affects the hydrological cycle, leading to decreased water availability and quality. The loss of vegetation cover reduces the capacity of the land to retain and store water, leading to increased runoff and decreased groundwater recharge. This affects not only human populations but also ecosystems that depend on water, such as wetlands and rivers. 2.3.2d Food insecurity: Desertification reduces the productivity of agricultural land, leading to decreased crop yields and food shortages. This is particularly devastating in regions where agriculture is the main source of livelihood for many people. The loss of productivity also leads to higher food prices and increased poverty, which can exacerbate social tensions and conflicts. 2.3.2e Migration: Desertification can lead to migration, as people are forced to move in search of better living conditions. This can lead to social and political instability, as displaced populations compete for resources and opportunities. 2.3.2f Climate change: Desertification contributes to climate change by releasing carbon into the atmosphere and reducing the ability of ecosystems to sequester carbon. This exacerbates the already significant challenges posed by climate change, such as sea-level rise and increased frequency and intensity of extreme weather events.

2.4 Land Degradation Leads to Desertification Land degradation is a major contributing factor to desertification. When land is degraded, it loses its productivity and ability to support vegetation, which in turn makes it vulnerable to becoming a desert. Desertification is a process that occurs gradually, as the soil becomes increasingly dry, and the vegetation cover is reduced.

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The loss of vegetation cover leads to increased soil erosion and decreased soil fertility, which makes it difficult for plants to grow and thrive (Eswaran et al. 2001; Bai et al. 2008; Beniston and Stoffel 2014; Blaikie and Brookfield 2015; Chappell and Webb 2016). Land degradation can be caused by natural factors, such as drought and low rainfall, but it is often exacerbated by human activities, such as overgrazing, deforestation, and poor agricultural practices. Overgrazing occurs when livestock grazing pressure exceeds the carrying capacity of the land, leading to soil erosion and vegetation loss. Deforestation is also a significant problem, as trees play a crucial role in maintaining soil fertility and moisture, and their removal can lead to soil degradation. Poor agricultural practices, such as monoculture farming, excessive use of agrochemicals, and poor soil management, also contribute to land degradation (Geist and Lambin 2004; FAO 2015; Lal 2015). As the land becomes increasingly degraded, it becomes less able to support plant life, leading to a reduction in vegetation cover. This reduction in vegetation cover then leads to increased soil erosion, as the topsoil is no longer held in place by plant roots. The loss of topsoil further reduces the ability of the land to support vegetation, leading to a vicious cycle of degradation that can ultimately lead to desertification (Reynolds et al. 2007; Middleton and Thomas 2013; Verstraete and Schwartz 2013; Thomas 2016). Desertification has far-reaching effects on the environment, society, and the economy. It leads to the loss of biodiversity, as vegetation cover is reduced and habitats are destroyed. It also leads to increased soil erosion, water scarcity, food insecurity, migration, and climate change. Preventing and mitigating desertification requires a multifaceted approach that addresses both the natural and human factors that contribute to the problem (Vlek and Le 2015). Sustainable land management practices, such as agroforestry, conservation tillage, and improved soil management, can help to prevent and mitigate land degradation and desertification. In addition, policy and institutional reforms are needed to address the underlying causes of land degradation and to support sustainable land management practices.

2.5 Semi-arid Regions of Andhra Pradesh Andhra Pradesh is a state located in the southeastern part of India, bordered by Tamil Nadu to the south, Karnataka to the west, and Odisha to the north. The state has a diverse geography, ranging from the Eastern Ghats Mountain range to coastal plains, and semi-arid regions. Semi-arid regions of Andhra Pradesh are mainly located in the central and southern parts of the state, covering districts such as Anantapur, Kurnool, Prakasam, and Kadapa. These regions receive low to moderate rainfall, typically between 500 and 900 mm per year, and are characterized by hot and dry summers and mild winters. The semi-arid regions of Andhra Pradesh face a range of environmental and socioeconomic challenges. Land degradation, water scarcity, and climate change are

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some of the major issues affecting these regions. The loss of vegetation cover due to land degradation has reduced soil fertility and increased soil erosion, leading to declining agricultural productivity and food insecurity. Water scarcity is a major issue in these regions, as the availability of water is limited due to low rainfall and overexploitation of groundwater resources. The rapid growth of agriculture and industrialization has further exacerbated water scarcity, leading to conflicts over water resources between different user groups. Climate change is also a major concern for the semi-arid regions of Andhra Pradesh, as rising temperatures and changing rainfall patterns are likely to exacerbate existing environmental and socioeconomic challenges. Climate change is expected to lead to increased water stress, soil degradation, and reduced agricultural productivity, further exacerbating poverty and food insecurity (Asia 1953; Singh and Anand 2013; Deuti et al. 2014; Kumar et al. 2020a, b). To address these challenges, a range of interventions is needed, including sustainable land management practices, water conservation and management, and climate change adaptation measures. Sustainable land management practices such as agroforestry, conservation tillage, and improved soil management can help to prevent and mitigate land degradation, while water conservation measures such as rainwater harvesting, check dams, and farm ponds can help to conserve and manage water resources. In addition, climate change adaptation measures such as the development of climate-resilient crops, early warning systems for extreme weather events, and capacity building for vulnerable communities can help to reduce the impacts of climate change on the semi-arid regions of Andhra Pradesh. Overall, the semi-arid regions of Andhra Pradesh face a range of environmental and socioeconomic challenges, but with the right interventions and policies, these challenges can be addressed, and sustainable development can be achieved.

2.6 Selection of the Study Area India, occupying a vast area in the northern hemisphere, is the world’s seventh-largest country. Its mainland stretches between latitudes 8° 4' and 37° 6' North, longitudes 68° 7' and 97° 25' East, covering an expansive 3,287,590 square kilometers. The country consists of 29 states and seven union territories, showcasing a diverse range of geographic features, including deserts, plateaus, mountains, and plains. One of these states, Andhra Pradesh, lies between latitudes 12° 41' and 19.07°N and longitudes 77° and 84° 40' E, encompassing an area of 1,60,205 square kilometers. It shares borders with Telangana to the north and west, Chhattisgarh to the northwest, Odisha to the north, the Bay of Bengal to the east, Tamil Nadu to the south, and Karnataka to the southwest and west. Boasting a remarkable coastline of approximately 974 km, Andhra Pradesh possesses the second-longest coastal stretch in the country.

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Andhra Pradesh is divided into two distinct regions. The first is Coastal Andhra, comprising nine districts, namely East Godavari, Guntur, Krishna, Sri Potti Sriramulu Nellore, Prakasam, Srikakulam, Visakhapatnam, Vizianagaram, and West Godavari. The second region is Rayalaseema, encompassing Anantapur, Kurnool, Kadapa, and Chittoor districts (Raju 1990). In the lowland coastal sections of Andhra Pradesh, the climate is hot and humid, but in parts of the Anantapur, Kurnool, and Kadapa districts, the climate is predominantly semi-arid as they are away from the Western Ghats’ rain shadow region. In this state, the summer season lasts from March until May or June. The moisture level is often higher in the coastal lowlands during these months than it is throughout the winter season (Hemingway 1906; Kumar et al. 2019).

2.6.1 Selection of the District Anantapur district, situated in the Rayalaseema region of Andhra Pradesh, is recognized as one of the driest areas in South India. It shares borders with Kadapa district to the northeast, Kurnool district to the north, Chittoor district to the southeast, and Karnataka State to the west. Being located in the rain shadow region of Andhra Pradesh, the district is prone to droughts. With a geographical area spanning 19,130 square kilometers, it holds the distinction of being the largest district in the state based on land area. Anantapur district experiences an average annual rainfall of approximately 550 mm, making it the district with the lowest precipitation in the state. It is considered the second driest part of the country, following Jaisalmer. As per the 2011 census, the district has a population of 4,083,315, making it the eighth-most populous district in Andhra Pradesh. Additionally, it ranks as the seventh-largest district in India based on its expansive area. The region faces recurrent droughts due to its affiliation with the Rayalaseema region. Over the past two decades, the district has witnessed famine occurrences about 18 times. Anantapur holds the distinction of being the driest district in the state. The annual precipitation in the district is meager, averaging around 550 mm, with the southern region receiving slightly more rainfall than the district average. However, this rainfall is not only insufficient but also irregular in terms of its timing and distribution across the area. Consequently, the combination of scanty and unpredictable rainfall, along with challenging agricultural conditions, has rendered the district perpetually prone to droughts. Although agriculture serves as the primary economic activity for approximately 80% of the population, the irrigated area in the district accounts for only about 10% of the overall cultivated land. The district does not have perennial rivers and is being a hard rock area, the groundwater potential is also assessed to be limited. The terrain is undulating, resulting in a high runoff and contributing to active erosion of the top layer of soil. The evapotranspiration is also high due to the semi-arid climate, high temperature, and high wind velocity. Apart from the above factors, the district has a low potential in terms

2.7 Selection of the Study Area Boundary for Research

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of other natural resources like mineral and forest wealth. The Ramagiri goldfield, the Vajrakarur diamondiferous field, steatite, limestone, and barite deposits are expected to sustain mining and the associated industrial activity in a very limited way. The forests occupy an area of 1936.25 square kilometers forming 10.1% of the total geographical area. Even these forests do not have substantial growth species like dry deciduous scrub, Euphorbia scrub, dry grasslands, southern thorn, etc., mainly forest cove in the district. The produce from these forests is so meager that it does not even meet the timber—and fuel requirements of the district. All these factors have prompted the state authorities to declare Anantapur district as a drought-prone area.

2.7 Selection of the Study Area Boundary for Research Three particular mandals—Bommanahal, Kanekal, and Beluguppa—out of the 63 mandals that make up the Anantapur district are struggling with desertification and land degradation. The three mandals, which together span an area of 1050.95 square kilometers, have been chosen as the subject of my research project. The soil in these places has lost its fertility and experienced deterioration as a result of the insufficient rainfall and the existence of uncultivated fields, which eventually led to desertification. Two large rivers cross the terrain in the study region. The Hagari or Vedavathi River, which runs through the heart of the area, is the first. The Penna River, which is situated in the eastern part of the research area, is the second. Because both rivers are classified as seasonal or ephemeral, they often dry up for most of the year. Before entering the state of Karnataka, the Hagari River flows through the mandals of Bommanahal, D-Herehal, Kanekal, Beluguppa, Gummaghatta, and Brahmasamudram in the Anantapur district. Historical records indicate that nearly 200 years ago, the Vedavathi River experienced severe flooding, causing a significant amount of fine sand from the riverbed to be carried and deposited over a considerable distance onto agricultural fields. This event resulted in a decline in soil fertility on the eastern side of the river. From June to August, the region is subjected to strong surface winds, reaching speeds of approximately 36–38 km per hour, blowing from the west in an easterly direction due to the southwest monsoon. The presence of unidirectional asymmetrical ripple marks in the sand dunes serves as evidence of the eastward migration of sand in the study area. These persistent surface winds have carried the sand into the crop fields, leading to land degradation and eventual desertification. The mandals of Bommanahal, Kanekal, and Beluguppa, located in the semi-arid regions of the south-central part of Anantapur district in Andhra Pradesh, South India, face recurrent droughts, land degradation, and desertification. Therefore, the present study has been undertaken to assess and map the geo-environmental conditions of these desertified regions using remote sensing and GIS techniques (Fig. 2.1).

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Fig. 2.1 Location map of the study area

2.8 Land Degradation and Desertification in the Semi-arid Region of Anantapur The semi-arid region of Anantapur district in Andhra Pradesh is particularly vulnerable to land degradation and desertification due to its geographical location, climate, and land use patterns. The district receives low to moderate rainfall, ranging from 500 to 700 mm annually, and is characterized by hot and dry summers and mild winters. The majority of the population in the district depends on agriculture, which is mainly rainfed, making it particularly vulnerable to the impacts of land degradation and desertification. Land degradation is a major issue in Anantapur district, with soil erosion, nutrient depletion, and salinization being the most common forms. The removal of vegetation cover due to deforestation, overgrazing, and improper land management practices has led to increased soil erosion, nutrient depletion, and soil compaction, making

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it difficult for plants to grow and thrive. Additionally, the overuse of groundwater for irrigation has led to the depletion of groundwater resources, exacerbating the problem of land degradation. Desertification is also a growing concern in Anantapur district, with the loss of vegetation cover being a key contributing factor. The reduction in vegetation cover leads to increased soil erosion and reduced soil fertility, which further exacerbates the problem of land degradation. Desertification has resulted in declining agricultural productivity, loss of biodiversity, and food insecurity, particularly for marginalized and vulnerable communities. The impacts of land degradation and desertification in Anantapur district are farreaching and have significant environmental, social, and economic implications. The loss of vegetation cover has led to a decline in soil productivity and increased soil erosion, which has resulted in declining agricultural productivity, food insecurity, and poverty. The loss of biodiversity has also resulted in a decline in ecosystem services, such as soil conservation, water regulation, and carbon sequestration. To address the problem of land degradation and desertification in Anantapur district, a range of interventions is needed, including sustainable land management practices, water conservation and management, and climate change adaptation measures. Sustainable land management practices such as agroforestry, conservation tillage, and improved soil management can help to prevent and mitigate land degradation. Water conservation measures such as rainwater harvesting, check dams, and farm ponds can help to conserve and manage water resources, while climate change adaptation measures such as the development of climate-resilient crops and early warning systems for extreme weather events can help to reduce the impacts of climate change. In postulation, land degradation and desertification are major challenges facing the semi-arid region of Anantapur district in Andhra Pradesh. The loss of vegetation cover, combined with unsustainable land use practices, has led to declining agricultural productivity, food insecurity, and poverty. However, with the right interventions and policies, these challenges can be addressed, and sustainable development can be achieved.

2.9 Geo-environment Geo-environment refers to the relationship between the natural environment and the Earth’s geological processes, including the atmosphere, lithosphere, hydrosphere, and biosphere. It is a multidisciplinary field that incorporates elements of geology, geography, hydrology, ecology, and atmospheric science. The study of geo-environment focuses on understanding the natural processes and phenomena that shape the Earth’s environment, including landforms, soils, water resources, climate, and ecosystems. It also examines how human activities, such as urbanization, agriculture, mining, and industrialization, impact the geo-environment and contribute to environmental degradation and pollution.

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One of the key concepts in the study of geo-environment is the idea of environmental systems. An environmental system is a complex, interconnected network of physical, chemical, and biological components that interact with each other and with the external environment. Examples of environmental systems include river basins, wetlands, forests, and deserts. The study of geo-environment also involves the use of advanced technology and analytical techniques to collect, analyze, and interpret data. This includes remote sensing, Geographic Information System (GIS), and modeling, which are used to map and monitor environmental changes, predict future trends, and develop strategies for environmental management and conservation. Geo-environmental issues are complex and often require interdisciplinary approaches to address. For example, the management of water resources in an area affected by land degradation may involve hydrological modeling, soil conservation measures, and changes in agricultural practices. Similarly, addressing air pollution may require collaboration between atmospheric scientists, urban planners, and policymakers (Babu 2016; Badapalli et al. 2019; Breckle 2012; Darkoh 1998; IMD 2013; Katyal and Vlek 2000; Sharma and Sharma 2016; Sivasankaranarayana 1970; Xie et al. 2020). Inclusive, the study of geo-environment is critical to understanding the complex relationships between the natural environment and human activities. It provides insights into the processes that shape the Earth’s environment and the impacts of human activities on the planet. Through the development of innovative solutions and sustainable management practices, the study of geo-environment can help to mitigate the negative impacts of human activities and promote a healthier and more resilient planet.

2.9.1 Geology The Anantapur district’s geological formations may be broadly separated into two well-defined groups: an older group of metamorphic rocks from the Archean age and a newer group of sedimentary rocks from the Proterozoic age (Ramam 1988). 2.9.1a Archaean: Archean rocks, including schists, gneisses, migmatites, and the younger granites, pegmatites, quartz veins, and basic dykes, make up the majority of the Anantapur district (Table 2.1). The Archean rocks have undergone a significant amount of tectonic disturbances, which has caused the rocks to undergo metamorphosis and recrystallization. 2.9.1b Proterozoic groups: Except for Archean, some of the minor formations like Tadipatri, Gooty, and Anantapur areas are occupied with the younger formations of Kadapa and Kurnool supergroup rock formations (Table 2.1). They are found to occur in the eastern part of the district.

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Table 2.1 Geological succession of Anantapur district Geological age

Formation

Lithology

Panyam Quartzite

Quartzite

Owk shales

Shales

Geological succession Kurnool group

Soil, and alluvium

Narji limestone

Limestone

Banaganapalli

Quartziotes, Conglomerates

Tadipathri shale

Shales

Pulivendula quartzites

Quartzites

Unconformity Proterozoic Cuddapah supergroup

Chitravathi group Papagni

Vempalli Dolomites

Dolomites, limestones

Gulcheru Quartzites

Quartzite, conglomorates

Unconformity Younger

Quart reefs, basic dykes (dolerites) pegmatites

Intrusives

Quartz veins pink granite and ultra-basics

Dharwar

Sericite, chlorite hornblende schists, and granulites

Supergroup Archeans Peninsular gneissic complex

Gray granite, gneisses, and migmatites

Older metamorphics Biotite schist, pyroxenite, and amphibolite

2.9.1c Geology of the study region: The Geological Survey of India (GSI) provided the geological map, specifically the District Resource Map, for the study area. In addition, Survey of India (SOI) toposheets, namely 57B/13, 57B/14, 57B/15, 57F/ 1, 57F/2, 57F/3, 57F/5, 57F/6, and 57F/7, at a scale of 1:50,000, were utilized in conjunction with the ArcGIS environment to create a geology map of the study area. Figure 2.2 displays the resulting geological map, illustrating the geological composition of the area. The predominant rock types within the study area include the Peninsular Gneissic Complex (PGC), which comprises granite, granodiorite, felsic hornblende-biotite gneiss, hornblende gneiss, biotite gneiss, and migmatites. These rock formations are primarily found in the eastern part of the study area and can be attributed to the Archean age. Gray granite and pink granite, on the other hand, are prevalent in the southwestern region of the study area. Table 2.2 represents the geological types in the study region and their geographical area. Hornblende—gneiss, Hornblende—biotite gneiss, biotite gneiss, and migmatite rocks are major types occupying an area of 844.86 square kilometers, gray granite/ pink granite rock types occupying in the southwestern portion with an area of

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Fig. 2.2 Geology

149.70 square kilometers, quartzite; BIF/BMQ/ferruginous quartzite rock types in the northwest occupying with an area of 3.70 square kilometers, granite and granodiorite in the southeastern portion occupying with an area of 1.54 square kilometers, and water bodies or the river Hagari/Vedavathi flowing through the center of the study area, occupying with an area of 51.15 square kilometers.

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Table 2.2 Geology of the study area ( Ramam 1988) S. no

Geology

1

Hornblende—biotite gneiss, hornblende—gneiss, biotite gneiss, migmatite

2

Quartzite; BIF/BMQ/ferruginous quartzite

Area in square kilometers 844.86 3.70

3

Gray granite/pink granite

149.70

4

Granite and granodiorite

1.54

5

Waterbody/river

6

Total

51.15 1050.95

2.9.2 Geomorphology Environmental management depends largely on geomorphology, which is the study of landforms and the associated physical processes. The potential of land for development in both urban and rural settings has been assessed with the use of better technologies for mapping geomorphological properties. Geomorphological processes are a component of a larger system of interconnected phenomena, and their importance to environmental issues must be evaluated in the context of the local population’s social, economic, and cultural circumstances. The essential components of the planning for development in many sectors are landforms and their naturally occurring soil and vegetation (Machireddy 2019). Thus, if a basic geomorphic map is produced showing the distribution of landform units and their characteristics, it would be easier to prepare other thematic maps from this base map. Remote sensing data has immense use in the preparation of such geomorphological maps. For the preparation of a geomorphological map of the study area, satellite data of Landsat 8 OLI/TIRS and NRSC maps was used. Interpretation and delineation of landforms were done based on the land—system mapping procedure in the ArcGIS environment (Fig. 2.3). Further, fieldwork was carried out, along limited traverses for the correlation of interpreted landforms with the field expressions and characteristics of individual geomorphic land units. During the field, traverses information is gathered on the nature of the soil, vegetation, slope characteristics, weathering, the character of the various bedrocks, and hydrological potential of the area. The four geomorphic units are identified in the study area are (Table 2.3): 1. 2. 3. 4.

Denudational origin Pediment and pediplain origin Structural origin Aeolian origin.

2.9.2a Denudational origin: Hills that have undergone denudation are the remains of processes like weathering, denudation, and denudation that were helped by subsequent fluvial action. Domes, inselbergs, linear ridges, mesas, low knolls and mounds,

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Fig. 2.3 Geomorphology Table 2.3 Geomorphology of the study area S. no

Geomorphology

1

Denudational origin

2

Denudational origin-pediment-pediplain complex

3

Structural origin-moderately dissected hills and valleys

4

Aeolian origin

5

River/waterbodies Total

Area in square kilometers 929.74 7.62 5.37 35.75 72.47 1050.95

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and tors with partial scree or debris-covered at the foot slopes are some of the geomorphic structures that are produced as a result of exfoliation. Rockfall, debris fall, and formation of debris cones and fans are common at the foothills. The zone of weathering is considerably shallow, and soil cover is thin. The occasional growth of low trees, thorny bushes, and is are marked along with the deep fractures. Most of these hills are stony and barren of vegetation. In the study area, the denudational origins are essentially stony, composed of gray, and pink granites, gneisses, and migmatites with very little soil cover and mostly barren vegetation. Denudational origin covers a major portion of the study area and covers 929.73 square kilometers geographical area. These are characterized by rugged surfaces and they occur as hill ranges and inselbergs. Besides these forms, several low mounds and knolls with a characteristic expression of tors and perched blocks are recognizable in the district (Fig. 2.2 and Table 2.3). 2.9.2b Pediment and pediplain origin: The term “pediment” is defined as an eroded rock surface of a considerable extent at the foot of a mountain slope or face formed normally under a semi-arid or arid cycle of erosion. The pediments often have only a thin veneer of debris/soil. Dissection of this pediment surface due to the fluvial action by sheet wash representing the dynamism of the erosive forces acting in the area results in dissected pediment at most devoid of the cover of natural soil. The study area around the dissected pediment formed by the above processes occupies an area of 7.32 square kilometers next to the category of structural origin. The pediment overlies all the litho units, viz; granite-gneiss, migmatite, and schist rocks. The pediment slopes are gentle to moderate (5–15%), characterized by a rugged appearance, with several small outcrops of rock and support scanty vegetation of low shrubs and grasses in areas covered by a thin mantle of soil. The term “pediplain” describes the flat or gently sloping surface that results from the joining of multiple pediments at the base of hill slopes. The research region’s pediplain is distinguished by a sizable expanse of low-lying flat land with mild slopes of less than 5%. Pediplain regions are covered with gritty, gravelly, sand, and clayey soils that are red, brown, or black in color and range in thickness from 20 to 60 cm, occasionally going as deep as 2 m. In several sections of the pediplain, the zone of weathering is moderate to deep (10–15 m) (Fig. 2.2 and Table 2.3). 2.9.2c Structural origin: Structural origin includes hills, valleys, mesa, butte, and rims. In the northeastern part of the study region dominated with the structural origin, this is mainly of hilly type with the banded hematite quartzite (BHQ) rock. The study area occupies an area of 5.36 square kilometers with a structural origin. Active mining activity is performed in and around this structural origin; this leads to the change of the environment and is responsible for geomorphic changes in the study area (Fig. 2.2 and Table 2.3). 2.9.2d Aeolian origin: The study area experiences dynamic geomorphic changes primarily driven by the Aeolian process. The Hagari/Vedavathi River, a non-perennial river, flows through the central part of the study area. Due to limited rainfall, the river remains dry for most of the year, resulting in the formation of stagnant dunes along its

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course. These dunes are susceptible to migration due to the influence of strong winds, particularly during the southwest monsoon season, which occurs primarily from June to August. The Aeolian action, facilitated by these heavy winds, contributes to the development of sand and sand sheets within the study area, influenced by various environmental and climatic conditions. The presence of sand dunes and sand significantly impacts the local ecosystem, with their characteristics and behavior being influenced by wind directions and the level of internal complexity. Figure 2.2 and Table 2.3 depict the aeolian origin of sand and sand dunes in the study area.

2.9.3 Soils The soil map of the study area is obtained from the National Bureau of Soil Survey and Land Use Planning (NBSS and LUP), using the SOI toposheets as base maps. The geology of the study area is very complicated involving all the major types of rocks under varying geomorphological conditions. The soil series demarcated in the study area is about eight types in number. The classification of soils according to soil taxonomy places these soils in the following four types (Table 2.4). 1. 2. 3. 4.

Aridsols Alfisols Entisols Vertisols.

Table 2.4 Soils of the study area (Kale et al. 2020) S. no

Soil type

Soils

1

Aridsols

Gravelly clayey moderately deep desert soils Clayey to gravelly clayey moderately deep dark brown soils

Area in square kilometers 620.92 46.70

Moderately deep calcareous moist clayey soils

180.84 17.89

2

Alfisols

Loamy to gravelly clay deep dark reddish-brown soils Deep black clayey soils

55.11

3

Entisols

Gravelly loam to gravelly clayey shallow dark brown soils

11.21

4

Vertisols

Very dark brown moderately deep wet silty soils

87.13

Water bodies/river Total

30.55 1050.95

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2.9.3a Aridsols: The most dominant type in the study area is aridsols comprises “gravelly clayey moderately deep desert soils” and “clayey to gravelly clayey moderately deep dark brown soils.” They are in the color from dark black to brown and occupies with an area of 620.92 square kilometers and 46.70 square kilometers, respectively (Fig. 2.4 and Table 2.4). The soils like clayey to gravelly clayey moderately deep dark brown soils are available along the Hagari River in the study area, and they are sandy soils and get migrated in the environmental conditions. Soils are derived from granites, granite gneisses, biotite gneisses, and hematite quartzites (Nallathiga 2001). They have well-developed argillic horizon with clay. They occur on gently sloping to undulating middle and lower pediments, with 1–5% slopes. The surface textures generally range from loamy to sandy loam, gravelly sandy loam, or gravelly clay loam. At times, the surface is covered with gravel, pebbles, and cobbles to the extent of 15–25%. The surface structures are generally granular to weak subangular blocky. These soils have moderately high available water content. Medium cation exchange capacity 70% or more base saturation slightly acid to neutral soil reaction. 2.9.3b Alfisols: These soils comprise dark brown, and dark reddish-brown, slightly to moderately calcareous, gravelly, coarse loamy to gravelly, fine loamy and clay skeletal, moderately deep to deep soils derived from granite gneisses, amphiboles, hematite quartzite or formed from colluvial material and have well-developed argillic horizon. The gravel portion comprises ferruginous, quartzitic, and siliceous material. The gravels are angular to subrounded and in most cases increase with depth. These soils are moderately permeable and well-drained and remain moist for 70–110 days during the year in some parts of the horizon. The water-holding capacity is moderately high. In the study area, “loamy to gravelly clay deep dark reddish-brown soils” and “deep black clayey soils” can be identified and occupy an area of 17.89 square kilometers and 55.11 square kilometers, respectively (Fig. 2.3 and Table 2.4). These soils are quite easy to cultivate under different moisture conditions. They remain moist for a longer time and are very well suited for irrigation. Almost all types of grain crops, pulses, groundnut, and other oil seeds are cultivated. Mixed cropping is commonly adopted under rainfed conditions for these soils. 2.9.3c Entisols: These soils comprise dark gravelly loam to gravelly clayey shallow dark brown soils, slightly calcareous, alluvial soils occurring on nearly level to gently sloping, lower, and buried pediments. In the study area, gravelly loam to gravelly clayey shallow dark brown soils occupies an area of 11.81 square kilometers. They have a weak, subangular blocky structure with good drainage and moderately rapid permeability (Fig. 2.3 and Table 2.4). These soils have low available water capacity, medium cation exchange capacity, high base saturation with neutral to slightly alkaline soil reaction and nil to slight erosion and very low available P. Millets, early varieties of paddy, and other irrigated crops are cultivated wherever tank irrigation is available, while millets and horse gram are cultivated in rainfed conditions. Cropping patterns suggested for these soils are jowar, groundnut in kharif, paddy, sugarcane, hybrid, maize, ragi, chillies under irrigated conditions (Dharumarajan et al. 2017).

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Fig. 2.4 Soil types in the study area

2.9.3d Vertisols: These soils comprise very dark brown moderately deep wet silty soils, very fine to fine, calcareous, formed on gray granites, and epidote granites. These vertisols occupy an area of 87.13 square kilometers in the study area (Fig. 2.3 and Table 2.4). They generally occur on the level to very gently sloping lower pediment with slopes ranging from 1 to 5%. The subsoil structures are very coarse angular and subangular blocky. The soil is hard when dry, extremely firm when moist sticky and plastic when wet. They have high cation exchange capacity and high base saturation, moderate to strong alkaline soil reaction, and at times moderately high exchangeable sodium (Izzo et al. 2013; Bhelawe et al. 2014). They are moderate to severely eroded. Moderately deep soil phases are found to occur in association with deep soil. Jowar and cotton are the crops mostly raised in

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these soils. Pulses are taken as mixed crops either with cotton or jowar. Coriander is also cultivated in a few places. The suggested crops which are suitable for these soils are jowar, cotton, and tur. Sunflower, wheat, and Bengal gram can also be cultivated in these soils during the rabi season.

2.9.4 Slope Slope features of a region are of considerably significant in the scientific supervision of land. This classification can bring out the critical restricting factors for certain uses. Limitations on gradients are especially pertinent in the case of transport and agriculture. The slope map of the study area is taken out from Cartosat Digital Elevation Model (DEM) with the spatial resolution of 30 m (Warren et al. 2004), which is freely accessible and downloaded from the NRSC BHUVAN website (www. nrsc.in), and performed spatial analysis in the ArcGIS environment (Fig. 2.5). The study area has been categorized into five groups based on their morphological features and developmental activities. Below 2% Between 2 and 5% Between 5 and 15% Between 15 and 30% Over 30%. 2.9.4a Below 2%: In the below 2% slope zone, widespread sand deposits are available along the banks of the streams (channel floor deposits). The sand deposits in the channels of the Hagari/Vedavathi and the Penna streams are of significance. The important aspect in this slope zone (below 2%) is the scope of the development of the brick and tile industry along the banks of some of the major tanks which hold a great amount of silt and also in the catchment area (toward higher slope) in the proximity of these tanks. The soil has a good thickness (Fig. 2.5). 2.9.4b Between 2 and 5%: The 2–5% area shown in the study area is mostly suitable for dryland farming and this requires extensive contour bunding for soil conservation. Contour bunding has an indirect influence on the raising of the groundwater table by preventing the monsoon runoff and allowing it to infiltrate. The soils in this slope zone are of utmost importance for agriculture—proper care is needed to conserve and develop them by way of fertilizer treatment and augmentation of soil micronutrients (Taripanah et al. 2021). 2.9.4c Between 5 and 15%: The third slope zone is 5–15%, which is ideally suitable for the development of pastures and also dryland farming. Development of forest in parts of this area can be undertaken. The soil conservation measures need great attention toward gully control measures, etc.

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Fig. 2.5 Slope

2.9.4d Between 15 and 30%: The fourth slope zone is 15–30%; it is also useful for the same purposes but due to rock exposures, the area may be more suitable for the development of forest and rock quarrying. Sometimes developed area is also considered as this zone due to height of the built-up area and surroundings. 2.9.4e Over 30%: The fifth slope zone is over 30%, it is consisting of hilly areas, underlain by granitic terrain. In the context of developmental activities of the district, rock quarrying for different building purposes can be carried out extensively in this zone. Some of the northeastern and southwestern parts have over 30% of the slope in the study region.

2.9 Geo-environment

35

2.9.5 Hill Shade The assessment of solar radiation has traditionally focused on aspect and topographic shape. With the advancements in ArcGIS technology, it has become possible to utilize hill shade maps for estimating solar radiation. The objective of this study was to examine the relationship between these indices and their ability to accurately define the characteristics of semi-arid lands in the study region. Analysis of the region’s hill shadow map and slope map revealed predominantly flat terrain. Similarly, diffusion and breed factors demonstrated lower significance across all three calibration rounds, indicating reduced overall variability, slower outward spread, and a decreased likelihood of new urban development. During the peak of summer, a hill shade map ranging from 0 to 254 was generated (Fig. 2.6). In comparison to the other two indicators, the shade index had a notable impact on vegetal drought, as observed from the analysis of dieback ratios in the three representative histograms. The findings indicated that the hill shade index outperformed the other indicators in characterizing and analyzing ecological processes dependent on soil moisture, such as forest dieback. This particular indicator could be employed to develop a risk model for predicting the consequences of recurring droughts caused by climate change or other detrimental factors.

2.9.6 Lineaments A manifestation of underlying structures like faults, joints, and fractures, a lineament is a linear feature. Any two sets of lineaments have a tendency to be similar along the NE-SW and NW–SE axes. Lineaments refer to fracture zones, igneous intrusions like dykes, and many other geomorphic structures. If any geological formation in the environment may be regarded as a lineament (Rajasekhar et al. 2019). These lineaments are very useful in groundwater and mineral exploration. Lineaments can give the clue to find the fracture or inner shape of the surface, which can provide the surface roughness and environmental consideration in the land degradation assessment. In the study area, we have prepared lineament maps by using the Landsat 8 OLI/ TIRS, and Cartosat DEM data with 30 m spatial resolution, in the ArcGIS environment, and further, this lineament can be crosschecked with the NRSC lineament map. The mapping of the research area’s lineaments is shown in Fig. 2.7. Lineaments have mostly been mapped into two categories: structural lineaments with faults (in red color) and structural lineaments with joints and fractures (in blue color).

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Fig. 2.6 Hill shade

2.9.7 Drainage or Hydrology The hydrology or drainage map of the study range was prepared by using Cartosat DEM; along with the toposheet overlay, the study area streams are digitized in the ArcGIS software (Fig. 2.8). The streams are identified from the first order to the fifth order in the study area. The Hagari River flows through the center of the study area; hence, the major stream of the Hagari is identified to fifth order. The Hagari River is the intermittent non-perennial river; hence most of the year it is dried. Identification of the stream orders in the study area will be helpful for the monitoring and assessment

2.9 Geo-environment

37

Fig. 2.7 Lineaments

of the geo-environment (Rajasekhar et al. 2018; Badapalli et al. 2021). In the study area, we identified 64 first-order streams, 45 second-order streams, 45 third-order streams, 44 fourth-order steams, and 1 fifth-order stream are present. The study is occupying an area of 1050.95 square kilometers.

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Fig. 2.8 Drainage

2.10 Atmospheric Conditions 2.10.1 Climate Due to the high Western Ghats cutting off the Anantapur district, which is located a short distance from the coast, it does not fully benefit from the northeast monsoon and is also prohibited from receiving rainfall from the southwest monsoon, which is why the study area is considered to be in a dry climate. Thus, the district is deprived

2.10 Atmospheric Conditions

39

of both the monsoons and subjected to recurrent droughts and bad seasons (Naveen et al. 1991; Virmani and Shurapli 1999). Following are some factors affecting the climate in the study area.

2.10.2 Air Temperature The study area experiences consistently warm conditions throughout the year. However, these warm environmental conditions undergo seasonal modifications due to variations in water regimes and surface characteristics. From March to July, the mean monthly maximum air temperature exceeds the annual average maximum temperature of 33.8 °C. During this period, mean monthly air temperatures remain above 38.0 °C for most of the year, except in July. The likelihood of maximum temperatures surpassing 40 °C but remaining below 45 °C is 3.0% in May and only 1.0% in April. Throughout the crop-growing season, which spans from July to October, the mean maximum temperature consistently remains at or above 30 °C, except for September (Naveen et al. 1991; Kale et al. 2020).

2.10.3 Relative Humidity (RH) In the study area, the relative humidity (RH) is assessed during the morning (07:20 h) and afternoon (14:20 h) time periods. In the summer months of March, April, and May, the relative humidity is generally low, ranging from 55 to 64% in the morning and 25–31% in the afternoon. For the remaining months of the year, the relative humidity exceeds 65% in the morning and 32% in the afternoon. The period spanning from February to May represents the driest part of the year, characterized by relative humidity levels of 50–60% in the mornings and 20–30% in the afternoons. However, during the southwest monsoon and retreating monsoon seasons, the relative humidity increases in response to the seasonal rainfall.

2.10.4 Mean Atmospheric Pressure and Vapor Pressure The average atmospheric pressure in the study area is measured at 967 mb annually. The range of atmospheric pressure varies from 965 mb during the months of May to August, reaching its peak at 974 mb in December. The mean vapor pressure deficit for Anantapur is calculated to be 19.6 mb. The vapor pressure deficit remains relatively low from November to April, with the lowest recorded value of 13.4 mb in March. As the rainy season begins, the vapor pressure deficit increases, reaching its maximum of 23.5 mb in August. From June to October, the vapor pressure deficit consistently

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remains above 23.0 mb. Notably, the variation in the mean vapor pressure deficit during the crop season is minimal.

2.10.5 Cloudiness In the Anantapur area, the sky is often clear all year round. From November onwards, the sky is comparatively clear, and it clears up even more in January. The two peak rainfall months of September and October have just 6 Oktas of cloud cover, compared to 7 Oktas during July and August (Naveen et al. 1991; Virmani and Shurapli 1999).

2.10.6 Sunshine The average amount of sunshine each day is 7 h 45 m d−1 . The range of sunshine hours is from 8:00 (during Oct–Dec) to 10:00 (during Mar–May). The number of sunlight hours is low from July through September, with July having the lowest number at 5.00 h per day−1 .

2.10.7 Wind Speeds In the study area, we have collected annual wind speeds for the past three decades, i.e., 1990–2000, 2001–2010, 2011–2020, climate data from NASA (https://power. larc.nasa.gov/data-access-viewer/). The weather stations data has categories, i.e., for 10-m, and 50-m wind speeds, we considered 10 m of data for the present research. Five wind stations in and around the study area are available; from there, we collected cup-anemometer readings to measure wind speeds. The average monthly wind speed is over 25 km/h, with high winds predominating from June to August. The yearly wind speed is 14.52 km/h. In the afternoons at this time, wind speeds can potentially reach 36–38 km/h. This also marks the start of the growing season, which is a unique characteristic of the climate in the research region (Kale et al. 2020; Kumar et al. 2020a, b).

2.10.8 Rainfall Anantapur district receives a mean annual rainfall of only 550 mm, which is spread over four seasons as follows: 1. Southwest monsoon period—June to September (312.42 mm)

2.10 Atmospheric Conditions

41

2. Northeast monsoon period—October to November (149.86 mm) 3. Cold weather period—December to February (12.70 mm) 4. Hot weathered period—March to May (76.20 mm). Drought is defined by the Planning Commission as occurring every three years, or twice every seven years. According to information on the seasonal distribution of rainfall, 27.1% of the yearly rainfall falls during the northeast monsoon and 58.8% falls during the southwest monsoon. 436 mm of reliable yearly precipitation may be expected with 75% likelihood. The wettest months are September and October, which combined account for 44% of the yearly precipitation. Even the wettest month experiences dry spells due to the extreme variety in rainfall throughout the month (Rao et al. 2009). In the selected study area, we have collected rainfall data from the district groundwater department, along with this daily, monthly, and annual rainfall for the past three decades, i.e., from 1990 to 2020, precipitation data has been procured by using the Google Earth Engine code editor, CHIRPS (Fig. 2.9). In the study area, the starting year of the research from 1990, the rainfall is noticed to be 394.28 mm, in 2000, it is 476.28 mm, in the year 2010, it is 546.85 mm, and in the year 2020, it is 601.83 mm, while the average annual rainfall in the study area is 472.17 mm. Figure 2.9 depicts the annual average rainfall, and Fig. 2.10 depicts the monthly average rainfall in the study area for the past three decades.

RAINFALL FROM 1990 TO 2020 711.9368 636.2454

605.916

Annual Rain fall inmm

519.5758

461.4486

457.3574

564.1966

498.6962 486.8655 476.2781

394.2764

380.8261 378.8542 371.2627 338.3392

601.8348

562.5939 546.8528

431.4572 436.1228 418.9289 388.5509

275.4949

505.9603 477.5945

419.6598 388.4218 350.3412 296.4534

494.4875

288.2708

199 199 199 199 199 199 199 199 199 199 200 200 200 200 200 200 200 200 200 200 201 201 201 201 201 201 201 201 201 201 202 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 Total 394 461 338 457 371 381 499 379 606 487 476 520 389 275 436 712 419 564 431 563 547 350 388 506 420 478 296 636 288 494 602

Years from 1990 to 2020

Fig. 2.9 Rainfall from 1990 to 2020

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RESEARCH AREA CATCHMENT AVERAGE CHIRPS PRECIPITATION 140

mm of Water

120 100 80 60 40 20 0 Precipitation (mm/mth)

Jan 0.0

Feb 0.1

Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2.6 21.9 68.1 11.7 11.3 51.7 129.9 122.8 37.8 1.1 Month

Fig. 2.10 Monthly average rainfall for the past three decades of the study area

2.11 Human Factors Human factors that contribute to degraded lands and desertification include the expansion and intensive use of agricultural lands, deforestation, overgrazing, urbanization, and poor irrigation practices, that affect the geo-environmental characterization in the study region. These elements significantly affect how the study area’s geoenvironmental characteristics are described, modifying the land to meet their needs (Hegde 2012).

2.12 Land Use Land Cover Types The main and most important natural resource of the human factor is land use/ land cover (LULC). Therefore, the information on the land characteristics is vital in environmental assessment in the study region. The way we use our land resources, however, is the most essential aspect that defines the quality of the ecosystem. The present study area is categorized into five types of LULC, viz., waterbodies (6.85%), agricultural lands (19.64%), built-up land (13.8%), degraded lands, or desertified lands (36.7%), and fallow lands (20.45%) as shown in Fig. 2.11. The majority is degraded or desertified lands followed by fallow lands. High vegetation cover has been observed in the western portion and northwestern portion of the study area. Land cover and land use patterns are very much useful in the identification of degradation spots, desertification status map, and preparing, land suitability for sustainable agricultural growth in the study area.

2.13 Cropping Pattern

43

Fig. 2.11 LULC of the study area

2.13 Cropping Pattern Cropping patterns are determined by soil type and quality, irrigation infrastructure, climate, crop variety, crop yield, and monetary return on investment. The study’s summer months are characterized by water shortages and extreme heat, which, along with the difficult geography of the study region’s remote places, limits farmers’ ability to use contemporary farming techniques. Traditional farming practices are used by the farmers. Farmers in irrigated regions have been spotted using mechanical farming technologies to cultivate their crops. This is mostly owing to the scarcity of labor in the region. The farmers are supplied with the necessary fertilizers and pesticides by

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private dealers, and the requisite equipment and tools are hired by the majority of the farmers. The chances of double cropping becoming a success are more possible in the black cotton soil but not in the red soil owing to low moisture availability. Millets, early varieties of paddy, and other irrigated crops are cultivated wherever tank irrigation is available, while millets and horse gram are cultivated in rainfed conditions. Cropping patterns suggested for the study area soils are jowar, groundnut in kharif, paddy, maize, ragi, and chillies under irrigated conditions. Black gram and sesamum can also be tried. The dominant crop in the study region is groundnut, cotton, and paddy in the eastern portion of the study region. Because of the sand and sand dunes encroachment in the central portion of the study region along the Hagari River (on the right bank of the river), jujube or red date plantation is the main cropping.

2.14 Population Profile Population expansion is connected to environmental pressures such biodiversity loss, air and water pollution, and increased demand on arable land. It has a detrimental impact on the environment mostly through the use of natural resources and the production of rubbish. With an ever-increasing population and worsening environmental conditions, the task of achieving long-term growth without causing environmental harm has never been greater. The presence or lack of beneficial natural resources can speed up or slow down the economic growth process. The study area is covered with three major mandal’s namely, Bommanahal, Kanekal, and Beluguppa (Urban) covered by 47 Villages (Rural) in the Anantapur district. The total population of the study area is 296100 (Fig. 2.12).

2.15 Conclusion A wide range of elements are present in the semi-arid areas of Anantapur, Andhra Pradesh, which contribute to their distinctive environmental features. The geology, geomorphology, soils, slopes, climate, atmospheric conditions, rainfall patterns, and human population dynamics in this area have all been thoroughly studied in previous literature. Information about the concealer, age, and structure of the rocks and formations in Anantapur has been gained from geological investigations. The landforms, soil types, and water availability of the area are influenced by these geological causes. Understanding landforms and their evolution, including the existence of plateaus, hills, and valleys, has been the focus of geomorphological research. The stability of the entire landscape and the fertility of the soil are impacted by the topography and slopes, which are vital in the processes of water drainage and erosion.

2.15 Conclusion

45

Fig. 2.12 Population density map of the study area

The semi-arid regions of Anantapur have a variety of soil types, according to soil studies. The soils have little organic matter and have a low water-holding capacity. They are frequently sandy, gravelly, and shallow. Such soil properties provide difficulties for agricultural productivity and call for the implementation of suitable soil conservation measures. Anantapur’s semi-arid climate is characterized by extreme heat, scant precipitation, and large seasonal fluctuations. Weather patterns and water availability in the area are greatly influenced by atmospheric conditions. In order to understand the possible effects of climate change and variability, earlier research has looked at the trends in the climate, including temperature variations and rainfall patterns.

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Semi-arid areas of Anantapur are also home to a sizable human population, which is undergoing demographic transition. Increased demand for natural resources due to population growth and related land use patterns, such as agriculture and urbanization, exacerbates problems with soil erosion, water shortages, and environmental deterioration. The prior research on the semi-arid areas of Anantapur, Andhra Pradesh, has shed light on the geology, geomorphology, soils, slopes, climate, atmospheric conditions, rainfall patterns, and dynamics of the human population. For the region’s environmental issues, climate change adaptation, and sustainable land and resource management to be successful, it is essential to comprehend these linked elements. In order to increase resilience, reduce risks, and promote sustainable development in the semi-arid regions of Anantapur, it is crucial to integrate scientific research with policy and community participation going ahead.

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Chapter 3

Process of Aeolian Action

Abstract The wind’s ability to carry silt and deposit it is referred to as the aeolian process. The Earth’s surface is significantly shaped by this process, particularly in dry and semi-arid areas where there is minimal water erosion. Sand dunes, ripples, and other distinctive landforms can be created by the movement of windblown particles. Additionally, the aeolian process has an impact on a number of biological and environmental processes, such as plant cover, air quality, and soil stability. For several fields, including geology, geography, environmental science, and engineering, it is crucial to comprehend the mechanics and impacts of aeolian processes. Keywords Sand dunes · Particles · Ripple marks · Geology · Geomorphology

3.1 Introduction Aeolian desertification is the process by which wind erosion causes the degradation of soil and vegetation in arid and semi-arid regions. The impact of aeolian desertification can be severe and far-reaching, affecting both the natural environment and human. One of the primary effects of aeolian desertification is the loss of fertile topsoil, which can result in reduced crop yields and decreased biodiversity. In extreme cases, it can lead to the complete depletion of soil resources, making it difficult or impossible for vegetation to grow. This can have significant impacts on the livelihoods of local communities, who may rely on agriculture and grazing for their survival. Aeolian desertification can also lead to the formation of sand dunes, which can encroach upon and bury infrastructure such as roads, buildings, and farmland. This can be particularly problematic in areas where human settlements are located near or within desert regions’ communities (Heshmati and Squires 2013; Feng et al. 2018; Chlachula 2021; Li et al. 2022). Furthermore, wind erosion can contribute to the spread of dust and particulate matter, which can have negative impacts on air quality and human health. Dust storms, which can be generated by aeolian desertification, can cause In this chapter, we discuss the process of aeolian weathering, and how this is impacted the semi-arid and in the study area. Additionally, we will discuss the ripple marks caused by the aeolian action. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 P. K. Badapalli et al., Aeolian Desertification, Advances in Geographical and Environmental Sciences, https://doi.org/10.1007/978-981-99-6729-2_3

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respiratory problems and exacerbate existing conditions such as asthma (Bagnold 1941; Cooke and Warren 1973; Greeley and Iversen 1985; Lancaster 1995; Pye and Tsoar 2008; Thomas and Goudie 2000a, b; Tsoar and Pye 2004; Zobeck et al. 2012; Bullard et al. 2016). Aeolian desertification may have a wide-ranging and severe influence on both environmental and human systems (Ravi et al. 2011). To ensure the sustainability of impacted areas and the welfare of local residents, efforts must be made to mitigate the consequences of aeolian desertification (Fig. 3.1).

Fig. 3.1 Aeolian desertification happening along the Hagari River in the semi-arid regions of Andhra Pradesh, India

3.2 Suspension, Saltation, and Surface Creep in Aeolian Process

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3.2 Suspension, Saltation, and Surface Creep in Aeolian Process Wind action is conscious in semi-arid regions, but it is particularly strong in degraded and desert environments. Aeolian topography is created by the geological action of wind, which can be conveniently involved by erosion, transportation, and deposition. The following are three major transportation processes involved in the sand migration by the action of wind. 1. Suspension 2. Saltation 3. Surface creep.

3.2.1 Suspension The process of removing, lifting, and blowing away dry and loose particles of sands and dust by winds is called deflation. The lighter or finer dust-like particles are lifted by the winds and suspended through the wind in its direction. The suspension is depending on the size of the sand particle, velocity of the wind, and direction (Wang et al. 2012). The finest particles, usually clay and silt materials, are carried by the wind in suspension as dust in the study region. The suspension process is one of the primary mechanisms of aeolian action, whereby wind can pick up and transport small particles such as sand, silt, and dust. This process can have significant impacts on the formation of landforms, the erosion of soil and rock, and the transport of nutrients and pollutants. When wind speeds are strong enough to overcome the gravitational forces binding particles to the ground, the suspension process takes place. Turbulence is produced by the wind as it passes over the ground, and this turbulence can lift particles into the air. With larger particles needing greater wind speeds to be suspended, the amount and weight of particles that can be lifted depends on the wind speed. Once in suspension, particles may be moved over great distances and play a role in the development of aeolian landforms like sand dunes and ripples. Additionally, the movement of suspended particles can erode the tops of rocks and soil, resulting in the creation of new landscapes. Human and environmental systems may be significantly impacted by the suspension process. It may help spread dust and other particle matter, which may be harmful to the environment and people’s health. Additionally, as suspended particles function as transporters for nutrients and toxins, it may have an impact on how they are distributed.

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3.2.2 Saltation Sand and gravel are moved throughout after saltation by bouncing, leaping, and hopping in the turbulent wind. By combining the effects of aerodynamic lift and the collision of other salting grains that return to the ground surface, saltating grains regularly climb to heights of up to 50 cm over a sand bed and up to 2 m over the pebbly surface (Alvarez et al. 2012). Saltation, which describes the movement of particles by a sequence of hops or bounces along the ground surface, is another significant aeolian action mechanism. Sand dunes and ripples are produced by this mechanism, which also has the ability to move bigger particles like sand and gravel. Saltation happens when wind speeds are high enough to dislodge particles from the ground but not powerful enough to completely suspend them. Small eddies or vortices are formed as wind passes over the ground, lifting particles briefly into the air before lowering them again. A series of leaping particles can be caused by the impact of the falling particles, which can also dislodge additional particles. Particle size, wind speed, and surface roughness are only a few of the variables that affect the magnitude and frequency of particle leaps. Smaller particles can be transported by both saltation and suspension, but larger particles can only be transported through saltation and require more wind energy to lift. Saltation may have a big influence on how landforms evolve because it causes particles to bounce and collide with the ground, creating ripples and dunes. In addition to moving particles through saltation, erosion of rock and soil surfaces can result in the creation of new landscapes. Salting may have detrimental effects on both environmental and social systems. The impact of bouncing particles can harm plant roots and stems, and the migration of particles through saltation can contribute to the deterioration of soil and plants. Additionally, saltation may let dust and other particle matter spread, which might be harmful to both human health and the quality of the air. In general, saltation is an essential part of the aeolian activity, with substantial effects on the formation of landforms, erosive processes, and environmental quality. For the purpose of foreseeing and minimizing the effects of wind erosion in natural and human systems, it is crucial to comprehend the mechanics of this process.

3.2.3 Surface Creep Surface creep is the movement of comparatively larger particles caused by high winds along the ground’s surface. When a result, when the particles move, they bump into one another and further comminute into smaller particles. Through the processes of saltation and surface creep, attrition is the mechanical wear and tear that the particles endure while being carried by the wind.

3.2 Suspension, Saltation, and Surface Creep in Aeolian Process

55

Larger particles migrate over the ground’s surface while being influenced by the wind, a phenomenon known as surface creep in aeolian motion. This process can move rocks like pebbles, cobbles, and boulders, and it may have a big impact on how erosion happens and how landforms are created. When wind energy is transmitted to the ground’s surface, particles move over the ground by rolling, sliding, or bouncing. This is known as surface creep. Numerous variables, including wind speed, particle size, surface roughness, and moisture content, affect the magnitude and frequency of particle motions. Surface creep may have a big influence on how landforms form because it causes particles to move and collide, resulting in patterns of gravel, stones, and boulders. Particle movement caused by surface creep can also contribute to soil and rock surface erosion, which creates new landscapes. Surface creep may have detrimental effects on both environmental and social systems. With the impact of rolling or sliding particles on plant roots and stems, the movement of bigger particles can lead to the degradation of soil and plants. Furthermore, surface creep can contribute to the development of desert pavement, a layer of gravel and stones that can hinder plant growth and accelerate erosion. The formation of landforms, erosive processes, and environmental quality are all significantly impacted by surface creep, which is a key part of aeolian activity. For the purpose of foreseeing and minimizing the effects of wind erosion in natural and human systems, it is crucial to comprehend the mechanics of this process. Figure 3.2 depicts the wind action.

Fig. 3.2 Aeolian transportation process

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3.3 Wind Direction and Speeds in the Study Area The study area has experienced significant geomorphological changes due to wind activity. The presence of unstable dunes and alluvium can be observed along the entire stretch of the Hagari River, resulting from strong surface winds during the southwest monsoon season (June to September). This sand has been displaced, leading to land degradation and eventual desertification. Sand and dunes play a crucial role in driving ecosystem changes within the study area, exhibiting various characteristics such as size, shape, environmental factors, complexity, and wind direction (Kumar et al. 2019). Arid and semi-arid regions face a high risk of wind erosion. This erosion process involves both the removal and deposition of soil particles caused by wind action, as well as the abrasive effects of particles in motion during transportation. In areas where sand accumulates with rainfall, its stabilization is influenced by the extent of vegetation cover it supports. This interaction between sand, wind erosion, and vegetation cover plays a crucial role in shaping the local landscape. The winds are floats from the southwest (SW) to northeast (NE) directions in the study area. The sand migration along the Hagari River is from SW to NE. A digital anemometer is used for measuring the wind speeds in the study region. In between June and August strong surface winds happening in the study area, recorded as 6 km/h is the lowest and 36 km/h is the highest (Fig. 3.3). Rather than the present surface winds we also collated the wind speeds for the past three decades from 1990 to 2020. Plate 3.1 depicts the wind speeds collection in the study region using the digital anemometer. From June to August, 30 wind station locations and wind speeds have been collected using GPS and anemometer in and around the study area (Table 3.1), and further Wind Speed Spatial Distribution Map (WSSDM) has been generated

Fig. 3.3 Anemometer readings for wind speeds along the Hagari River

3.3 Wind Direction and Speeds in the Study Area

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Plate 3.1 Anemometer readings collection in the field, along the Hagari River

using the IDW interpolation method using the ArcGIS environment. Plate 3.1 depicts anemometer readings collection in the field, and Fig. 3.4 shows the WSSDM of the study area.

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Table 3.1 GPS locations, elevation, and anemometer wind speeds S. no

Longitude

Latitude

Elevation

Wind speeds

1

77.069808°

14.746487°

480

26

2

77.094293°

14.771728°

449

25

3

77.101298°

14.786307°

451

26

4

77.109733°

14.822482°

458

24

5

77.098158°

14.870086°

451

28

6

77.090540°

14.897467°

445

30

7

77.084185°

14.901699°

443

36

8

77.076950°

14.915261°

442

36

9

77.059743°

14.927371°

436

38

10

77.048973°

14.933409°

435

35

11

77.051152°

14.939719°

442

34

12

77.044286°

14.957891°

433

32

13

77.048518°

14.968641°

432

36

14

77.048165°

14.980458°

430

34

15

77.048279°

15.000994°

428

32

16

76.927393°

15.012023°

490

22

17

76.982637°

14.976120°

442

24

18

77.005047°

14.945092°

438

24

19

76.945500°

14.907177°

449

26

20

76.991761°

14.926932°

445

28

21

76.970971°

14.858264°

454

26

22

77.005728°

14.828106°

446

26

23

77.026875°

14.813603°

464

24

24

77.018904°

14.776378°

478

24

25

77.117959°

14.693182°

485

22

26

77.131905°

14.648153°

503

24

27

77.203288°

14.684150°

495

28

28

77.260191°

14.640949°

470

26

29

77.163441°

14.760921°

477

26

30

77.154444°

14.809314°

468

24

3.4 Sand Dune Formation Sand builds up in layers on top of one another due to wind, eventually producing dunes. After the first mound has developed, it will keep accumulating on the windward side until the dune’s edge is crushed by its weight (Goudie et al. 1979). The dune falls as the slant becomes too great to support the weight. The angle of repose is typically between 30° and 34°, but it varies with grain size, wind speed, and how rounded

3.4 Sand Dune Formation

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Fig. 3.4 Spatial distribution of wind speeds in the study region

each grain is. If there is no wind blowing in the other direction or any obstructions, these dunes collapse in the same direction as the wind, becoming barchan dunes (Wiggs 2001). Figure 3.5 depicts the dune formation process, and Fig. 3.6 depicts the moment of sand dunes.

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Fig. 3.5 Sand dune formation process

Fig. 3.6 Sand dune moment

3 Process of Aeolian Action

3.5 Ripple Marks

61

3.5 Ripple Marks Sedimentary formations called ripple marks show that the wind, current, or waves have stirred the silt. Sediment ridges called ripple marks are created when a layer of sediment is blown by the wind at the same time. Each ridge is nearly equal distance from the ripple mark on either side and is generated perpendicular to the direction of the wind (Alvarez et al. 2012). Ripple markings come in two different varieties: symmetrical ripple marks and asymmetrical ripple marks.

3.5.1 Symmetrical Ripple Marks Symmetrical ripple marks typically form when two-way currents interact, resulting in a wave-like structure. These ripple marks exhibit pointed crests and rounded troughs, without a predominant inclination toward any specific direction. However, in the study region, no symmetrical ripple marks have been observed.

3.5.2 Asymmetrical Ripple Marks Asymmetrical ripple marks, in contrast to symmetrical ones, are formed by the action of one-way currents. These ripple marks exhibit pointed crests and rounded troughs, but they are noticeably inclined in the direction of the current (Alvarez et al. 2012). This characteristic makes them valuable as paleocurrent indicators, as they provide insights into the direction of ancient currents based on their distinctive asymmetrical shape. Figure 3.7 depicts the ripple marks and their shape.

Fig. 3.7 Symmetrical and asymmetrical ripple marks

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3.5.3 Unidirectional Asymmetrical Ripple Marks in the Study Area Asymmetrical ripple marks are seen along the Hagari River in the study region, which reveals that the wind or current direction is only from one side, and these types of ripples are called unidirectional asymmetrical ripple marks. This reveals that the SW monsoon winds are responsible causes the sand migration, and desertification along the Hagari River. The following Plates 3.2, 3.3, 3.4, 3.5, 3.6, 3.7 and 3.8 reveal the unidirectional asymmetrical ripple marks and sand migration that causes desertification in the study region.

3.6 Sand Dunes Present in the Study Area Sand and sand dunes play a significant role in shaping environmental ecosystems, and they can be classified based on various factors such as dune size, shape, environmental occurrence, internal complexity, and wind direction. Among the different types of dunes, five main classifications are transverse, oblique, barchans, longitudinal, and parabolic. In the study area, the prevailing low rainfall contributes to the presence of sandy soil. The scarcity of moisture makes it easier for silt and sand-sized particles to be carried away by wind, while the remaining particles gradually consolidate into a compact layer known as desert pavement (Kumar et al. 2019). This phenomenon reflects the environmental conditions and processes influenced by the region’s arid

Plate 3.2 Wind direction and ripple formation in the study area

3.6 Sand Dunes Present in the Study Area

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Plate 3.3 Unidirectional asymmetrical ripple marks in the study area

Plate 3.4 Ripple marks along the Hagari River

climate and limited water availability. Three types of sand dunes are present in the study area, they are as follows: 1. Barchan dunes, 2. Parabolic dunes, 3. Nebkha or Coppice dunes.

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Plate 3.5 Sand migration in the form of ripple marks to the agricultural field in the study region

Plate 3.6 Asymmetrical ripple forms in the study region

3.6.1 Barchan Dunes Along the Hagari River, there are many Barchans dunes formed by the unidirectional wind moment by the SW monsoon seasons, and they are not static but continuously

3.6 Sand Dunes Present in the Study Area

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Plate 3.7 Asymmetrical ripple migrated to agricultural field and formed desert environment in the study area

migrated because of wind speeds along with their directions. In the study region this type of barchan dunes found to migrated from June to August only, the remaining months of the year they became stagnated. The development of the Barchans is started with small-sized ripples, and in the dune coarse, the size of the ripple became higher and finally formed into Barchans (Plate 3.9). These asymmetrical ripple marks continuously formed with high-velocity winds and the size became increased with time and finally formed as a “Barchan’s sand dune.” Barchans are crescent-shaped sand dunes formed primarily by the wind blowing predominantly from one direction. They are the most widespread type of dunes found in sandy deserts worldwide. Barchans have a convex shape that faces the wind, with the crescent’s horns pointing in the downwind direction, indicating the lateral movement of the sand. These dunes exhibit distinct asymmetry in their cross section, featuring a gentle slope facing the wind and a steeper slope, called the slip face, on the side facing away from the wind. Plates 3.10 and 3.11 depict the Barchan-type sand dune formed by the unidirectional winds in the study area. Barchans can reach heights of 5–20 m (15–60 feet) and have a width of approximately 50 m (150 feet) at the base, measured perpendicular to the wind direction. These dunes gradually move with the wind, undergoing erosion on the windward side and deposition on the leeward side. The migration rate of barchans can vary from around one meter to a hundred meters per year. They often appear as individual dunes grouped together and may form chains that stretch across a plain in alignment with the prevailing wind. Plate 3.11 illustrates the presence of isolated sand dunes in the study area.

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Plate 3.8 Asymmetrical ripple marks observation in the field

3.6.2 Parabolic Dunes A large portion of the sand sheet is vegetated. A parabolic dune may develop if high winds destroy a part of the vegetative sand (often known as a blowout). If blowout sand is deposited on the parabolic dune’s opposite slope, leeward motion results. As the leeward “nose” of the dune migrates forward into the main dune field, vegetation

3.6 Sand Dunes Present in the Study Area

67

Plate 3.9 Small-sized unidirectional asymmetrical ripple marks in the study area

maintains the “arms” of the dune in position. In the sand sheet southwest of the main dune area, parabolic dunes are typical. Following Plate 3.12 depicts the parabolic dunes in the study area along the Hagari River. Most of the parabolic dune fields cover with little vegetation cover on the top of the dune.

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Plate 3.10 Barchan sand dune in the study area

Plate 3.11 Height mound Barchan sand dunes in the study area

They represent environmental elements such as wind speed and direction, sand availability, vegetation, physical obstacles, and distance from the source that impact sand movement and deposition. Each single dune type is caused by a different combination of these factors, and the genesis and evolution of the main dune types allow for generalization.

3.7 Impact of Aeolian Weathering in Semi-arid Lands

69

Plate 3.12 Parabolic sand field in the study area

3.6.3 Nebkha or Coppice Dunes Sand migration happens along the Hagari River, by the SW monsoon winds hence remaining months the migrated sand fields remain stagnated, and formed Nebkha sand dunes in the study area. These are extremely basic dunes that grow around plants, typically on the sand sheet, and are also known as coppice dunes. Windblown sand is being ground up by clumps of grass and bushes; as the sand becomes deeper, the plants also develop taller, allowing more sand to accumulate around them. Along the Hagari River, we can get this type of dunes. Plate 3.13 depicts Nebkha dunes in the study area.

3.7 Impact of Aeolian Weathering in Semi-arid Lands Aeolian weathering is a process in which wind-driven particles cause erosion and breakdown of rock formations. This type of weathering is most common in semi-arid regions, where the lack of vegetation and high winds allow for significant movement of particles. The process of aeolian weathering starts when wind picks up small particles of sand and dust, which can range in size from a few microns to several millimeters. These particles are then carried along by the wind, and as they collide with other particles or rocks, they can cause abrasion and erosion. Over time, this process can lead to the formation of sand dunes and other landforms (Kocurek and

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Plate 3.13 Nebkha sand dunes with plant cover sand sheets in the study area

Havholm 1993; Lancaster and Baas 1998; Li et al. 2005; McKenna Neuman et al. 2013; Hugenholtz et al. 2014; Bullard and Livingstone 2016). Due to the mixture of strong winds and little rainfall, aeolian weathering can have a particularly large influence in semi-arid areas. Since there is little to hold the soil in place due to the lack of vegetation, the wind may readily pick up and transport away loose particles. This may cause soil erosion, which would be bad for the environment and for farming. Aeolian weathering can also have an effect on infrastructure and human-made constructions. Sand and dust carried by the wind can harm structures and roadways while also posing a danger to drivers. Aeolian weathering occasionally even results in the development of sandstorms, which can have detrimental effects on both human and animal health (Ravi and D’Odorico 2005; Thomas and Goudie 2000a, b; Warren and Lancaster 2003; Zobeck et al. 2012). Inclusive, aeolian weathering is a prominent natural phenomenon that has a big impact on ecosystems and landscapes in semi-arid areas. While it may have detrimental effects on human activities, it also plays a crucial role in the creation and upkeep of a variety of dynamic settings.

3.8 Conclusion Aeolian action is a process that affects the semi-arid regions of Anantapur, Andhra Pradesh, and it significantly influences the landscape. The term “aeolian action” describes how wind moves and deposits sediments. The effects of wind erosion on soil deterioration and the evolution of landforms in this area have been noted in

References

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earlier research. The procedure entails raising and detaching loose particles, moving them by saltation or suspension, and then depositing them. Implementing proper soil conservation measures and land management methods to reduce the negative impacts of wind erosion in the semi-arid districts of Anantapur requires a thorough understanding of the dynamics of aeolian activity. Approximately 80% of the Hagari River flows through the Bommanahal, Kanekal, and Beluguppa mandals, while the remaining 20% traverses Gummagatta, Rayadugam, D-Hirehal, and Bramhasamudram mandals in the semi-arid Anantapur District. The Hagari River holds significant importance in the region; however, it is a seasonal or ephemeral river, remaining dry throughout the year. The mandals of Bommanahal, Kanekal, and Beluguppa face challenges of sand migration and desertification. The origin of the sand can be traced back to an extreme flash flood during the Great Storm of May 1851, approximately 170 years ago. Since then, the Hagari River has likely deposited the majority of windblown sands on its right bank. From June to August, the region experiences strong surface winds, ranging from 36 to 38 km/h, blowing from the west to the east during the southwest monsoon. These high-speed winds are responsible for sand migration and subsequent desertification. The prevailing wind direction in the study area is southwest (SW) to northeast (NE). Evidence of this easterly migration can be observed through the presence of unidirectional asymmetrical ripple marks on the dunes. The study area comprises various types of dunes, including barchan dunes, parabolic dunes, and nebkha or coppice dunes.

References Alvarez LJ, Epstein HE, Li J, Okin GS (2012) Aeolian process effects on vegetation communities in an arid grassland ecosystem. Ecol Evol 2(4):809–821. https://doi.org/10.1002/ece3.205 Bagnold RA (1941) The physics of blown sand and desert dunes. Methuen Bullard JE, Livingstone I (2016) Aeolian geomorphology: dust, sand, and landforms. Wiley Bullard JE, Livingstone I, Merritt J, Wiggs GF (2016) Aeolian processes and the biosphere. Rev Geophys 54(3):685–719 Chlachula J (2021) Between sand dunes and hamadas: environmental sustainability of the thar desert, West India. Sustainability 13(7):3602 Cooke RU, Warren A (1973) Geomorphology in deserts. University of California Press Feng L, Jia Z, Li Q, Zhao A, Zhang Z, Zhao Y (2018) Spatiotemporal change of aeolian desertification land distribution in northern China from 2001 to 2015. J Indian Soc Remote Sens 46:1555–1561 Goudie AS, Cooke RU, Doornkamp JC (1979) The formation of silt from quartz dune sand by salt-weathering processes in deserts. J Arid Environ 2(2):105–112 Greeley R, Iversen JD (1985) Wind as a geological process on Earth, Mars, Venus and Titan. Cambridge University Press Heshmati GA, Squires VR (2013) Introduction to deserts and desertified regions in China. Combating desertification in Asia, Africa and the Middle East: proven practices, pp 3–20 Hugenholtz CH, Wolfe SA, Arrowsmith JR (2014) Aeolian processes and the biosphere. In: Aeolian geomorphology: a new introduction. Wiley, pp 207–233

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Kocurek G, Havholm KG (1993) Eolian systems. Sediment Geol 86(1–2):1–3 Kumar BP, Babu KR, Rajasekhar M, Ramachandra M (2019) Assessment of land degradation and desertification due to migration of sand and sand dunes in Beluguppa Mandal of Anantapur district (AP, India), using remote sensing and GIS techniques. J Ind Geophys Union (March 2019) 23(2):173–180 Lancaster N (1995) The development of fluvial and aeolian morphologies on an artificial dune, Sydney, Australia. Geomorphology 12(4):299–318 Lancaster N, Baas A (1998) Aeolian geomorphology: introduction. In: Geomorphology of desert dunes. Routledge, pp 1–22 Li Q, Wu P, Fan H, Ma Y, Li R, Zhao G (2022) Spatial distribution pattern and natural causes analysis of sandy desertification land in Ali area. Sustainability 14(14):8734 Li X, Zhang Q, Shao Y, Dong Z (2005) The role of Aeolian dust in shaping desert ecosystems. In: Vegetation degradation in Central Asia under the impact of human activities. Springer, pp 191–204 McKenna Neuman C, Munoz N, Marticorena B (2013) Aeolian dust emissions and their potential impacts on climate. Aeol Res 9:3–9 Pye K, Tsoar H (2008) Aeolian sand and sand dunes. Springer Science & Business Media Ravi S, D’Odorico P (2005) Patterns of aeolian erosion and deposition in a semi-arid environment: results from field observations and simulations. J Arid Environ 62(1):75–94 Ravi S, D’Odorico P, Breshears DD, Field JP, Goudie AS, Huxman TE, Zobeck TM et al (2011) Aeolian processes and the biosphere. Rev Geophys 49(3) Thomas DS, Goudie AS (2000a) Aeolian environments, landforms and sediments. Wiley Thomas DS, Goudie AS (2000b) The dictionary of physical geography. Wiley-Blackwell Tsoar H, Pye K (2004) Dust transport and the question of desert loess formation. Sedimentology 51(2):233–245 Wang X, Hua T, Zhang C, Lang L, Wang H (2012) Aeolian salts in Gobi deserts of the western region of Inner Mongolia: gone with the dust aerosols. Atmos Res 118:1–9 Warren A, Lancaster N (2003) Aeolian processes and landforms in deserts. In: Treatise on geomorphology, vol 10. Academic Press, pp 527–558 Wiggs GF (2001) Desert dune processes and dynamics. Prog Phys Geogr 25(1):53–79 Zobeck TM, Van Pelt RS, Ravi S (2012) Aeolian processes: a diverse global system. Aeol Res 3(2):165–166

Chapter 4

Surface Micromorphology of Aeolian Sand Grains

Abstract This chapter the results of scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDAX) analysis of sand samples collected from aeolian desertification areas. The SEM images revealed the microstructure and morphology of the sand grains, including their size, shape, and surface texture. The EDAX analysis provided elemental composition data of the sand grains, which helped to identify mineralogical components and their spatial distribution. The study found that the sand samples from the aeolian desertification areas were dominated by quartz, feldspar, and mica minerals, with small amounts of other minerals such as calcite, gypsum, and hematite. These results can provide valuable information for understanding the geological processes that lead to aeolian desertification and developing effective measures for preventing or mitigating this phenomenon. Keywords Sand · Micromorphology · Aeolian · SEM · EDAX · Elements

4.1 Introduction Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDAX) are advanced techniques used for analyzing the composition and morphology of materials. SEM provides high-resolution, three-dimensional imaging of the sample surface, while EDAX identifies the elemental composition of the sample. The combination of these techniques is useful in materials science and engineering for investigating the properties of various materials, such as metals, polymers, and ceramics (Brown and Leventhal 2015; Chen et al. 2017; Li and Wu 2018). SEM uses an electron beam to scan the sample’s surface and produce highresolution images. The electron beam interacts with the sample, causing secondary electrons to be emitted, which are detected by the SEM and used to create images with high magnification and depth of field. SEM imaging can reveal the surface In this chapter, we will discuss the aeolian sand micromorphology by using the SEM and EDAX studies. Using the micromorphological studies we will estimate the rate of sand migration in the selected study area. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 P. K. Badapalli et al., Aeolian Desertification, Advances in Geographical and Environmental Sciences, https://doi.org/10.1007/978-981-99-6729-2_4

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morphology of a sample, such as surface features, defects, and grain structures (Peth and Horn 2016; Hunt 2017; Goldstein et al. 2018). EDAX is often used in conjunction with SEM imaging to analyze the elemental composition of the sample. EDAX uses X-rays to identify the elements present in the sample. When the sample is bombarded with the electron beam, it emits Xrays with characteristic energies that correspond to specific elements. The EDAX detector measures the intensity of these X-rays, allowing for the identification and quantification of elements in the sample (Zhan et al. 2017; Guevara et al. 2019). The combination of SEM and EDAX can provide valuable insights into the structure and properties of materials, which can be used to optimize materials design, manufacturing processes, and quality control. Applications of SEM and EDAX include failure analysis, materials characterization, and microstructure analysis. As a result, SEM and EDAX analysis are effective methods for analyzing the morphology and composition of materials. These methods are used to learn more about the characteristics and behavior of diverse materials and have several applications in materials science and engineering. Figure 4.1 represents the SEM and EDAX equipment.

4.2 SEM and EDAX Studies for Visual Disaster of Aeolian Desertification SEM and EDAX analysis can be used to investigate the impact of Aeolian desertification on the environment. Aeolian desertification refers to the process of soil degradation and erosion caused by wind action, which can lead to the formation of deserts and other arid landscapes. This process can have significant environmental and economic impacts, including loss of arable land, biodiversity, and water resources. SEM imaging can be used to study the morphological changes of the soil and identify the physical characteristics of soil particles, such as size, shape, and surface features. In Aeolian desertification, the movement of sand and dust particles can cause abrasion and erosion of the soil surface. SEM imaging can reveal the extent of this damage, including the formation of cracks, fissures, and other surface features (Rey and Vasconcelos 2017; Barabasz-Krasny et al. 2018; Gama and Gama 2018). EDAX analysis can be used to investigate changes in the elemental composition of soil caused by Aeolian desertification. The accumulation of sand and dust particles can introduce new elements to the soil, which can alter its chemical properties. EDAX data can be used to identify the presence and concentration of elements such as silicon, aluminum, iron, calcium, and magnesium in the soil, which can provide insights into the soil’s chemical and mineralogical characteristics (Carter and Gregorich 2010; Klug and Alexander 2013; Janssen et al. 2016; MacKenzie and Zenger 2019).

4.3 SEM and EDAX Analytical Procedure

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Fig. 4.1 SEM/EDAX equipment. a and b smart coater and specimen chamber

By combining SEM and EDAX analysis, researchers can gain a comprehensive understanding of the physical and chemical changes in soil caused by Aeolian desertification. This information can be used to develop strategies for mitigating the environmental impact of Aeolian desertification, such as soil conservation and restoration, land use planning, and vegetation management.

4.3 SEM and EDAX Analytical Procedure Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDAX) are analytical techniques commonly used in materials science and engineering to investigate the composition and morphology of materials. The following is a general procedure for SEM and EDAX analysis:

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4.3.1 Sample Preparation The first step is to prepare the sample for analysis. The sample must be clean and dry. The surface may need to be polished or sputter-coated with a thin layer of conductive material (such as gold or carbon) to avoid charging during SEM imaging (Ahumada-Sempoal et al. 2019).

4.3.2 SEM Imaging The sample is then loaded into the SEM chamber and scanned with an electron beam. The beam interacts with the sample, producing secondary electrons that are collected by a detector to create an image. SEM images provide high-resolution, three-dimensional views of the sample’s surface morphology.

4.3.3 EDAX Analysis EDAX is often used in conjunction with SEM imaging to identify the elemental composition of the sample. The EDAX detector is mounted inside the SEM chamber and measures the characteristic X-rays emitted by the sample when it is bombarded with the electron beam. The X-rays are specific to each element, and their intensity is proportional to the concentration of that element in the sample. EDAX data can be used to determine the elemental composition of the sample and to generate elemental maps showing the distribution of elements in the sample (Ghadiri, and Sander 2017; Thompson and Shimizu 2018).

4.3.4 Interpretation and Analysis The SEM and EDAX data can be interpreted and analyzed to understand the material properties and composition. SEM images can be used to identify surface features such as cracks, pores, and grains, while EDAX data can provide quantitative elemental analysis. The results of the analysis can be used to optimize materials properties or troubleshoot problems in manufacturing processes.

4.4 Sand Sample Collection

77

4.3.5 Reporting The final step is to report the results of the SEM and EDAX analysis. The report should include a description of the sample, sample preparation details, SEM imaging parameters, and EDAX data analysis results. Interpretations of the data should be provided to help the reader understand the significance of the results (Zhang et al. 2018). It is important to note that the specific procedure for SEM and EDAX analysis may vary depending on the instrument and sample type. The instrument operator should consult the manufacturer’s instructions and follow best practices for sample preparation and analysis.

4.4 Sand Sample Collection In the study area, we have collected ten sand samples along the right side of the Hagari River, where the sand migration happens by the Aeolian action. Ten locations are identified, and each location is considered into one unit; in each unit, we collect at least five samples, at one kilogram. All five samples were collected in a unit and processed into one sample, by using the coning and quartering process. The process is repeated up to the required sample pocket of one kilogram. The same process is followed in ten sampling sites and the collected ten sand samples in ten different locations. All the collected sand samples are kept in a polythene bag, by writing the sample location number, and latitude and longitude values.

4.4.1 SEM/EDAX Analysis for Sand Samples The collected sand sample materials were sorted by using special sieves to a grain size of 0.5–1.00 mm. Further, these sand samples are analyzed in the geochemical laboratory for further process. Evaluated fraction of grain size was further boiled with concentrated hydrochloric acid to remove undesirable carbonates, clays, and organic materials. The samples were then rinsed and neutralized with distilled water and dried in a wet environment at room temperature. Further, the samples are examined under the binocular microscope and extracted 100 to 200 sand or quartz grains for further studies. The extracted sand or quart samples are examined for surface features, and micromorphological features using the scanning electron microscope (SEM), and energy dispersive X-ray spectroscopy (EDAX). For the SEM analysis, the samples were prepared ordinarily—the material of the sample was mounted with carbon tape on a standard stub. A carbon coating of 20 nm was applied to prevent sample charging and allow subsequent EDAX mapping

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of elemental distribution in the case of unsorted and complex grains. A detailed examination of the surface features was performed with the TESCAN high-resolution imaging field emission electron microscope MIRA equipped. The type of secondary– electron detector for very detailed sample topography and structure visualization, and energy dispersive spectrometer, which detects characteristics spectrum of X-ray to obtain information its elemental composition.

4.5 Image Snapper for SEM This software module is designed for automated image acquisition of large-area samples, when it is desired to obtain images with a resolution higher than the maximum resolution of a single image. It uses motorized stage movements and image stitching to provide a high-resolution ion panoramic image of a selected part of the sample or the whole sample. The final panoramic image is created for each sample at optional resolution. The selected area is divided into multiple scanning fields with the defined field of view and overlaps for stitching. This module allows automated navigation of the stage with the sample according to a template (SEM panoramic image, optical image, digital camera image, etc.). It needs just two points of calibration between the live SEM image of the sample and the template. When the position of the sample is calibrated, the template can be used as a clicking map for stage navigation. A table of interesting positions, relative to the reference points, can be defined easily.

4.6 EDAX EDS, or energy dispersive X-ray analysis, is a system software utilized for analyzing the energy spectrum and determining the abundance of specific elements within a sample. In this study, EDAX is employed to determine the chemical composition of minerals in the sand grains. A typical EDAX plot displays X-ray counts versus energy (in keV). Energy peaks in the plot correspond to different elements present in the sample. These peaks are generally narrow and distinct, although many elements may yield multiple peaks due to their characteristic energy signatures.

4.7 Micromorphology of Sand Grains (SEM/EDAX) Thirteen sand samples are collected along the right side of the Hagari River (Table 4.1) and evaluated fractions of grain size by boiling with the hydrochloric acid and removing undesirable carbonates, clays, and organic materials cleaned with distilled water and dried at room temperature. Further, these sand samples are examined under

4.7 Micromorphology of Sand Grains (SEM/EDAX)

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Table 4.1 Sand sample locations and migration happening in villages in the study area Study mandal Bommanahal

Location of the sample Longitude

14° 58' 14.67'' N

77° 3' 11.13'' E

Bollanaguddam

77° 2' 50.29'' E

Kalludevanahalli

77° 3' 14.65'' E

Govindawada

14°

57'

15.20''

N

14° 56' 9.57'' N 14° Kanekal

54'

28.34''

N

77°

4'

50.98''

E

D. Honnuru

14° 52' 57.07'' N

77° 5' 28.91'' E

Bidurukuntham

14° 52' 34.6'' N

77° 5' 51.76'' E

Meenahalli

14°

52'

8.13''

N

77°

5'

51.14''

E

Garudachedu

14° 51' 5.49'' N

77° 6' 36.00'' E

Thumbiganuru

14° 49' 17.00'' N

77° 6' 38.93'' E

Malyam

14° Beluguppa

Sand migrated villages

Latitude

46'

50.33''

N

77°

5'

4.99''

E

Kalekurthi

14° 44' 36.02'' N

77° 4' 3.21'' E

Sreerangapuram

14° 42' 32.39'' N

77° 3' 4.03'' E

Narinjagundlapalle

14°

40'

53.36''

N

77°

3'

29.26''

E

Narasapuram

the binocular microscope and picked required sand samples for SEM and EDAX analysis for their micromorphological studies.

4.7.1 SEM Analysis of Sand Grains The sand grains extracted from the sample were carefully mounted on a standard stub using carbon tape. The stub was then placed in a smart coater for a duration of two to five minutes. In this study, a coating of gold was applied to the sand grains to protect them from the thermal effects of the emitted rays during analysis and to enhance the secondary electron signal required for topographic examination in the SEM. Once coated, the sample was transferred from the smart coater to the specimen chamber for SEM analysis, which enabled visualization of the topography and structure of the sand grains (Barden and Smith 2016; Kumar et al. 2019). Special software models such as Image Snapper and X-Positioner were utilized as part of the SEM software. These software tools facilitated the analysis of the micromorphology of each sand grain in the sample. Image Snapper allowed for the creation of panoramic images for individual grains by dividing the sample into different scanning fields, offering high optical resolution. This panoramic image served as a template for the X-Positioner, which automatically guided the SEM to examine and image each grain in detail, enabling a comprehensive evaluation of their micromorphology (Kumar et al. 2019). In the panchromatic (black and white) SEM images of the sand grains at various magnifications, the study of the sand grains reveals various forms and structures.

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According to the current investigation, desert varnish—which gives grains a reddish or rusty tint—occurs often. The samples of desert sand have matt or, less commonly, semi-glass-shaped granules. A few of the sample grains are rounded, while others have an oval or semi-oval form. Sand grains’ micromorphology with a scanning electron microscope (SEM) reveals the predominate surface patterns that are commonly articulated by aeolian sediments, including oval to semi-oval forms, V-shaped pits, dish-shaped breaking concavities, crescent-shaped features, and conchoidal fractures (Badapalli et al. 2021). All the extracted sand samples are examined in SEM and revealed the micromorphological features of sand samples with different magnifications like 500, 200, 100, 50, 20, and 5 µm. Figure 4.2a–d depict the SEM imageries with 500 µm, and these sand grains have different types of minerals grains like quartz, feldspar, and tourmaline. Sand samples are dominated with the quartz grains, and the alterations are also clearly visible in the imageries. Well-rounded, rounded, V-shaped pits, and desert varnish have been seen in the sand samples under SEM examination. Figure 4.2a–d were used as a template for X-Positioner to automatically navigate SEM to individual grains for detailed micromorphological evaluation and imaging.

Fig. 4.2 High-resolution SEM panoramic image of sand samples. a, b, c, and d: are the 500 µm magnification SEM imageries. Desert varnish can be seen in the samples. d: Quartz, feldspar, and tourmaline sand grains

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81

Further, the sand grains are analyzed in detail; for this, the magnification has increased to 100 µm and extracted each grain for mineralogical and morphological studies. Figure 4.3a–d depict the 100 µm magnification. In Fig. 4.3, the oval to semioval, and V-shaped surface shapes are identified, these shaped grains having less transportation rate comparatively with rounded shapes. Among the thirteen villages, five villages have dominated V-shaped oval to semi-oval shaped sand grains, and hence, migration rate is also very low to moderate speeds. In Beluguppa Mandal, all three villages have oval to semi-oval V-shaped morphological sand grains. Sreerangapuram and Naringagundla Palli villages have ovalshaped sand grains, and hence, the migration rate is “Low.” In the Narasapuram Village, semi-oval-shaped sand grains are present, and hence, the migration is “Very low” (Table 4.2). Well-rounded to subrounded sand grains are identified in the Bommanahal and Kanekal Mandals, and among the thirteen villages, eight villages are identified with these well-rounded to rounded and subrounded sand grains. These well-rounded to rounded and subrounded sand samples are easily eroded or migrated by the aeolian action, and the transportation rate is also high; hence, the migration is also very high

Fig. 4.3 High-resolution SEM panoramic image of sand samples with 200 and 100 µm. a, b show oval to semi-oval-shaped sand grains. c: Quartz grain with an oval shape with a conchoidal fracture. d: V-shaped sand grain dominants

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Table 4.2 Surface micromorphology and rate of sand migration and desertification Study mandal

Sand migrated villages

Micromorphology of sad grain

Rate of migration/ desertification

Bommanahal

Bollanaguddam

Subrounded

Moderate

Kalludevanahalli

Rounded

High

Govindawada

Well-rounded

Very high

Kanekal

Beluguppa

D. Honnuru

Well-rounded

Very high

Bidurukuntham

Rounded

Moderate

Meenahalli

Subrounded

Moderate

Garudachedu

Rounded

High

Thumbiganuru

Well-rounded

Very high

Malyam

Well-rounded

Very high

Kalekurthi

Subrounded

Moderate

Sreerangapuram

Angular to subangular

Low

Narinjagundlapalle

Angular to subangular

Low

Narasapuram

Subangular

Very low

in the study area. Figure 4.4 depicts the well-rounded, rounded, and subrounded sand samples. In Bommanahal Mandal of Govindawada and D-Honnuru, villages are having well-rounded sand particles, Kalludevanahalli Village has moderate sand migration because of sample rounded micromorphological feature, and Bollanaguddam Village has moderate to low migration rate because of subrounded morphological features of sand grains (Table 4.2). In Plates 4.4a, b, a well-rounded to rounded quartz sand grain has been seen with the magnification of 100 µm. The aeolian wind plays a very important role in the transportation of these types of sand grains to greater distances along their direction of motion and deposited over long distances. In Plates 4.4c, d, subrounded sand grains are perceived with 100 µm magnification. Silica dissolution has been seen on the surface of the sand grains; this reveals that the transportation rate of the wind is high. In Fig. 4.5, surfaces of sand grains are revealed by their texture. In Plate 4.5a, irregular depressions are identified, and this is because of aeolian action. These irregular depressions are reshaping the sand grain from oval to subrounded and subrounded to rounded in its shape. In Plate 4.5b, a smooth surface has been identified, and this is because of the resistance to weathering. Most of the quartz particles show this smoothness, and becomes looks desert vanish to that sand grain. In Plates 4.5c, d, silica dissolutions are identified, and this is because of the atmospheric humidity and complex environmental conditions in the study area. The rate of migration of sand particles are depending on the micromorphological conditions. The well-rounded sand sample is identified at Govindawada, D-Honnuru, villages of Bommanahal Mandal, and Thumbiganuru, Malyam villages of Kanekal

4.7 Micromorphology of Sand Grains (SEM/EDAX)

83

Fig. 4.4 High-resolution SEM panoramic image of sand samples with 100 µm. a: Well-rounded quartz grain with high relief. b: Rounded quartz grain with a conchoidal fracture. c: Subrounded sand grain with less relief d: Subrounded silica dissolution during the transportation

Mandal, and hence, the rate of sand migration and desertification is considered to be “Very High.” The rounded sand samples are identified at Kalludevanahalli Village of Bommanahal, and Garudachedu, Bidurukuntham, villages of Kanekal Mandal, and hence, the migration of sand and desertification is considered to be “High.” The subrounded sand samples are identified at Bollanaguddam Village of Bommanahal, Meenahalli, and Kalekurthi villages of Kanekal Mandal, and hence, the migration of sand and desertification is considered to be “Moderate.” The angular to subangular sand particles are identified in the Sreerangapuram and Naringagundlapalle villages of Beluguppa Mandal, and hence, the rate of migration and desertification is “Low.” The subangular sand grains are identified in the Narasapuram Village of Beluguppa; hence, the rate of migration and desertification is “Very low.” Table 4.2 shows the village and Mandal-wise list of micromorphological features and sand migration and desertification rate in the study area.

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4 Surface Micromorphology of Aeolian Sand Grains

Fig. 4.5 High-resolution SEM panoramic image of sand samples with 20, 50, 5 µm. a: Irregular depressions on the sand grain. b: Smooth surface of a sand grain. c: Mechanical disintegrated surface on sand grain. d: Dissolute surfaces with irregular pit shapes on sand grains

4.7.2 Elemental Analysis for Sand Grains (EDAX) The system software used to analyze the energy spectrum and identify the amount of the individual elements present in the sample is called EDS or energy dispersive X-ray analysis (EDAX). The chemical makeup of the minerals found in the sand grains is determined in the current investigation using EDAX. An illustration of a typical EDAX is an X-ray count versus energy (in keV) plot. The various elements in the sample are represented as energy peaks in the picture. Typically thin and easily dissolved, however, the majority of the components produce several peaks (Badapalli et al. 2021; Kumar et al. 2019). Table 4.3 shows the resultant elemental analysis of sand grains through EDAX. The sand grains have minerals like quartz (SiO2 ), feldspar ((K–Na) AlSi3 O8 ), and tourmalines (Al6 B3 Fe3 H10 NaO31 Si6 ). Oxygen (O) in the high concentrations, next to carbon (C), followed by aluminum (Al), and silica (Si). Remaining all the clays, Fe–Mn oxides, and organic materials are washed out in the analytical procedure, and hence, they are omitted present in the EDAX analysis.

References Table 4.3 EDAX analysis of sand grains

85

Element

Weight%

Atomic%

C

28.45

42.75

Net Int 56.81

O

38.69

43.63

22.46

Al

15.09

2.59

4.41

Si

17.77

11.03

16.32

4.8 Conclusion Inclusive, SEM and EDAX studies can play a crucial role in identifying and mitigating the visual disasters caused by aeolian desertification. These techniques provide powerful tools for understanding the processes of soil erosion and degradation and can help inform management strategies aimed at preserving and protecting our natural resources. The analyzed surface micromorphological features based on SEM studies, we find that the sand samples from Govindawada and D-Honnuru villages of Bommanahal Mandal, and Thumbiganuru, Malyam villages of Kanekal Mandal, showing wellrounded morphology of sand grains facing a very high rate of sand migration causes to desertification. Kalludevanahalli Village of Bommanahal Mandal, and Garudachedu Village of Kanekal Mandal, showing the rounded morphology of sand grains facing a high rate of sand migration. Bollanaguddam Village of Bommanahal Mandal, and Bidurukuntham, Meenahalli, and Kalekurthi villages of Kanekal Mandal shows subrounded morphology of sand grains facing a moderate rate of sand migration. Sreerangapuram and Narinjagundlapalle villages of Beluguppa Mandal show angular to subangular morphology of sand grains facing a low rate of sand migration. Narasapuram Village of Beluguppa Mandal, showing subangular morphology of sand grains facing a very low rate of sand migration in the study area. The sand grains have the minerals like quartz (SiO2 ), feldspar ((K–Na) AlSi3 O8 ), and tourmalines (Al6 B3 Fe3 H10 NaO31 Si6 ). Oxygen (O) in the high concentrations, next to carbon (C), followed by aluminum (Al) and silica (Si). Remaining all the clays, Fe–Mn oxides, and organic materials are washed out in the analytical procedure, and hence, they are omitted in the EDAX analysis.

References Ahumada-Sempoal MA, Castro-García S, Klysubun W, Batten D, Lamé-López MA (2019) Scanning electron microscopy for microplastics analysis: a review and recommendations for quality control. J Environ Manage 248:109262 Badapalli PK, Kottala RB, Rajasekhar M, Ramachandra M, Krupavathi C (2021) Modeling of comparative studies on surface micro morphology of Aeolian, River, Lake, and Beach sand samples using SEM and EDS/EDAX. Mater Today: Proc. https://doi.org/10.1016/j.matpr.2021. 04.049

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Barabasz-Krasny B, Bieganowski A, Wachowski L (2018) Application of scanning electron microscopy and energy-dispersive X-ray spectroscopy in environmental research. Microsc Res Tech 81(4):390–403 Barden C, Smith M (2016) Particle size analysis by SEM: concepts and techniques for earth scientists. Mineral Mag 80(7):1251–1264 Brown P, Leventhal JS (2015) Scanning electron microscopy in the earth sciences. Cambridge University Press Carter MR, Gregorich EG (2010) Soil sampling and methods of analysis. CRC Press Chen Y, Li C, Cao H, Wang Y (2017) Application of scanning electron microscopy in soil and sediment analysis: a review. Environ Monit Assess 189(5):233 Gama AC, Gama MM (2018) Scanning electron microscopy applied to soil analysis: an overview. J Soils Sediments 18(6):1981–1996 Ghadiri M, Sander GC (2017) Characterisation of sand particles under cyclic loading using scanning electron microscopy and image analysis. Geotechnique Letters 7(3):230–235 Goldstein J, Newbury DE, Echlin P, Joy DC, Fiori C, Lifshin E (2018) Scanning electron microscopy and x-ray microanalysis. Springer Guevara M, Lozano-García B, Torrescano G, Borja-Aburto V (2019) Application of scanning electron microscopy for the analysis of soil mineralogy: a review. Geoderma 333:117–130 Hunt ML (2017) Practical scanning electron microscopy: electron and ion microprobe analysis. CRC Press Janssen M, Oomen AG, Dossi C, Bos PM (2016) Toward a harmonized strategy for microplastic analysis in environmental samples: state of the art and perspectives. Anal Chem 88(2):942–953 Klug HP, Alexander LE (2013) X-ray diffraction procedures for polycrystalline and amorphous materials. John Wiley & Sons Kumar BP, Babu KR, Rajasekhar M, Ramachandra M (2019) Exoscopy of sand grains of the desert prone villages of Anantapur district, Andhra Pradesh, Using SEM-EDS/EDX analysis. Nat Environ Pollut Technol 2019(4):655–663 Li C, Wu J (2018) Soil particle size analysis using scanning electron microscopy and image processing. CATENA 161:244–251 MacKenzie RC, Zenger DH (2019) Electron microprobe analysis and scanning electron microscopy in geology. Cambridge University Press Peth S, Horn R (2016) Scanning electron microscopy for soil structure analysis: review and outlook. J Plant Nutr Soil Sci 179(5):565–575 Rey F, Vasconcelos C (2017) Scanning electron microscopy and X-ray analysis, 3rd Ed. CRC Press Thompson M, Shimizu K (2018) SEM and EDX analysis of microplastics in environmental samples. Microscopy Today 26(6):20–25 Zhan H, Wang S, Zhang Z, Zhou Q (2017) Quantitative analysis of mineral components in soils using scanning electron microscopy equipped with energy dispersive X-ray spectroscopy. Environ Earth Sci 76(10):356 Zhang H, Lin H, Wu X, Li J, Zhou Q (2018) Investigation on the composition and morphology of weathered sands using scanning electron microscopy and image analysis. CATENA 167:38–46

Chapter 5

Source of Sand for Aeolian Sand Migration

Abstract Aeolian sand migration is a complex natural phenomenon that affects the ecological environment and human activities in semi-arid regions worldwide. The availability of sand for aeolian sand migration is determined by multiple factors, including geology, climate, topography, vegetation, and human activities. These factors can affect the size, shape, and mineral composition of sand particles, which can influence their susceptibility to wind erosion and transport. Understanding the sources of sand for aeolian sand migration is essential for developing effective strategies for preventing or mitigating the negative impacts of aeolian sand migration. These strategies can include land management practices, such as soil conservation and vegetation restoration, as well as engineering interventions, such as sand barriers and windbreaks. By understanding the sources of sand for aeolian sand migration, we can work to protect the ecological environment and human activities in semi-arid regions and ensure their sustainable development. Keywords Topography · Vegetation · Impacts · Windbreaks · Ecology

5.1 Introduction Semi-arid regions cover more than one-third of the Earth’s surface and are characterized by limited rainfall and high evaporation rates. These regions are often dominated by aeolian sand migration, a natural process by which sand is eroded and transported by wind, forming dunes, sand sheets, and other landforms (Francis 1905). Aeolian sand migration has significant impacts on the ecological environment and human activities in semi-arid regions, including desertification, soil degradation, and damage to infrastructure (Han 2007; Pye and Tsoar 2008; Glennie 2010; Goudie 2013; D’Odorico et al. 2013). Understanding the sources of sand for aeolian sand migration is critical for developing effective strategies for preventing or mitigating the negative impacts of this In this chapter, we will discuss the source of sand for the aeolian sand migration that causes land degradation and desertification in the study area. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 P. K. Badapalli et al., Aeolian Desertification, Advances in Geographical and Environmental Sciences, https://doi.org/10.1007/978-981-99-6729-2_5

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natural phenomenon. The availability of sand for aeolian sand migration is determined by a complex interplay of factors, including geology, climate, topography, vegetation, and human activities. These factors can affect the size, shape, and mineral composition of sand particles, which can influence their susceptibility to wind erosion and transport (Sivakumar 2005; Hugenholtz et al. 2012; Keijsers et al. 2015). This chapter will examine the various factors that determine the sources of sand for aeolian sand migration in semi-arid regions. We will explore the geologic processes that generate sand particles, the climate factors that influence sand availability, the topographic features that affect the distribution of sand, the vegetation cover that stabilizes or exposes sand particles, and the human activities that alter the availability of sand. By understanding these factors, we can gain insights into the sources of sand for aeolian sand migration and develop strategies for sustainable land management and infrastructure development in semi-arid regions (Shepherd et al. 2016; Lancaster 2023).

5.2 Source of Sand for Aeolian Sand Migration in Semi-arid Regions Aeolian sand migration is a significant natural phenomenon that affects the ecological environment and human activities in semi-arid regions worldwide. Aeolian sand migration refers to the process of sand particles being moved by wind, which can cause desertification, soil erosion, and other environmental issues. The source of sand for aeolian sand migration in semi-arid regions is a complex topic that involves multiple factors, including geology, climate, topography, vegetation, and human activities. This article will discuss the various sources of sand for aeolian sand migration in semi-arid regions, focusing on the factors that influence sand supply and how they contribute to sand migration.

5.2.1 Geological Factors Geology is one of the primary factors that determine the availability of sand for aeolian sand migration in semi-arid regions. The parent material of the soil, the rock type, and the geological structure of the region all play a significant role in determining the size, shape, and mineral composition of the sand particles. Different rock types weather at different rates, resulting in different types of sand particles. For example, sand particles derived from granite and basalt are typically more angular and coarse-grained than those derived from sandstone and limestone, which are typically more rounded and fine-grained (McCauley et al. 1984; Mountney et al. 1999). The geological structure of the region also plays a role in determining the availability of sand for aeolian sand migration. Faults, joints, and other structural features

5.2 Source of Sand for Aeolian Sand Migration in Semi-arid Regions

89

can provide pathways for sand to move from the subsurface to the surface, where it can be picked up by the wind. For example, in the Negev Desert in Israel, sand dunes are formed in areas where sandstone formations have been faulted and tilted, creating exposed sand layers that are easily eroded by the wind.

5.2.2 Climate Factors Climate is another important factor that affects the availability of sand for aeolian sand migration in semi-arid regions. Climate influences sand availability through its effects on erosion rates, weathering, and the amount and frequency of rainfall. Regions with high erosion rates, such as those with strong winds, steep slopes, and sparse vegetation, tend to have a high supply of sand particles. Regions with low erosion rates, such as those with gentle slopes, abundant vegetation, and low wind speeds, tend to have a low supply of sand particles (Kocurek and Nielson 1986; Boulghobra 2016). Climate also affects the mineral composition of sand particles, which can affect their susceptibility to aeolian sand migration. In arid and semi-arid regions, where rainfall is low and evaporation is high, the concentration of soluble minerals in the soil and groundwater can be high. When these minerals are weathered and transported to the surface by water or wind, they can form a crust on the soil surface that can be difficult for the wind to erode (Maroulis et al. 2007). However, if the crust is disturbed, for example by grazing animals or human activity, the underlying sand particles can be exposed and become more susceptible to wind erosion.

5.2.3 Topography Factors Topography is another factor that influences the availability of sand for aeolian sand migration in semi-arid regions. The shape, slope, and orientation of the land surface can affect the strength and direction of the wind, which can influence the transport and deposition of sand particles. Regions with a steep slope tend to have a high supply of sand particles because the wind can easily pick up and transport the particles. Regions with a gentle slope tend to have a low supply of sand particles because the wind does not have enough force to transport the particles (Mason et al. 1999). The orientation of the land surface relative to the direction of the prevailing wind can also affect the availability of sand for aeolian sand migration. In regions where the prevailing wind blows parallel to the slope, the sand particles tend to accumulate on the leeward side of the slope, forming sand dunes. In regions where the prevailing wind blows perpendicular to the slope, the sand particles tend to accumulate in depressions, such as playa lakes or alluvial fans.

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5.2.4 Vegetation Factors Vegetation is a crucial factor that affects the availability of sand for aeolian sand migration in semi-arid regions. Vegetation can influence sand availability by stabilizing the soil surface, reducing erosion rates, and modifying the microclimate. Vegetation also affects the mineral composition of sand particles and the size distribution of soil particles (Buckley 1987). In areas with abundant vegetation cover, the soil surface is stabilized by roots, litter, and other organic matter. The vegetation cover can reduce wind speeds and increase surface roughness, which can reduce the amount of sand that is available for transport. The vegetation can also reduce erosion rates by intercepting rainfall and reducing runoff, which can reduce the amount of sediment that is available for transport (Kocurek and Nielson 1986). The vegetation cover can also modify the microclimate, which can affect the mineral composition of sand particles. Vegetation can increase the amount of organic matter in the soil, which can increase the concentration of nutrients and minerals (Tsoar 2001; Tao 2014). Vegetation can also increase the amount of shade and reduce the amount of direct sunlight, which can reduce the temperature and evaporation rates. These factors can influence the weathering rates of rocks and minerals, which can affect the size, shape, and mineral composition of sand particles.

5.2.5 Human Factors Human activities can also have a significant impact on the availability of sand for aeolian sand migration in semi-arid regions. Human activities can affect sand availability by altering vegetation cover, modifying the soil surface, and increasing erosion rates. Human activities can also affect the size, shape, and mineral composition of sand particles through mining and other extractive activities. In many semi-arid regions, human activities, such as overgrazing, agriculture, and urbanization, have led to a reduction in vegetation cover and an increase in soil erosion rates. When the vegetation cover is reduced, the soil surface becomes more vulnerable to erosion by wind and water. This can increase the amount of sand that is available for transport and can lead to the formation of sand dunes and other aeolian landforms (Kasse, and Aalbersberg 2019; Jin et al. 2022). Human activities can also modify the size, shape, and mineral composition of sand particles through mining and other extractive activities. Mining activities, such as sand mining and gravel extraction, can remove sand and other sediment from the environment, altering the availability of sand for aeolian sand migration. These activities can also create new sources of sand by exposing new layers of sand or by generating waste materials that can be transported by wind.

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5.3 Sand Migration in the Study Area Hagari River is a major river that flows through the semi-arid Anantapur District in the state of Andhra Pradesh, India. The river is an important source of water for agriculture and livestock, providing livelihoods for thousands of people in the region. However, the river is also facing a serious problem of sand migration, which is causing significant damage to the local ecosystem and human activities. Sand migration in the Hagari River has been observed for many years, and it is believed to be caused by a combination of natural and human factors. The river basin is located in a semi-arid region, where there is limited vegetation cover and high evaporation rates, leading to the exposure of sand particles. The river flows through a relatively flat landscape, which allows for the accumulation and transport of sand by wind and water. Human activities in the region, such as sand mining, agriculture, and infrastructure development, have also contributed to the problem of sand migration. Sand mining in the river basin has led to the removal of sand from the river bed and banks, altering the natural balance of sediment transport. Agriculture and infrastructure development have also led to the clearance of vegetation cover, which has increased the vulnerability of the river banks to erosion and sand migration. The problem of sand migration in the Hagari River has had significant impacts on the local ecosystem and human activities. The sand deposits have reduced the capacity of the river to carry water, leading to frequent flooding and damage to agricultural lands and infrastructure. The sand deposits have also altered the hydrological regime of the river, affecting the quality and quantity of water available for irrigation and drinking. To address the problem of sand migration in the Hagari River, various interventions have been proposed and implemented. These interventions include sand dredging, construction of sand barriers and check dams, and restoration of vegetation cover along the river banks. However, the effectiveness of these interventions is limited by the complex and dynamic nature of sand migration, which requires a comprehensive understanding of the sources and drivers of sand movement.

5.4 Source of Sand in the Study Area The deposition of windblown riverine sands is believed to have occurred during a significant flood event that took place approximately 1 to 2 centuries ago. Historical records, such as the Anantapur District Gazetteer published in 1970, mention the complete burial of the Sri Ranganatha Temple in Vepalaparthi under windblown sands until its excavation and restoration in 1930. This suggests that the extraordinary flood event occurred sometime before 1930. The Gazetteer also reports damages caused by major floods in 1804, 1817, 1851, and 1874 but does not specifically mention

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Fig. 5.1 Satellite images showing prominent locations (arrows) of sand exposures (light-colored) on the right bank of River Hagari in March 1990 and April 2020

widespread sand deposition by a large flood before 1930 (Sivasankaranarayana 1970; Abhishankar 1972; Francis 1904; Kale et al. 2020; Kumar et al. 2020). The Madras District Gazetteers, specifically the volume on Bellary district published in 1904, includes information from the original Manual of Bellary written in 1872. It describes a “Great Storm of 5th May 1851” that affected Bellary and Anantapur, resulting in the destruction of channels, extensive sand deposition, and the loss of lives and properties in the town of Guliam located on the right bank of the Hagari River (Fig. 5.1). Based on these historical accounts, several inferences can be made. Firstly, the 1851 flood was most likely a severe flash flood, as it occurred in early May outside of the monsoon months. Secondly, the flashy nature of the flood suggests that large quantities of sand were transported and deposited during this event. Lastly, the concentration of floodwaters on the right bank of the Hagari River, despite its generally low sinuosity, indicates that the elevation of the right bank was relatively lower than the left bank. Considering that no comparable flood occurred on the Hagari River until the early twentieth century, it is reasonable to conclude that the majority of the windblown sands were likely first deposited by the Hagari on the right bank during the extreme flash flood of May 1851, which took place approximately 170 years ago.

5.5 Conclusion In conclusion, the problem of sand migration in the Hagari River is a significant challenge that requires urgent attention from policymakers, researchers, and local communities. Addressing this problem will require a multidisciplinary approach that considers the complex interplay of natural and human factors that contribute to

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sand migration. By developing effective strategies for managing sand migration, we can ensure the sustainable development of the region and safeguard the livelihoods of local communities.

References Abhishankar K (1972) Bellary District Gazetteer Boulghobra N (2016) Climatic data and satellite imagery for assessing the aeolian sand deposit and Barchan migration, as a major risk sources in the region of In-Salah (Central Algerian Sahara). Arab J Geosci 9:1–15 Buckley R (1987) The effect of sparse vegetation on the transport of dune sand by wind. Nature 325(6103):426–428 D’Odorico P, Bhattachan A, Davis KF, Ravi S, Runyan CW (2013) Global desertification: drivers and feedbacks. Adv Water Resour 51:326–344 Francis W (1904) Madras District Gazetteers: Bellary. Superintendent, Government Press Francis W (1905) Anantapur. Addison/Government Press Glennie KW (2010) Desert sedimentary environments. Elsevier Goudie AS (2013) Arid and semi-arid geomorphology. Cambridge University Press Han FX (2007) Biogeochemistry of trace elements in arid environments, vol 13. Springer Science & Business Media Hugenholtz CH, Levin N, Barchyn TE, Baddock MC (2012) Remote sensing and spatial analysis of aeolian sand dunes: a review and outlook. Earth Sci Rev 111(3–4):319–334 Jin J, Ling Z, Li Z, Zuo X, Fan X, Huang Y, Qiu J (2022) Spatiotemporal distribution of sea-island prehistoric dune sites, Holocene sea levels, and aeolian sand activities in Fujian Province, China. J Geograph Sci 32(6):1157–1176 Kale VS, Narayana AC, Jaiswal MK (2020) Wind-blown, flash flood-deposited sands of Hagari River, Anantapur district, Andhra Pradesh, India. Curr Sci 119(3):556 Kasse C, Aalbersberg G (2019) A complete Late Weichselian and Holocene record of aeolian coversands, drift sands and soils forced by climate change and human impact, Ossendrecht, the Netherlands. Neth J Geosci 98:e4 Keijsers JG, Giardino A, Poortinga A, Mulder JP, Riksen MJ, Santinelli G (2015) Adaptation strategies to maintain dunes as flexible coastal flood defense in The Netherlands. Mitig Adapt Strat Glob Change 20:913–928 Kocurek G, Nielson J (1986) Conditions favourable for the formation of warm-climate aeolian sand sheets. Sedimentology 33(6):795–816 Kumar BP, Babu KR, Ramachandra M, Krupavathi C, Swamy BN, Sreenivasulu Y, Rajasekhar M (2020) Data on identification of desertified regions in Anantapur district, Southern India by NDVI approach using remote sensing and GIS. Data Brief 30:105560. https://doi.org/10.1016/ j.dib.2020.105560 Lancaster N (2023) Geomorphology of desert dunes. Cambridge University Press Maroulis JC, Nanson GC, Price DM, Pietsch T (2007) Aeolian–fluvial interaction and climate change: source-bordering dune development over the past ∼100 ka on Cooper Creek, central Australia. Quatern Sci Rev 26(3–4):386–404 Mason JA, Nater EA, Zanner CW, Bell JC (1999) A new model of topographic effects on the distribution of loess. Geomorphology 28(3–4):223–236 McCauley JF, Breed CS, Helm PJ, Billingsley GH, MacKinnon DJ, Grolier MJ, McCauley CK (1984) Remote monitoring of processes that shape desert surfaces: the Desert Winds project (No. USGS-BULL-1634). Geological Survey, Reston, VA (USA)

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Mountney N, Howell J, Flint S, Jerram D (1999) Climate, sediment supply and tectonics as controls on the deposition and preservation of the aeolian-fluvial Etjo sandstone formation, Namibia. J Geol Soc 156(4):771–777 Pye K, Tsoar H (2008) Aeolian sand and sand dunes. Springer Science & Business Media Shepherd G, Terradellas E, Baklanov A, Kang U, Sprigg W, Nickovic S, Joowan C (2016) Global assessment of sand and dust storms Sivakumar MV (2005) Impacts of sand storms/dust storms on agriculture. In: Natural disasters and extreme events in agriculture: impacts and mitigation, pp 159–177 Sivasankaranarayana BH (1970) Anantapur. Andhra Pradesh District Gazetteers, Director of Printing and Stationery, The Government Secretariat PRBBS, Hyderabad, 1970 Tao W (2014) Aeolian desertification and its control in Northern China. Int Soil Water Conserv Res 2(4):34–41 Tsoar H (2001) Types of aeolian sand dunes and their formation. In: Geomorphological fluid mechanics. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 403–429

Chapter 6

Impact of Desertification in Semi-arid Regions

Abstract Semi-arid regions’ agriculture is severely impacted by desertification, which causes a loss of flora, soil fertility, and water supplies. Soil deterioration, water shortage, and biodiversity loss are the three ways that desertification affects agriculture. Degradation of the soil lowers its capacity to store nutrients and water, which lowers agricultural output. Crop failure results from the drying up of rivers and lakes, loss of groundwater reserves, and water shortages. Pollination, pest management, and soil fertility are all impacted by a loss of biodiversity. A multifaceted strategy is needed to prevent and reduce the effects of desertification on agriculture, including the adoption of sustainable land use practices, water conservation measures, and biodiversity preservation. Reducing the number of animals, introducing rotational grazing systems, and utilizing conservation agriculture and agroforestry are all examples of sustainable land use practices. The creation of water harvesting structures and the deployment of effective irrigation methods are examples of water-saving initiatives. The preservation of plant and animal species that are important for pollination and soil fertility is a key component of biodiversity conservation. Keywords Soil · Crop · Biodiversity · Land use · Water conservation

6.1 Introduction A global issue, desertification affects arid, semi-arid, and dry subhumid areas. It is a form of land degradation that causes the loss of flora, animals, and fertile soil. Combinations of manmade and natural variables, such as climate change, deforestation, overgrazing, and unsustainable land use practices, are what lead to desertification (Le Houérou 1996; Ayoub 1998; Sivakumar and Stefanski 2007; Abdi et al. 2013; Costa et al. 2016). This essay will examine how desertification affects semi-arid areas, which are especially susceptible to land degradation.

In this chapter, we will discuss the impacts of desertification on agricultural land and society. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 P. K. Badapalli et al., Aeolian Desertification, Advances in Geographical and Environmental Sciences, https://doi.org/10.1007/978-981-99-6729-2_6

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6.2 Impact of Desertification on Soil Any ecosystem’s base is its soil, and desertification significantly affects the quality of that soil. Loss of plant cover exposes the soil to sunlight, wind, and rain, which causes erosion and topsoil loss. Topsoil depletion affects the soil’s capacity to store nutrients and water, both of which are necessary for plant development. Salt builds up in the soil as a result of desertification, rendering it unusable for farming. This can therefore result in the eviction of rural populations whose economies are based on agriculture (Stringer et al. 2012).

6.3 Impact of Desertification on Biodiversity Biodiversity, or the variety of plant and animal species that reside in an environment, is significantly impacted by desertification. A decrease in biodiversity results from the loss of vegetative cover, which also destroys the habitat of many species. The food chain is subsequently impacted by this when some species become extinct or relocate. Microorganisms in the soil, which are crucial to the nutrient cycle in the ecosystem, are also impacted by desertification (Kosmas et al. 2003; Gupta et al. 2011).

6.4 Impact of Desertification on Water Resources Water resources, which are already in short supply in arid and semi-arid areas, are significantly impacted by desertification. The loss of vegetation reduces the soil’s capacity to hold onto water, which causes runoff and soil erosion. In turn, this causes groundwater reserves to be exhausted and rivers and lakes to dry up. Water quality is also impacted by desertification because salt and other minerals that build up in the soil can taint water supplies (Osman 2014; Günal et al. 2015).

6.5 Impact of Desertification on Agriculture For many rural populations in semi-arid areas, agriculture is a vital source of income. Agriculture is significantly impacted by desertification because it diminishes soil productivity and renders the land unfit for growing crops. As a result, farmers are compelled to give up farming or utilize unsustainable land use techniques like monoculture or overgrazing. This furthers the issue of desertification by causing the soil fertility to decrease (Onate and Peco 2005; Samy 2010; Al-Obaidi et al. 2022).

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6.6 Impact of Desertification on Health Human health is significantly impacted by desertification as well. Rural populations may become food insecure and destitute as a result of being compelled to give up their land. Malnutrition, malaria, and cholera cases therefore rise as a result of this. Communities may be uprooted as a result of desertification, which can also cause social upheaval, economic disruption, and an increase in resource-related warfare (Yusa et al. 2015; Olagunju, 2015).

6.7 Impact of Desertification in Semi-arid Regions Agriculture For many rural populations in semi-arid areas, agriculture is a vital source of income. Agriculture is significantly impacted by desertification because it diminishes soil productivity and renders the land unfit for growing crops. As a result, farmers are compelled to give up farming or utilize unsustainable land use techniques like monoculture or overgrazing. This furthers the issue of desertification by causing the soil fertility to decrease.

6.8 Impact of Desertification on Agriculture Desertification has a significant impact on agriculture in semi-arid regions, as it leads to the loss of soil fertility, vegetation, and water resources. The impact of desertification on agriculture can be divided into three categories: soil degradation, water scarcity, and loss of biodiversity.

6.8.1 Soil Degradation In semi-arid regions impacted by desertification, soil deterioration is a serious issue. Loss of plant cover exposes the soil to sunlight, wind, and rain, which causes erosion and topsoil loss. Topsoil depletion affects the soil’s capacity to store nutrients and water, both of which are necessary for plant development. In turn, this lowers the soil’s productivity and renders it unfit for growing crops. The loss of soil organic matter, which is essential for soil fertility, is a result of soil erosion as well. In addition to giving plants nutrition, soil organic matter enhances the physical characteristics of the soil, such as its ability to store water and its structure. As erosion removes organic matter from the soil, the soil’s fertility declines, resulting in a fall in agricultural production.

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6.8.2 Water Scarcity In semi-arid areas impacted by desertification, water scarcity is a serious issue. The loss of vegetation reduces the soil’s capacity to hold onto water, which causes runoff and soil erosion. In turn, this causes groundwater reserves to be exhausted and rivers and lakes to dry up. Crop failure brought on by a lack of water may have devastating effects on rural populations’ ability to support themselves.

6.8.3 Loss of Biodiversity Desertification also leads to the loss of biodiversity, which refers to the variety of plant and animal species that live in an ecosystem. As vegetation cover is lost, the habitat of many species is destroyed, leading to a decline in biodiversity. This, in turn, affects the food chain, as some species become extinct or migrate to other areas. Loss of biodiversity can have severe consequences for agriculture, as it affects pollination, pest control, and soil fertility (Mall et al. 2006). Desertification’s visual danger in semi-arid areas is fairly dramatic. The terrain seems desolate with little to no vegetation growing as it degrades and loses its plant cover. Plant growth becomes challenging when the Earth dries up and cracks. In some places, wind erosion can result in the formation of sand dunes, which can envelop entire fields and prevent the growth of crops. As plant roots assist to bind soil and prevent erosion, the loss of vegetation cover also results in a deterioration in soil quality. The end effect is an unproductive, uninhabitable area with little to no animals.

6.8.4 Visual Hazard of Desertification in Agricultural Lands One of the most visible impacts of desertification on agriculture is the loss of crops. In semi-arid regions, crops are already under stress due to limited rainfall and high temperatures. When the soil becomes degraded, it becomes even more difficult for crops to grow, leading to lower yields and crop failure. As a result, farmers are forced to abandon their fields or move to other areas in search of more productive land. Another visible hazard of desertification is the depletion of water resources. As soil quality declines, it becomes more difficult for the soil to hold water, leading to increased runoff and reduced groundwater recharge. In some cases, the loss of vegetation cover can cause rivers and streams to dry up, further reducing water availability for agriculture. Finally, another obvious threat of desertification is the decline of biodiversity. The variety of plant and animal species decreases as vegetative cover is removed. This may significantly affect soil fertility, insect management, and pollination. Farming

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becomes less productive without these crucial ecological services, which makes it extremely harder for farmers to make a livelihood in semi-arid areas. A barren, unproductive environment with little to no plant cover, animals, or water supplies is the immediate visible danger of desertification in semi-arid settings. As a result, agricultural production is significantly impacted, resulting in poorer yields, crop failure, and the depletion of water supplies.

6.9 Conclusion Ultimately, it has to be noted that the effects of desertification in semi-arid areas provide a serious environmental and socioeconomic problem that needs immediate attention and decisive action. Ecosystems get disrupted by desertification, which also causes soil degradation, biodiversity loss, and a decrease in water availability. This in turn has an impact on communities that depend on the land for their livelihoods, agricultural output, and food security. A multifaceted strategy is needed to reduce the negative impacts of desertification. In order to rehabilitate and safeguard degraded lands, sustainable land management practices such as afforestation, reforestation, and soil conservation techniques are required. Implementing effective water management techniques, such as rainwater gathering and irrigation techniques, can also increase water availability and lessen communities’ susceptibility to droughts. Additionally, it is crucial to raise awareness of desertification and its effects in order to persuade local communities, governments, and international organizations to work together to tackle this problem. A framework for coordinated action and resource allocation can be provided through strengthening laws, regulations, and international agreements linked to climate change, environmental protection, and land management.

References Abdi OA, Glover EK, Luukkanen O (2013) Causes and impacts of land degradation and desertification: case study of the Sudan. Int J Agric Fores 3(2):40–51 Al-Obaidi JR, Yahya Allawi M, Salim Al-Taie B, Alobaidi KH, Al-Khayri JM, Abdullah S, AhmadKamil EI (2022) The environmental, economic, and social development impact of desertification in Iraq: a review on desertification control measures and mitigation strategies. Environ Monit Assess 194(6):440 Ayoub AT (1998) Extent, severity and causative factors of land degradation in the Sudan. J Arid Environ 38(3):397–409 Costa ARS, de Lima Ferreira G, de Souza EB, Neto FCR (2016) Desertification in semi-arid northeast of Brazil| Desertificação no nordeste semi-árido do Brasil. Revista Geama:427–445 Günal H, Korucu T, Birkas M, Özgöz E, Halbac-Cotoara-Zamfir R (2015) Threats to sustainability of soil functions in Central and Southeast Europe. Sustainability 7(2):2161–2188

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Gupta AK, Tyagi P, Sehgal VK (2011) Drought disaster challenges and mitigation in India: strategic appraisal. Curr Sci:1795–1806 Kosmas C, Tsara M, Moustakas N, Karavitis C (2003) Identification of indicators for desertification. Ann Arid Zone 42:393–416 Le Houérou HN (1996) Climate change, drought and desertification. J Arid Environ 34(2):133–185 Mall RK, Gupta A, Singh R, Singh RS, Rathore LS (2006) Water resources and climate change: an Indian perspective. Curr Sci:1610–1626 Olagunju TE (2015) Drought, desertification and the Nigerian environment: a review. J Ecol Nat Environ 7(7):196–209 Onate JJ, Peco B (2005) Policy impact on desertification: stakeholders’ perceptions in southeast Spain. Land Use Policy 22(2):103–114 Osman KT (2014) Soil degradation, conservation and remediation, vol 820. Springer Netherlands, Dordrecht Samy AR (2010) A desertification impact on Siwa Oasis: present and future challenges. Res J Agric Biol Sci 6(6):791–805 Sivakumar MV, Stefanski R (2007) Climate and land degradation—an overview. Springer, Berlin Heidelberg, pp 105–135 Stringer LC, Akhtar Schuster M, Marques MJ, Amiraslani F, Quatrini S, Abraham EM (2012) Combating land degradation and desertification and enhancing food security: towards integrated solutions Yusa A, Berry P, Cheng JJ, Ogden N, Bonsal B, Stewart R, Waldick R (2015) Climate change, drought and human health in Canada. Int J Environ Res Public Health 12(7):8359–8412

Chapter 7

Long-Term Temporal Analysis of Desertification

Abstract This study uses remote sensing techniques to map land use and cover in desertified areas as well as analyze visual hazard catastrophes caused by desertification. Ground cover classes such as barren ground, degraded vegetation, agricultural regions, water bodies, and urban areas are classified using multispectral and hyperspectral satellite images, as well as supervised classification. The generated land use and cover map is examined in order to identify regions vulnerable to visual hazards such as sand invasion and land degradation. The findings contribute to a better knowledge of the geographical patterns of desertification-induced visual hazards, hence promoting effective mitigation measures and long-term land management practices. Keywords Temporal · Water bodies · Hyperspectral · Urban areas · Visual hazard

7.1 Introduction Desertification, or the conversion of previously fruitful land to dry or desert-like conditions, is a global environmental concern with serious socioeconomic and ecological repercussions. It causes substantial visual hazards, such as sand invasion, loss of plant cover, and land degradation, resulting in habitat destruction, decreased agricultural output, and increased vulnerability of residents in impacted areas. Accurate mapping of land use and cover in desertified areas is critical for understanding the extent and trends of desertification and establishing effective mitigation methods for visual hazards (Bai et al. 2008; Chuvieco and Huete 2010; Chen et al. 2015; Bai and Wu 2016). Remote sensing, a strong technology for gathering information about the Earth’s surface from a distance, may be used to map land usage and cover in desertified areas. It permits the collection of spectral, geographical, and temporal data that captures the properties of various desertification-affected land cover types. Remote sensing techniques like multispectral and hyperspectral imaging give a plethora of information regarding plant health, soil moisture, and land surface attributes, which is In this chapter, we will discuss the land use and land cover changes based on the satellite data. We will discuss the supervised classification method for land use and land cover studies. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 P. K. Badapalli et al., Aeolian Desertification, Advances in Geographical and Environmental Sciences, https://doi.org/10.1007/978-981-99-6729-2_7

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crucial for mapping and monitoring desertification-induced visual hazards (Fensholt and Sandholt 2003; Geist and Lambin 2004; He and Wu 2015; Dong et al. 2019; Huang et al. 2019). The aim of this research is to use remote sensing to map land use and cover in desertified areas and to assess the visual hazards associated with desertification. The project attempts to properly categorize land cover classes such as barren land, degraded vegetation, agricultural regions, water bodies, and urban areas using satellite images and supervised classification approaches. To increase categorization accuracy, ancillary data such as topographic information and soil parameters will be included (Tucker 1979). The produced land use and cover map will give useful information on the geographical distribution and extent of various land cover types in desertified areas. It will be used to analyze the severity of visual hazard catastrophes such as sand encroachment and land degradation by identifying sensitive locations and measuring their spatial linkages with different land cover classes. Such data is critical for understanding the effects of desertification and implementing targeted actions to reduce visual hazards and promote sustainable land management practices (Lu et al. 2004; Rietkerk et al. 2004; Reynolds et al. 2007; Pu et al. 2010).

7.2 Land Use The human actions and reasons for which land is used are referred to as land use. It includes all of the numerous ways that land is occupied, developed, and managed. Residential areas, commercial and industrial zones, agricultural fields, leisure places, transportation infrastructure, conservation areas, and other uses are all examples of land use. It entails judgments on the allocation of land for specific purposes as well as the physical layout of various land uses within a given area (Mabbutt 1978); Turner et al. 2007). Effective land use planning and management are essential for long-term development, balanced urban expansion, environmental protection, and resource efficiency (Hill et al. 2008; Albalawi and Kumar 2013; Bestelmeyer et al. 2015).

7.3 Land Cover The physical properties and varieties of plants, soil, water bodies, and artificial surfaces found on the Earth’s surface are referred to as land cover. It represents the observed or identified aspects of the land without regard for their usage or human activity. Forests, grasslands, marshes, croplands, urban areas, barren ground, water bodies such as lakes and rivers, and numerous natural and manmade surfaces are all examples of land cover (Huang and Siegert 2006; Lamchin et al. 2016; Tomasella et al. 2018).

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Land cover categorization is commonly based on remote sensing data, such as satellite photography, which allows for the identification and mapping of various land cover categories at regional, national, and global sizes. Land cover change monitoring and analysis offer essential information for environmental evaluations, land management, biodiversity protection, climate research, and urban planning (Kumar et al. 2019; Kumar and Sharma 2020; Moumane et al. 2022; Anusha et al. 2023). Data and analysis on land cover help to understand ecosystem dynamics, land degradation, habitat loss, and other environmental challenges.

7.4 Land Use and Land Cover Mapping Land use and land cover mapping involves the process of identifying and categorizing the different types of land use and land cover present in a specific area. It is done through the interpretation of satellite imagery, aerial photographs, and other remote sensing data. The mapping process typically involves several steps.

7.4.1 Data Acquisition Obtain satellite imagery or aerial photographs covering the area of interest. This data serves as the primary source for identifying and classifying land use and land cover features.

7.4.2 Preprocessing Prepare the imagery for analysis by correcting for atmospheric effects, geometric distortions, and radiometric variations.

7.4.3 Image Interpretation Visual interpretation of the imagery is performed to identify and delineate different land cover features such as forests, urban areas, water bodies, and agricultural fields. This step can be conducted manually or with the assistance of automated classification algorithms.

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7.4.4 Classification Assign each image pixel or area to a specific land use or land cover class based on its spectral characteristics, texture, and contextual information. This can be achieved through supervised or unsupervised classification methods.

7.4.5 Validation Assess the accuracy of the classification results by comparing them with ground truth data collected through field surveys or existing land use and land cover maps. Adjustments may be made to improve the accuracy of the mapping.

7.4.6 Mapping and Reporting Generate a map or spatial database that represents the distribution of different land use and land cover classes in the study area. This information can be further analyzed and used for various purposes such as urban planning, environmental management, natural resource monitoring, and policy development. Land use and land cover mapping provides valuable insights into the spatial patterns and dynamics of land resources, enabling informed decision-making and sustainable land management practices.

7.5 Importance of Land Use and Land Cover Land use and land cover mapping have numerous applications and benefits across various fields. Here are some of the key uses:

7.5.1 Urban Planning Land use and land cover maps are crucial for urban planning and development. They help identify suitable areas for residential, commercial, and industrial purposes, as well as for infrastructure development such as roads, parks, and utilities. These maps assist in managing urban growth, optimizing resource allocation, and ensuring efficient land use (Pasham et al. 2022).

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7.5.2 Environmental Management Land use and land cover mapping play a vital role in environmental management and conservation. They provide valuable information for assessing habitat fragmentation, biodiversity distribution, and ecosystem health. These maps aid in identifying areas of ecological significance, implementing conservation strategies, and monitoring the impact of human activities on natural habitats.

7.5.3 Agriculture and Forestry Land use and land cover maps support agricultural and forestry management. They assist in crop monitoring, precision farming, and identifying suitable areas for cultivation. Additionally, these maps aid in forest inventory, monitoring deforestation, and planning sustainable forestry practices (Anusha et al. 2023; Kumar et al. 2023).

7.5.4 Natural Resource Management Mapping land use and land cover helps in the effective management of natural resources. It enables the identification of areas suitable for mining, water resource management, and energy development. These maps also aid in assessing land suitability for various activities and implementing sustainable resource management practices.

7.5.5 Disaster Management Land use and land cover mapping are valuable for disaster management and risk assessment. They provide essential information for identifying areas prone to natural hazards such as floods, landslides, and wildfires. This mapping aids in planning emergency response, land use zoning, and reducing vulnerability to disasters.

7.5.6 Climate Change Studies Land use and land cover maps contribute to climate change studies by monitoring changes in vegetation cover, land surface temperature, and carbon storage. They assist in assessing the impact of land use changes on climate patterns, modeling

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future scenarios, and developing mitigation and adaptation strategies (Kumar et al. 2023).

7.5.7 Infrastructure Development Land use and land cover mapping are used in infrastructure planning and development. They help identify suitable areas for transportation networks, utilities, and energy infrastructure. These maps aid in optimizing infrastructure placement, minimizing environmental impacts, and ensuring efficient use of land resources.

7.5.8 Policy Development Land use and land cover maps provide critical information for policy development and decision-making. They assist governments, organizations, and stakeholders in formulating land use policies, zoning regulations, and environmental protection measures. These maps support evidence-based decision-making and help balance economic development with environmental sustainability. Overall, land use and land cover mapping serve as valuable tools for understanding and managing our landscapes, promoting sustainable development, and preserving our natural resources.

7.6 Remote Sensing Approaches for Land Use and Land Cover Mapping in Desertified Regions Remote sensing approaches for land use and land cover mapping in desertified regions can be particularly useful due to the challenges and unique characteristics of such areas. Here are some remote sensing techniques commonly employed for land use and land cover mapping in desertified regions:

7.6.1 Multispectral Imagery Multispectral satellite imagery, such as those captured by sensors like Landsat, Sentinel-2, or MODIS, provides valuable spectral information. Different land cover types in desertified regions exhibit distinctive spectral signatures that can be utilized

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for classification and mapping. Spectral indices like Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) can be used to assess vegetation cover and its health.

7.6.2 Hyperspectral Imaging Hyperspectral sensors capture a larger number of narrow and contiguous spectral bands, allowing for more detailed spectral analysis. This high spectral resolution enables better differentiation between land cover classes in desertified regions. It helps detect subtle variations in vegetation stress, mineral composition, and soil properties associated with desertification processes.

7.6.3 Thermal Infrared (TIR) Imaging TIR sensors capture thermal energy emitted by the Earth’s surface. In desertified regions, TIR imagery can be used to analyze surface temperature patterns, which are indicative of land cover types and can provide insights into heat stress and water availability. TIR data combined with other spectral bands can improve land cover classification accuracy.

7.6.4 Synthetic Aperture Radar (SAR) SAR sensors transmit microwave signals and measure the backscatter reflected from the Earth’s surface. SAR imagery is beneficial in desertified regions due to its ability to penetrate through clouds, haze, and sandstorms. SAR can detect surface roughness, soil moisture content, and vegetation structure, providing valuable information for land use and land cover mapping.

7.6.5 Light Detection and Ranging (LiDAR) LiDAR systems use laser pulses to measure the distance between the sensor and the Earth’s surface, allowing for the generation of highly accurate and detailed elevation models. In desertified regions, LiDAR data can help identify topographic features, terrain changes, and vegetation height, which are essential for land cover classification and mapping.

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7.6.6 Change Detection Techniques Desertification often involves land cover changes over time. Remote sensing techniques, such as image differencing, post-classification comparison, or time-series analysis, can be used to detect and quantify land cover changes in desertified regions. These approaches help understand the dynamics of desertification and assess the effectiveness of land management interventions. Integration of multiple remote sensing datasets, along with field validation and expert knowledge, is crucial for accurate land use and land cover mapping in desertified regions. Classification algorithms like maximum likelihood, support vector machines (SVM), random forests, or neural networks are commonly employed for automated classification and mapping. Additionally, data fusion techniques and spatial modeling can enhance the accuracy and reliability of land cover mapping results in desertified areas.

7.7 Image Classification Techniques 7.7.1 Supervised Classification Technique Supervised classification is a remote sensing technique used to classify and categorize pixels or image segments into different land cover or land use classes. It involves the use of training samples, which are representative examples of each class, to train a classification algorithm. The algorithm then applies the learned classification rules to assign class labels to the remaining pixels in the image (Badapalli et al. 2019; Talukdar et al. 2020; Sertel et al. 2022). Here’s how the supervised classification process typically works: 7.1.1a Training Sample Collection: Representative training samples are collected from the study area. These samples should be accurately labeled, meaning their land cover or land use class is known. Field surveys, existing maps, or expert knowledge can be used to collect the training samples. 7.1.1b Feature Selection: Relevant spectral, textural, or other ancillary data layers (such as vegetation indices or topographic variables) are extracted from the remote sensing data for each training sample. These features should capture the characteristics that differentiate different land cover classes. 7.1.1c Training Stage: The training samples and their associated features are used to train a classification algorithm or model. Common algorithms used for supervised classification include maximum likelihood, support vector machines (SVM), random forests, and decision trees. The algorithm learns the statistical patterns and relationships between the features and the known classes.

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7.1.1d Classification Stage: Once the model is trained, it is applied to the entire image or the desired area of interest. The algorithm analyzes the features of each pixel and assigns it to the most likely land cover class based on the learned classification rules. The result is a classified image where each pixel is assigned a specific land cover class label. 7.1.1e Accuracy Assessment: The accuracy of the classification results is assessed by comparing them with ground truth data. This involves collecting additional reference data from the field or using existing data to evaluate the classification accuracy. Various metrics, such as overall accuracy and kappa coefficient, are calculated to quantify the agreement between the classified image and the reference data. Supervised classification is a widely used technique for land use and land cover mapping as it allows for the efficient and automated analysis of large-scale remote sensing data. It requires a good understanding of the study area and careful selection of training samples to achieve accurate classification results.

7.7.2 Unsupervised Classification Technique Unsupervised classification is a remote sensing technique used to classify and categorize pixels or image segments into different land cover or land use classes without the need for pre-defined training samples. Unlike supervised classification, unsupervised classification relies on the inherent patterns and statistical properties of the data to group similar pixels together (Ramanamurthy and Victorbabu, 2021; Badapalli et al. 2021; Osman et al. 2022). Here’s how the unsupervised classification process typically works: 7.7.2a Initial Image Segmentation: The remote sensing image is initially segmented into regions or pixels based on similarity measures such as spectral similarity, texture, or other characteristics. This segmentation step helps to identify homogeneous image segments that potentially represent distinct land cover classes. 7.7.2b Cluster Analysis: Unsupervised classification uses cluster analysis algorithms, such as k-means clustering or Gaussian mixture models, to group pixels or segments with similar spectral characteristics into clusters. The number of clusters is typically determined by the analyst or based on the statistical properties of the data. 7.7.2c Cluster Assignment: Each pixel or segment in the image is assigned to a cluster based on its similarity to the cluster’s spectral properties. The algorithm iteratively assigns pixels to the most similar cluster until convergence is achieved. 7.7.2d Class Labeling: After the clustering process, the clusters need to be assigned meaningful land cover class labels. This step is performed by analyzing the spectral properties, visual interpretation of the cluster statistics, and comparison with ground

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truth data or existing land cover maps. The analyst interprets the characteristics of each cluster to assign appropriate class labels. Post-Classification Refinement: Unsupervised classification results may require refinement to improve accuracy. This can involve spatial filtering, incorporating ancillary data or contextual information, and applying additional rules or constraints to ensure coherence and consistency in the final classified image. 7.7.2e Accuracy Assessment: The accuracy of the unsupervised classification results is assessed by comparing them with ground truth data or existing land cover maps. Similar to supervised classification, various metrics, such as overall accuracy and kappa coefficient, are calculated to evaluate the agreement between the classified image and the reference data. Unsupervised classification is useful when the land cover classes in the image are unknown or complex, and it allows for the discovery of patterns and groupings in the data. However, since it relies on statistical properties, it may result in classes that do not have direct correspondence to specific land cover types, requiring additional interpretation and refinement steps.

7.8 Sand Migration and Desertification Status Along the Hagari River Using LULC Technique 7.8.1 Satellite Data Used The Landsat program, a collaborative effort between NASA and the US Geological Survey, encompasses a collection of satellite missions dedicated to observing the Earth. These missions capture comprehensive measurements of terrestrial and polar regions, covering the visible, near-infrared, short wave, and thermal infrared spectrums. With their exceptional ground resolution and spectral bands, Landsat satellites are ideally equipped to monitor land use patterns and record alterations caused by various factors such as climate change, urbanization, drought, wildfires, changes in biomass (including carbon assessments), as well as a wide range of other natural and human-induced transformations. The Landsat program’s continuous record, which spans from 1972 to the present, offers crucial data on land change and trends that are otherwise inaccessible. The world’s longest-running, continuous, moderate-resolution land remote sensing data gathering project is called Landsat. The US Department of the Interior relies heavily on Landsat to successfully manage Federal lands. Worldwide, research, business, education, and other uses of Landsat data are common. For the preparation of the desertification status map (DSM), the data was acquired from 1990 to 2020, i.e., thirty years or three decades. In the present study, the Landsat 4–5 TM/MSS, Landsat 7 ETM+, and Landsat 8 OLI/TIRS images on 13th March 1990, 16th March 2000, 19th March 2010, and

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27th April 2020 were selected purposively for identifying, and mapping the land degradation and desertification area, because these satellite images contain different spectral bands with different ranges out of the bands only six bands, namely green band, red band, NIR band, SWIR band, TIR—1 band, and TIR—2 band were used. Landsat 5 Multispectral Scanner (MSS) was acquired on 13th March 1990, from USGS EarthExplorer. Landsat 5 MSS satellite was launched on 1st March 1984, and it has seven spectral bands, with 60 m spatial resolution. The objective of Landsat 5-MSS was to enable worldwide, repeatable daylight capture of high-resolution, multispectral data of the Earth’s surface and to show that remote sensing from space is a feasible and practical approach to effective resource management. The list of the Landsat 4–5 TM bands, wavelengths, and resolutions has been shown in Fig. 7.1. Landsat 7 Enhanced Thematic Mapper Plus (ETM+) was acquired on 16th March 2000, and 19th March 2010, from USGS EarthExplorer. Landsat 7 ETM+ satellite was launched on 15th April 1999, and it has eight spectral bands, with 30 m resolution. In Landsat 7, ETM+ satellite data band 8 (Panchromatic) has 15 m resolution. The list of the Landsat 7 ETM+ bands, wavelengths, and resolutions has been shown in Fig. 7.2. Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) was acquired on 27th April 2020, from EarthExplorer. Landsat 8 OLI/TIRS satellite was launched on 11th February 2013, and it has eleven spectral bands, including panchromatic band (8 bands) with 15 m spatial resolution, Thermal Infrared I (Band 10 TIRS—1), and Thermal Infrared II (Band 11 TIRS—2) with 100 m resolution.

Fig. 7.1 Landsat 4–5 TM/MSS bands, wavelength, and spatial resolution

Fig. 7.2 Landsat 7 ETM+ bands, wavelength, and spatial resolution

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Fig. 7.3 Landsat 8 OLI and TIRS bands, wavelength, and spatial resolution

The list of the Landsat 8OLI/TIRS bands, wavelengths, and resolutions has been shown in Fig. 7.3.

7.8.2 Software’s Used In the present study, ArcGIS 10.8, ERDAS IMAGINE 2014, QGIS, RockWorks, and Google Earth Engine Code editor software are used for calculation and analysis of the satellite imageries and conventional maps.

7.8.3 ArcGIS 10.8 The ArcGIS 10.8 software was used to create and analyze the map. ArcGIS is a comprehensive platform for implementing GIS on computers, servers, the web, and in the field for a single user or many users. ArcGIS is a collection of GIS software tools that may be used to create a full GIS. ArcGIS is a tool that allows anybody to make maps using data and shapefiles. Maps made using the application may be altered in a variety of ways, allowing for the creation of maps that highlight certain data. Along with the Arc toolbar, the ArcGIS includes several features for computing raster and vector data of any images.

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7.8.4 Erdas Imagine 2014 ERDAS IMAGINE 2014 is a specialized software package that operates on rasterbased data, primarily aimed at extracting valuable information from imagery. With a wide array of tools at its disposal, ERDAS IMAGINE empowers users to generate precise base imagery suitable for integration into GIS and ESRI Geodatabases. Offering functionalities such as image orthorectification, mosaicking, reprojection, classification, and interpretation, this software enables thorough analysis of image data and facilitates its representation in diverse formats, ranging from traditional printed maps to advanced 3D models. The ERDAS IMAGINE 2014 software is widely employed for layer stacking and image processing purposes. It supports various techniques such as NDVI, SAVI, TGSI, and supervised classification, empowering users to perform these methods effectively within their study areas.

7.9 Methodology Adopted For the estimation of sand migration along the Hagari River, the satellite data of Landsat 4–5 TM for 1990, Landsat 7 ETM+ for 2000 and 2010, and Landsat 8 OLI/TIRS for 2020 has been procured from the USGS website. Survey of India (SOI) toposheets are procured from the GSI website. A detailed field survey has been carried out for the sand sample collection and field photos collection in the study area. Figure 7.4 depicts the methodology flow chart for the sand migration and desertification estimation along the Hagari River in the study region.

7.10 LULC by Supervised Classification Technique In order to conduct land use and land cover (LULC) analysis, a supervised classification technique utilizing the maximum likelihood algorithm was implemented in ERDAS IMAGINE 2014. The maximum likelihood algorithm is widely regarded as one of the most effective and user-friendly approaches for image classification using remote sensing datasets. This approach relies on pixel-based probability analysis, which involves assessing the likelihood of a pixel belonging to a specific class. The algorithm calculates probabilities based on identical pixels associated with individual features, assuming that the input pixels follow a standard distribution (Sharma and Joshi 2016; Kumar et al. 2019; Bhimala et al. 2020). However, it is important to note that this method can be computationally intensive and relies heavily on the normal distribution assumption within each input range. Moreover, it has a tendency to overclassify when used with relatively small signature editor in the covariance matrix. The spectral analysis approach involves computing

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Fig. 7.4 Methodology flowchart for the sand desertification along the Hagari River

the spectral analysis between the measurement vector of the candidate vector pixel and the mean vector for each signature (Fig. 7.5). The maximum likelihood algorithm, while offering the advantage of the shortest calculation time compared to other image classification approaches, has certain limitations. It tends to classify pixels beyond the intended target and does not consider class variability. In order to address these issues, fieldwork was conducted to make necessary corrections for regions that were accessible or had uncertainties within the ERDAS IMAGINE environment. The accuracy assessment is a crucial final step in the classification process, aiming to quantitatively evaluate the effectiveness of pixel sampling in accurately representing land cover classes (Meer and Mishra 2020). The accuracy assessment focused on selecting pixels from areas that could be identified on Landsat images, Google Earth images, and Google Maps. This selection process plays a significant role in ensuring the reliability of the classification results. In the study area, four types of land use and land cover (LULC) change detection were classified, including: (a) (b) (c) (d)

Sand dunes vegetation fallow land and water body.

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Fig. 7.5 Ground signatures of Landsat imageries

7.11 Land Use and Land Cover (LULC) Changes Along the Hagari River The region exhibits a diverse land cover comprising vegetation, fallow land, water bodies, and dunes. The findings of this study emphasize that land use and land cover (LULC) are pivotal in identifying and assessing the extent of human-induced land use exploitation, which significantly contributes to desertification. These activities have negatively impacted the productivity, biodiversity, and sustainability of the land. Anthropogenic factors, such as mining, brick kiln operations, and industrial seepage, have particularly affected specific areas. Within the study area along the Hagari River, active geomorphological changes have occurred due to wind action. The presence of unidirectional asymmetrical ripple marks in the study area provides evidence of ongoing desertification. The high surface winds during the southwest monsoon (June–September) have led to the presence of unstable sand dunes and alluvium along the river’s surroundings. As a result of sand migration, land degradation and eventual desertification have taken place. The role of sand and dunes in ecosystem transformation is significant, and they are categorized based on their size, shape, environmental influence, complexity, and wind direction. Arid and semi-arid regions face a severe risk of wind erosion, involving both the

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removal and deposition of soil particles due to wind action and the abrasive effects of particles in motion during transport.

7.12 Change Detection Analysis for the Preparation of Sand Migration and Desertification Status Maps (SMDSM) The areas surrounding the Hagari River fall within the rain shadow zone, as per Koeppen’s climatic division in India. Typically, the migration of desert dunes occurs on the right side of the mandalas. The Hagari River bed serves as the origin point for these sands, which are then carried and transported by the force of wind. Consequently, these sands are referred to as aeolian sands, and this particular type of desertification is known as aeolian desertification (Kumar et al. 2021). During the southwest monsoon season (June–September), the study area experiences strong surface winds flowing from the west to the eastern side, reaching speeds of 22–36 km/h. As a result of these powerful winds, the sand has migrated into the agricultural fields, leading to reduced soil fertility and devastating effects on agriculture within the study area. The study reveals the presence of various sizes and shapes of dunes, with transverse and linear dunes being particularly common (Anusha et al. 2022). The migration of sands and the process of desertification from the west to the eastern side is evidenced by the presence of unidirectional asymmetrical ripple marks. Data from the past 30 years, spanning from 1990 to 2020, has been taken into consideration for analysis. The statistical analysis indicates a moderate to high rate of migration of aeolian sands along the Hagari River. The study presents the Soil Moisture Density Scatterometer (SMDSM) data individually for the years 1990, 2000, 2010, and 2020. Figure 7.6 illustrates the SMDSM maps of the Hagari River for the aforementioned years. In 1990, the measurement of aeolian sand desertification was 28.22 km2 , which increased to 33.86 km2 in the year 2000. The decade from 1990 to 2000 witnessed a growth of 5.64 km2 in desertification. By the year 2010, the extent of aeolian sand desertification reached 46.30 km2 , and in 2020, it expanded further to 58.62 km2 (5862 ha). Over the decade from 2010 to 2020, desertification increased by 12.32 km2 . These numbers highlight the alarming rate at which aeolian sand desertification has escalated over the span of 30 years, resulting in a total land extent of 30.4 km2 (as shown in Table 4.6). Utilizing geometric calculation techniques, the migration of sand over this 30-year period was analyzed, revealing continuous dune migration and a highly active desertification process in this area. This study confirms that the aeolian sands present in the Hagari River are the primary drivers of this desertification phenomenon. Figure 7.7 depicts the various field photographs showing the intensity of sand migration that causes to desertification in and around the Hagari River in the study area (Table 7.1).

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Fig. 7.6 SMDSM for the years 1990, 2000, 2010, and 2020

Fig. 7.7 Sand migration and desertification status along the Hagari River. a Hagari River b Sand migration into agricultural fields and desertified entire agricultural field c Sand dune formation in the agricultural lands d Vegetation cover filled with migrated sands e Sand dune encroachment f Roads are filled with migrated sands by the action of wind g Hagari/Vedavathi Cannel flows along the Hagari River h Reduction of sand dune encroachment along the Hagari River by DWAMA

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Fig. 7.7 (continued)

Table 7.1 Change detection analysis Year

1990

2000

2010

2020

Change (1990–2020)

Desertified area (km2 )

28.22

33.86

46.30

58.62

30.4

7.13 Accuracy Assessment Accuracy assessment (AA) plays a crucial role in the grouping procedure. To ensure precise evaluation, pixel selection was focused on areas that could be clearly identified using high-resolution images from Landsat 8 OLI/TIRS, Google Earth, and Google Maps. A total of 50 points were characterized on the image. Geographical maps and Google Earth were utilized as reference sources to classify the selected features (Aslami and Ghorbani 2018; Johnson 2015). Figure 7.1 illustrates the relationship between the ground truth information and the corresponding classified information, as depicted in the error matrix report. To assess accuracy, KAPPA analysis, a discrete multivariate technique, was employed (Rwanga and Ndambuki 2017). The KAPPA analysis generated a Khat statistic, which serves as an estimate of KAPPA and measures the level of agreement or accuracy. Using the equation provided in ArcGIS, the accuracy was computed. The results obtained from the AA process indicated an overall accuracy of approximately 88% based on the random sampling

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method used for the image. Figure 7.8 shows the highly reputed and highly circulated newspaper articles on the sand migration and desertification intensity in the study area.

Fig. 7.8 Newspaper articles on sand migration and desertification happening in the semi-arid regions of Anantapur district of southern India

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7.14 Conclusion The use of remote sensing techniques for land use and cover mapping in desertified areas has major benefits, such as broad geographic coverage, frequent data availability, and the ability to track changes over time. A full knowledge of the geographical patterns and dynamics of visual hazard events may be acquired by merging remote sensing data with field observations and auxiliary information. This understanding will aid in evidence-based decision-making, policy formulation, and proactive planning to mitigate desertification and safeguard sensitive areas. The supervised classification-based land cover changes for Hagari River are classified into five classes, viz. sand dunes, vegetation, fallow land, and water bodies for the past three decades, and restricted to estimate change detection for sand dunes. The resultant land cover changes of sand dune migration caused desertification in the study area in the year 1990 is estimated as 28.22 km2 , in the year 2000, it is increased and estimated as 33.86 km2 , in the year 2010. It is increased and estimated as 46.30 km2 , and in the year 2020, it is increased and estimated as 58.62 km2 . Based on the findings, the resultant land cover change for desertification is increased from 1990 to 2020 at alarming rates. A total of 30.4 km2 of land or 3040 ha or 7512.04 acres of productive land is turned into desertification. The accuracy assessment showed an overall accuracy of about 88% from the random sampling process.

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Chapter 8

Controlling Measures for a Visual Disaster

Abstract The chapter “Controlling Measures for a Visual Disaster” focuses on practical methods and mitigation techniques for visual catastrophes. It emphasizes the significance of proactive planning, emergency response, catastrophe recovery, and community participation in preserving aesthetically significant sites and fostering sustainable development. The chapter emphasizes the importance of risk assessment, early warning systems, sustainable reconstruction, and public awareness in order to ensure the preservation of visual aesthetics and cultural heritage in the face of calamities. Keywords Visual disaster · Planning · Assessment · Sustainable development

8.1 Introduction The chapter begins by discussing the importance of visual aesthetics in our societies and the psychological and economic significance attached to visually appealing environments. It highlights the vulnerability of visually impactful landmarks, monuments, and tourist attractions to natural disasters, accidents, or intentional acts of destruction (Alkhamisi et al. 2020). Next, the chapter delves into the key elements of a comprehensive visual disaster management plan. It explores the need for preemptive measures such as risk assessment, vulnerability mapping, and emergency preparedness strategies to mitigate the potential impacts. The importance of early warning systems, evacuation procedures, and communication networks is emphasized to facilitate efficient response and coordination during visual disasters (Bautista et al. 2014; Brandt et al. 2016; Alsharif et al. 2020). Furthermore, the chapter explores post-disaster measures aimed at recovery, restoration, and reconstruction. It delves into the role of urban planners, architects, engineers, and local communities in the revitalization of damaged areas. The integration of sustainable practices and innovative technologies for reconstruction is also highlighted, ensuring the preservation of cultural and environmental values while In this chapter, we will discuss the controlling measures for the visual hazard of land degradation and desertification. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 P. K. Badapalli et al., Aeolian Desertification, Advances in Geographical and Environmental Sciences, https://doi.org/10.1007/978-981-99-6729-2_8

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enhancing resilience against future disasters (Dorji et al. 2019; Cheng and Wang, 2020; Gao et al. 2021). The chapter also addresses the role of government agencies, non-profit organizations, and international collaborations in coordinating and implementing effective controlling measures. It discusses the allocation of resources, legal frameworks, and policies required to support disaster response and recovery efforts. Finally, the chapter concludes by highlighting the importance of public awareness, education, and community engagement in preventing visual disasters and promoting responsible tourism practices. It emphasizes the need for ongoing monitoring, regular maintenance, and periodic reviews of disaster management plans to ensure their relevance and effectiveness. In summary, “Controlling Measures for a Visual Disaster” provides a comprehensive overview of the strategies and measures necessary for managing and mitigating the impacts of visual disasters. By understanding the complexities involved and implementing appropriate controlling measures, societies can safeguard their valuable visual assets and promote sustainable development for future generations. Desertification and land degradation are two linked problems that have gained significant worldwide attention. Land degradation is the term used to describe the decline in land quality brought on by human activities including overgrazing, deforestation, and improper farming methods (Glantz 2015; Ibrahim et al. 2017; Guo et al. 2019). On the other hand, the term “desertification” describes the process through which rich land eventually resembles a desert as a result of a mix of natural and human-caused events. Both of these problems have the potential to significantly alter how the landscape seems, notably by causing soil erosion, the loss of flora, and the formation of arid-looking regions. This article will examine several forms of control that may be used to deal with these problems.

8.2 Controlling Measures “Controlling Measures for a Visual Disaster” focuses on the critical aspects of managing and mitigating the impacts of visual disasters. Visual disasters refer to catastrophic events that result in significant damage to landscapes, iconic structures, or natural wonders, causing distress and loss for communities and tourists alike. This chapter explores various strategies, techniques, and frameworks employed to control and minimize the adverse effects of such disasters (Jaetzold et al. 2007; Lal 2016; Li et al. 2019). 8.2a Land Use Planning: Addressing land deterioration and desertification requires thoughtful land use planning. It entails locating regions that are more vulnerable to these issues and creating suitable land use strategies to safeguard them. For instance, places with sloping terrain, delicate soils, or few water supplies may be set aside for conservation or replanting (Long et al. 2021). Similar to this, locations with high levels of erosion might be targeted for soil conservation techniques such contour

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plowing, crop rotation, terracing, and cover cropping. In addition, zoning restrictions may be used to limit activities in susceptible regions that are likely to contribute to desertification or land degradation. Land use planning is a critical component of controlling measures for the visual disaster of land degradation and desertification. It involves the careful management and allocation of land resources to ensure that they are used in a sustainable and responsible manner. The following are some land use planning measures that can be used to address land degradation and desertification: 8.2b Zoning: Zoning involves dividing land into different zones for different uses, such as agricultural, residential, commercial, and industrial (Mabhaudhi et al. 2019). This helps to prevent land degradation and desertification by ensuring that each zone is used for its intended purpose and that incompatible land uses are separated. 8.2c Land Use Regulations: Implementing laws and rules to limit how land is used is known as land use regulation. The quantity of land that may be utilized for agriculture may be restricted, the use of pesticides and fertilizers may be regulated, and soil conservation practices may be mandated. By encouraging sensible land use habits, these policies assist to stop desertification and land degradation. 8.2d Rehabilitation of Degraded Land: Restoring degraded land to its original form is part of the rehabilitation process. This might involve establishing vegetation, such as grasses and trees, as well as taking action to conserve soil. By restoring the biological balance of degraded regions and maintaining ecosystem services, the restoration of degraded land aids in the prevention of land degradation and desertification (Mahyari and Mofidi 2020). 8.2e Sustainable Land Management Practices: Sustainable land management practices involve using land in a way that is environmentally and socially sustainable. This can include practices such as conservation agriculture, agroforestry, and sustainable grazing. These practices help to prevent land degradation and desertification by promoting responsible land use practices that preserve soil fertility, reduce soil erosion, and protect biodiversity (Martínez-Valderrama et al. 2021). 8.2f Participatory Land Use Planning: Participatory land use planning involves involving local communities in the planning and management of land resources. This helps to ensure that the needs and priorities of local communities are taken into account, and that land use practices are implemented in a way that is socially and culturally appropriate (Montserrat and Martínez-Fernández 2016). In summary, land use planning is an essential part of strategies for preventing the visual catastrophes of land degradation and desertification. We can make sure that land resources are used in a sustainable and responsible manner and that the visual impact of land degradation and desertification is reduced by implementing zoning, land use regulations, sustainable land management practices, the rehabilitation of degraded land, and participatory land use planning. We can encourage sustainable land use practices and safeguard our planet’s land resources for future generations by cooperating to put these policies into action.

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8.3 Soil Conservation Soil conservation measures are critical to prevent soil erosion and improve soil quality. These practices may include contour plowing, crop rotation, terracing, and cover cropping. Contour plowing involves plowing across the slope of the land rather than up and down, which helps to reduce water runoff and soil erosion. Crop rotation involves rotating crops on a field to reduce soil nutrient depletion and increase soil fertility. Terracing involves building steps into steep slopes to prevent soil erosion and retain water. Cover cropping involves planting a cover crop such as clover or vetch to protect the soil and improve soil quality (Nicholson 2014; Squires and Lu 2020; Muñoz-Rojas et al. 2021). Soil conservation is another important component of controlling measures for the visual disaster of land degradation and desertification. Soil erosion, nutrient depletion, and loss of soil fertility are common consequences of land degradation and desertification, which can lead to a decline in crop productivity, biodiversity, and ecosystem services. The following are some soil conservation measures that can be used to address these issues: 8.3a Conservation Tillage: Conservation tillage involves reducing the amount of tillage or plowing used in agriculture. This helps to preserve soil structure, reduce erosion, and increase soil organic matter. Conservation tillage also promotes the retention of soil moisture, which is important for maintaining crop productivity and supporting ecosystem services. 8.3b Cover Cropping: Cover cropping involves planting crops that cover the soil surface during the fallow period between crops. This helps to protect the soil from erosion, improve soil fertility, and support biodiversity. Cover cropping also promotes the retention of soil moisture, which is important for maintaining crop productivity and supporting ecosystem services. 8.3c Terracing: Terracing involves constructing terraces or steps on steep slopes to reduce soil erosion and increase water retention. This helps to prevent soil loss, promote soil fertility, and support ecosystem services. Terracing also provides additional benefits, such as reducing the risk of landslides and promoting sustainable land use practices. Windbreaks: Windbreaks involve planting rows of trees or shrubs to protect fields from wind erosion. This helps to reduce soil loss, improve soil fertility, and support biodiversity. Windbreaks also provide additional benefits, such as reducing the risk of crop damage from wind and promoting sustainable land use practices. 8.3d Soil Amendments: Soil amendments involve adding organic matter, such as compost or manure, to the soil to improve soil fertility and structure. This helps to promote crop productivity, support biodiversity, and enhance ecosystem services. Soil amendments also help to reduce soil erosion and promote the retention of soil moisture, which is important for maintaining healthy soil and supporting sustainable land use practices.

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Finally, soil preservation is a crucial part of strategies for preventing the visually disastrous effects of desertification and land degradation. Measures for preserving the soil aid in preventing soil erosion, enhancing soil fertility, and supporting ecosystem services. We can lessen the visual effects of desertification and land degradation by putting in place soil conservation measures. We can also rehabilitate damaged regions and encourage sustainable land management techniques for future generations.

8.4 Water Conservation Water conservation measures can help to reduce water use and promote more sustainable water management. These may include drip irrigation, rainwater harvesting, and the use of drought-resistant crops. Drip irrigation involves using a network of tubes to deliver water directly to the roots of plants, which can reduce water loss due to evaporation and runoff. Rainwater harvesting involves collecting and storing rainwater for later use, which can be especially beneficial in arid regions. The use of drought-resistant crops can help to reduce water use and promote more sustainable agriculture (Tengberg et al. 2020; Wang et al. 2020; UNCCD 2021). Water conservation is an important component of controlling measures for the visual disaster of land degradation and desertification. Land degradation and desertification can lead to a decline in water availability, quality, and accessibility, which can have significant impacts on human and ecosystem health. Water conservation involves reducing water use, improving water quality, and preserving water resources, which helps to support ecosystem services and promote sustainable land use practices (Zhang et al. 2018). The following are some water conservation measures that can be used to address these issues: 8.4a Rainwater Harvesting: Rainwater harvesting involves collecting and storing rainwater for later use. This can be done through the use of rain barrels, cisterns, or other storage devices. Rainwater harvesting helps to reduce water use and improve water quality by reducing runoff and erosion. It also promotes sustainable agriculture and supports ecosystem services, such as soil conservation and biodiversity conservation. 8.4b Soil Moisture Conservation: Soil moisture conservation involves retaining soil moisture through the use of conservation tillage, cover crops, and other techniques. This helps to reduce water use, improve soil fertility, and prevent erosion. Soil moisture conservation also promotes sustainable agriculture and supports ecosystem services, such as carbon sequestration and biodiversity conservation. 8.4c Irrigation Management: Irrigation management involves optimizing irrigation practices to reduce water use and improve crop productivity. This can be done through the use of efficient irrigation systems, such as drip irrigation, and by reducing water losses through evaporation and runoff. Irrigation management also promotes

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sustainable agriculture and supports ecosystem services, such as soil conservation and biodiversity conservation. 8.4d Water Reuse: Water reuse involves treating and reusing wastewater for nonpotable uses, such as irrigation and industrial processes. This helps to reduce water demand and improve water quality by reducing pollution and nutrient runoff. Water reuse also promotes sustainable land use practices and supports ecosystem services, such as soil conservation and biodiversity conservation. 8.5e Restoration of Wetlands and Riparian Areas: Wetlands and riparian areas play a critical role in regulating water cycles, supporting biodiversity, and providing ecosystem services. Restoration of wetlands and riparian areas helps to improve water quality and availability, reduce erosion, and support sustainable land use practices. This can be done through the restoration of degraded wetlands and riparian areas and the protection of existing wetlands and riparian areas from further degradation. In conclusion, water conservation is an important component of controlling measures for the visual disaster of land degradation and desertification. Water conservation helps to reduce water use, improve water quality, and preserve water resources, which are critical for supporting ecosystem services and promoting sustainable land use practices. By implementing water conservation measures, we can reduce the visual impact of land degradation and desertification, restore degraded areas, and promote sustainable land management practices for future generations.

8.5 Reforestation Reforestation can aid in the restoration of damaged regions and the prevention of additional land degradation. This entails planting trees and other plants to stabilize soils and offer animal habitat. Furthermore, reforestation can assist to trap carbon dioxide from the atmosphere, therefore mitigating the effects of climate change. Reforestation can occur naturally or by the planting of trees and other plants (Pete et al. 2019; Yang et al. 2020; Smith et al. 2020). Reforestation is an important component of the visual disaster of land degradation and desertification management strategies. Forests serve an important role in regulating water cycles, maintaining soil fertility, and sustaining biodiversity; hence, deforestation and forest degradation are primary causes of land degradation and desertification. Reforestation is the intentional planting of trees in degraded or deforested regions in order to restore forest cover and ecosystem services. Some replanting strategies that can be utilized to alleviate these challenges are as follows: 8.5a Afforestation: Afforestation is the practice of growing trees in regions where there were previously no woods. This can be done on degraded or deforested land, in urban areas, or in other locations. Afforestation contributes to the restoration of ecosystem services including carbon sequestration, biodiversity conservation, and soil conservation.

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8.5b Reforestation: Planting plants in locations where forests have been destroyed or damaged is known as reforestation. This can be done on deforested or degraded land, as well as in locations where forests have been devastated by natural catastrophes or other disturbances. Reforestation contributes to the restoration of ecosystem services including carbon sequestration, biodiversity conservation, and soil conservation. 8.5c Agroforestry: Agroforestry is the practice of incorporating trees into farming systems to offer shade, soil conservation, and crop variety. Agroforestry also supports biodiversity protection and carbon sequestration, which aids in climate change mitigation. Agroforestry has the potential to repair damaged or deforested land while also promoting sustainable agriculture. 8.5d Forest Landscape Restoration: Forest landscape restoration entails rebuilding damaged or deforested areas by reforestation, afforestation, and agroforestry. The goal of forest landscape restoration is to restore ecosystem services such as carbon sequestration, biodiversity conservation, and soil conservation while also supporting sustainable land use practices. 8.5e Community-Based Reforestation: Community-based reforestation involves working with local communities to restore degraded or deforested areas. This approach involves engaging local communities in the restoration process, including the selection of tree species, planting, and maintenance. Community-based reforestation also helps to build community resilience and promote sustainable land use practices. To summarize, reforestation is a crucial component of the visual calamity of land deterioration and desertification. Reforestation contributes to the restoration of forest cover and ecosystem services, which are necessary for regulating water cycles, preserving soil fertility, and sustaining biodiversity. We can lessen the visual effect of land degradation and desertification, rehabilitate damaged regions, and encourage sustainable land management practices for future generations by applying reforestation techniques.

8.6 Sustainable Agriculture Sustainable agricultural practices can help to reduce soil erosion, increase soil fertility, and improve crop yields. This may include the use of organic farming methods, integrated pest management, and crop diversification. Organic farming methods involve using natural fertilizers and pesticides rather than synthetic ones, which can help to improve soil quality and reduce water pollution. Integrated pest management involves using a combination of methods to control pests, such as crop rotation, planting pest-resistant crops, and using natural predators. Crop diversification involves growing a variety of crops on a field to reduce soil nutrient depletion and increase soil fertility (Akpoti et al. 2019; Kowalska et al. 2020; Anusha et al. 2023).

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Sustainable agriculture is a crucial component of controlling measures for the visual disaster of land degradation and desertification. Unsustainable agricultural practices, such as overgrazing, deforestation, and intensive monoculture farming, are major drivers of land degradation and desertification. Sustainable agriculture, on the other hand, promotes the use of land and water resources in a way that preserves soil fertility, protects biodiversity, and supports food security. The following are some sustainable agriculture measures that can be used to address these issues: 8.6a Conservation Agriculture: Conservation agriculture is a sustainable farming system that promotes minimal soil disturbance, permanent soil cover, and crop rotations. This farming system helps to improve soil fertility, reduce erosion, and conserve water. Conservation agriculture also promotes the use of agroforestry systems, which integrate trees into farming systems to provide shade, soil conservation, and crop diversification (Taghizadeh-Mehrjardi et al. 2020). 8.6b Integrated Pest Management: Integrated pest management (IPM) is an environmentally friendly approach to pest control that aims to reduce the use of pesticides. IPM involves using a combination of techniques, such as crop rotation, biological control, and natural pest predators, to control pests. IPM helps to reduce the negative impacts of pesticides on the environment and human health. 8.6c Agroforestry: Agroforestry is a land use system that integrates trees and crops on the same land. This system helps to improve soil fertility, reduce erosion, and provide shade and shelter for crops and livestock. Agroforestry also promotes biodiversity conservation and carbon sequestration, which helps to mitigate climate change. 8.6d Soil Conservation: Contour farming, terracing, and conservation tillage are all soil conservation techniques that assist to reduce soil erosion and promote soil fertility. These strategies help to sustain agricultural land production while also protecting the environment. 8.6e Water Conservation: Drip irrigation, rainwater harvesting, and efficient irrigation systems are examples of water conservation practices that help to preserve water and decrease water stress. Water conservation strategies also assist to increase crop yields and promote long-term agricultural productivity. Finally, sustainable agriculture is a critical component in mitigating the visual disasters of land degradation and desertification. Sustainable agricultural practices encourage the use of land and water resources in ways that conserve soil fertility, safeguard biodiversity, and contribute to food security. We can lessen the visual impact of land degradation and desertification by implementing sustainable agricultural methods, restoring degraded regions, and promoting sustainable land management practices for future generations.

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8.7 Education and Awareness Educating people about the impacts of land degradation and desertification can help to increase awareness and encourage action to address these issues. This may involve providing training and education programs for farmers, land managers, and community members. These programs can help to promote sustainable land management practices, raise awareness about the importance of soil and water conservation, and encourage the adoption of sustainable agriculture practices (Amini et al. 2020). Education and awareness are important components of controlling measures for the visual disaster of land degradation and desertification. Education and awareness campaigns can help to raise public awareness about the causes and impacts of land degradation and desertification and promote sustainable land management practices. The following are some education and awareness measures that can be used to address these issues: 8.7a School-Based Education: Schools may serve as an essential platform for spreading knowledge and raising awareness regarding land degradation and desertification. Sustainable land management practices, such as soil conservation, water conservation, reforestation, and sustainable agriculture, can be included into school curricula. Field tours to degraded regions can also be organized by schools to assist students understand the effects of land degradation and desertification, as well as the need of sustainable land management practices. 8.7b Public Awareness Campaigns: Public awareness initiatives can assist to increase understanding of the causes and consequences of land degradation and desertification. Advertisements, posters, pamphlets, and social media campaigns are examples of these campaigns. Community events such as tree planting, clean-up efforts, and educational seminars can also be included in public awareness campaigns. 8.7c Informational Materials: Informational materials can help to educate the public about sustainable land management practices. These materials may include brochures, pamphlets, and fact sheets. They may also include videos, webinars, and online resources. Informational materials can be distributed at community events, schools, and public gatherings. 8.7d Community-Based Education: Community-based education can help to encourage local sustainable land management practices. This may entail collaborating with local populations to understand the causes and consequences of land degradation and desertification, as well as devising local solutions to these problems. Community-based education can also serve to raise knowledge and comprehension of the significance of sustainable land management practices. 8.7e Training Programs: Technical instruction and assistance for sustainable land management practices can be provided via training programs. These programs might involve soil conservation, water conservation, reforestation, and sustainable agricultural training. They may also involve company management, marketing, and financial

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planning training. Training programs can assist local communities and individuals gain the ability to adopt sustainable land management practices. Finally, education and awareness are critical components in controlling the visual calamity of land degradation and desertification. Education and awareness campaigns can assist improve public knowledge about the causes and consequences of land degradation and desertification while also promoting sustainable land management practices. We can lessen the visual effect of land degradation and desertification, rehabilitate degraded regions, and promote sustainable land management practices for future generations by adopting education and awareness efforts.

8.8 Policy and Governance Play a crucial role in addressing land degradation and desertification. Effective policies can help to create an enabling environment for sustainable land management, while good governance can ensure that policies are implemented effectively and efficiently. The following are some policy and governance measures that can be used to address these issues: 8.8a National Action Plans: National action plans can provide a framework for addressing land degradation and desertification at a national level. These plans may include strategies for sustainable land management, soil conservation, water conservation, and reforestation. They may also include targets for reducing land degradation and desertification and measures for monitoring and reporting progress. 8.8b Land Tenure and Property Rights: Secure land tenure and property rights can be used to incentivize sustainable land management. People who have solid land rights are more inclined to invest in soil protection and reforestation. Secure land tenure and property rights can also help to reduce land degradation by decreasing land grabs and speculation. 8.8c Payment for Ecosystem Services: Payment for ecosystem services (PES) can provide financial incentives for environmentally sound land management. PES programs compensate landowners or communities for environmental services such as carbon sequestration, water conservation, and biodiversity protection. Reforestation, sustainable agriculture, and soil protection can all benefit from PES programs. 8.8d Environmental Regulations: By establishing environmental protection standards, environmental rules can help to avoid land deterioration and desertification. These rules may include soil conservation, water conservation, and air quality criteria. They may also involve land use planning and zoning restrictions. 8.8e Participatory Governance: Participatory governance can assist to guarantee that land degradation and desertification policies and programs are responsive to local needs and interests. This may entail integrating local communities and stakeholders in decision-making processes and providing them a voice in policy and program

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creation and execution. Participatory governance may aid in the development of trust and ownership in policies and programs, as well as their effective execution. To summarize, land degradation and desertification are severe worldwide concerns with enormous aesthetic consequences for the landscape. To address these concerns, a variety of control measures are required, including land use planning, soil conservation, water conservation, reforestation, sustainable agriculture, education and awareness, and policy and governance. Policies and governance that are effective and efficient can assist to establish an enabling environment for sustainable land management. We can lessen the visual effect of land degradation and desertification by applying these strategies, restoring damaged regions, and promoting sustainable land management practices for future generations.

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