514 106 3MB
English Pages 100  Year 1996
Internationally recognized scholars from many parts of the world provide a critical survey of recent developments and ac
169 29 109MB Read more
Gender inequality is entrenched in the cultural, political, and market systems that operate at household, community, and
428 92 47MB Read more
This brief presents the case study of a hill in Czech Republic (Říp) and its region, and contributes to theorization in
392 77 23MB Read more
Internationally recognized scholars from many parts of the world provide a critical survey of recent developments and ac
151 23 24MB Read more
299 98 227MB Read more
138 45 143MB Read more
InOn the Genealogy of Color, Zed Adams argues for a historicized approach to conceptual analysis, by exploring the relev
417 38 2MB Read more
Vincent Gaffney and Zoran Stancic
A case study of the island of Hvar preface by Kenneth Kvamme Ljubljana
Dr. Vincent Gaffney stu died archaeology at the University of Reading, where he was awarded a PhD for his work on the archaeology of Hvar; Croatia. He is currently employed as research fellow and computer officer in the Birmingham University Field Archaeology Unit (UK). Dr. Gaffney's research interests include the Balkan Iron Age, GIShased applications in archaeology and computer-based teaching. He is Co-Director of the Adriatic Islands Project and Senior Investigator of the Wroxeter Hinterland project.
GIS approaches to regional analysis: A case study of the island of Hvar Vincent Gaffney and Zoran Stancic preface by Kenneth Kvamme
C IP - K atalozni zapis o publikaciji N aro d n a in univerzitetna knjiznica, Ljubljana 903/904(497.5 H var) 902:681.3 681.3:902 G A F FN E Y , V incent G IS approaches to regional analysis : a case study of the island of H var / V incent G affney and Z o ran Stancic ; preface by K enneth Kvanne. - R eprint - Ljubljana : Z nanstveni institut Filozofske fakultetc, 1996. - (R azprave Filozofske fakultete) ISBN 86-7207-036-4 1. Stancic, Z o ran 62722816
V incent G affney and Z o ran Stancic
GIS approaches to regional analysis: A case study of the island of Hvar E ditor: R esearch institute o f the Faculty of A rts and Science U niversity o f Ljubljana Executive E ditor: D usan N ecak Editorship: Jad ran k a Sumi Design: R anko Novak P rinted by: Birografika BOR1 p.o., Ljubljana R eprint: 300
GIS approach to regional analysis: A case study of tie island ol Hvar preface by Kenneth Kvamme
Znanstveni institut Filozofske fakultete Ljubljana 1996
PREFACE TO THE SECOND EDITION W hen we w ere approached by the Znanstveni institut Filozofske fakultete to consider a reprin t of the “A pproaches to G IS ” volum e th ere w ere a num ber of points to con sider before we accepted such a kind invitation. T he first was w hether there was any justification for a reprint. O n the whole we felt that this was worthwhile. We noted that although the num ber of G IS applications in archaeology was always increasing, there w ere very few concise texts which covered general GIS issues within the context of a basic application - even fewer had cartoons th at w ere as good as ours! Having decided that a rep rin t should go ahead, we then had to consider w hether we should com pletely revise the text or to publish as originally printed. T he decision was a hard one. We w ere well aware that not only had reviewers pointed out the shortcom ings of the original work (C hapm an 1992), but there had been a num ber of very sig nificant collections of papers and individual publications which any revision would have to take into account. In opposition to any m ajor revision was the fact that the archaeo logical project which form ed the core of the original work - The A driatic Islands Project - was now com plete and moving towards publication (Gaffney et al. forthcoming). T here seem ed little point in producing a parallel text to the final publication of a m ajor project. Equally significant was the presence of several m ajor publications on GIS in archaeol ogy to which it seem ed m ore reasonable to point the reader towards. T hese publica tions provide the read er with the m ost recent bibliographic references and applica tions and include the collection of papers edited by Lock and Stancic (1995), based on the proceedings of an excellent conference held at Ravello, and the archaeological G IS bibliography (P etrie et al. 1995). R eplication o f such good work seem ed u n re a sonable. Consequently, the text rem ains as original and is presented, once again, “warts and all”. Since the first edition was published the countries of form er Yugoslavia have witnessed m uch turm oil and disruption. As a result of these events, the island of H var and D al m atia now reside within the state of C roatia, whilst Ljubljana is now the capital of the Slovenia. D espite this, it is im portant to note th at all our colleagues have m aintained the true spirit of academ ic co-operation and that their selfless support alllowed us to p roduce this book. P erhaps we can allow ourselves one last personal observation. Once again the in tro duction is being w ritten on a cold w in ter’s day in Ljubljana, but this time we are in the com pany of Professor Ken Kvamme, who w rote the preface to the original work. We anticipate lots of beer and lots of fun. Vince G affney and Z o ran Stancic Ljubljana D ecem ber 1995 C hapm an J. 1992, V. G affney - Z. Stancic, GIS approaches to regional analysis: a case study o f the island of Hvar. A R H E O , 15, 111-112. Gaffney V , Kirigin B., Petrie M. and Vujnovic N. forthcom ing, The A driatic Islands Project: com m erce, contact and colonisation, Volume 1. T he archaeological heritage of H var. B ritish A rchaeological R eports, Oxford. Lock G. and Stancic Z. (Eds.) 1995. A rchaeology and geographical inform ation sys tems: a E u ro p ean perspective, Taylor & Francis, London. Petrie L., Johnson I., Cullen B. and Kvamme K. (Eds.) 1995, GIS in archaeology: an an notated bibliography, Sydney University A rchaeological M ethods Series 1, Sydney.
Contents Illustrations Preface
Section one: THE C O N C EPTS AND C O M PO N E N T S O F G E O G R A PH IC INFORM ATION SY STE M S 1. GIS -- introduction and definition 2. The components o f GIS
15 15 16
2.1. H ardw are ......................................................................................................... 2.1.1. D ata input devices ............................................................................ 2.1.2. Rem ote sensing ................................................................................. 2.2. Software ............................................................................................................ 2.2.1. The data acquisition modules .................................................... 2.2.2. D ata processing m odules ............................................................. 2.2.3. Analytical m odules ......................................................................... 2.2.4. D ata presentation modules .......................................................... 3. GIS data
3.1. Vector vs. Raster G IS
16 17 19 21 21 22 22 24 25
4. GIS and Archaeology ........................................................... 5. Choosing a Geographic Information System ............................ 6. GIS software and hardware used in the case study
29 32 33
Section two: THE HVAR CASE STU DY 1. The study area 2. The environmental data base
35 35 36
D EM ................................................................... Soils .................................................................................................................. Lithology ......................................................................................................... M icro-clim ate
36 37 39 40
2.1. 2.2. 2.3. 2.4.
3. The Hvar archaeological database
3.1. Previous archaeological w ork on the island ......................................... 3.2. An outline of the archaeology of H var ................................................. 3.2.1. The Neolithic period ...................................................................... 3.2.2. The Bronze Age ............................................................................... 3.2.3. The Iron Age .................................................................................... 3.2.4. The G reek Period 3.2.5. The Rom an Period ................................................................... 3.2.6. The Post Rom an period 3.3. The archaeological database ......................................................................
41 42 42 43 43 44 45 46 46
4. GIS approaches to the archaeology of Hvar .................................. 5. G IS approaches to territorial boundary definition ......................... 6. Cairns and tumuli; agricultural clearance or ritual activity ...............
47 48 57
6.1. Problem s in the definition o f stone cairns and tum uli .................... 6.2. The analysis o f stone cairns on the island of H var ..........................
7. Roman villas in the landscape 8. The Greeks on Hvar: optimal paths and visibility analysis in archaeology .............................................................. 9. Neolithic settlement on Hvar: archaeological limitations and GIS applications 10. GIS and heritage management 11. Concluding comments
Appendix: Codes used in the Hvar sites and monuments register
ILLUSTRATIONS 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42.
G IS hardw are The digitiser The scanner The electrom agnetic spectrum Exam ples o f inform ation derived from the D igital Elevation M odel (D EM ) G IS d ata layers R aster representation o f vegetation d ata layer Flow chart representing G IS inform ation paths L ocation of the island o f H v ar within Europe The H var D E M Simplified soil m ap based on agricultural potential Pie chart illustrating soil classes on the island of H var Lithological m ap o f H var Pie chart illustrating lithology classes on the island of H var M icroclim ate zones N eolithic findspots on the island o f H var Bronze Age findspots on the island o f H var Iron Age findspots on the island o f H var G reek findspots on the island o f H var R om an findspots on the island o f H var D istribution o f hillfort sites with boundaries defined through G IS modules T rad itio n al site catchm ents for hillfort sites T rad itio n al and G IS derived catchm ents for the Gracisce hillfort T rad itio n al and G IS derived catchm ents for the H var Castle hillfort G IS catchm ents for m ajor hillfort sites on the island of H var G racisce catchm ent and soil types H illfort catchm ents and soil types on the island of H var Relative size o f hillfort catchm ents in hectares H illfort sites and pie charts illustrating the p ro portion of soil types within in dividual catchm ents Soils and hillfort catchm ents including the Umic site The d istribution o f stone cairns The distribution o f tum uli C airns and tum uli: expected and actual occurrences against soil type C airns and tum uli: expected and actual occurrences against lithology C airns, tum uli and the G racisce catchm ent C airns, tum uli and the H var Castle catchm ent T um uli w ithin the bay at Vira (after Zaninovic 1978b) The distribution o f cairns and tum uli w ithin hillfort catchm ents on the eastern p a rt o f the island o f H var C orrelation o f R om an settlem ent sites and soil types C orrelation o f R om an settlem ent sites and climate R om an settlem ent sites, clim ate and soil ranked by chi square value G IS derrived m odel for R om an settlem ent 7
43. The distribution o f R om an settlem ent sites on the Stari G rad plain 44. The distribution o f R om an settlem ent sites and soil groups on the Stari G rad plain 45. The distrib u tio n o f R om an settlem ent sites and lithologies on the Stari G rad plain 46. R om an settlem ent sites and soils on the Stari G rad plain: expected and actual occurrence 47. R om an settlem ent sites and lithology on the Stari G rad plain: expected and actual occurrence 48. R om an sites w ith pie charts illustrating the proportions of soil types within G IS derived catchm ents 49. G IS derived territory and soil types for the R om an site at Dolcic 50. Visibility analysis based on the G reek tow er at M aslinovik 51. C ost surface analysis between Pharos and the tow er at T or 52. O ptim al path between Pharos and the tow er at M aslinovik 53. N eolithic cave sites on H var 54. Soil types within neolithic cave site catchm ents 55. Soils and lithologies within the catchm ent of the cave site of Vela spilja 56. Soils and lithologies w ithin the catchm ent of the cave site of M arkova spilja 57. L and surface falling within the catchm ents of neolithic cave sites 58. N eolithic cave sites and lithology on the island of H var 59. Levels of destruction on archaeological sites on H var 60. Excavated sites on H var 61. Slightly dam aged sites on H var 62. Badly dam aged sites on H var 63. T otally destroyed sites on H var
ACKNOWLEDGEMENTS We w ould like to acknow ledge all the help, finance and encouragem ent given by the follow ing individuals and institutions w ithout w hom we w ould not have been able to com plete this volum e. Lots o f beers and lots of fun. T he staff o f the A rkansas A rchaeological Survey especially; Dr. F. Lim p, J. L ock h art, R. H arris, J. Fairley, I. W illiam s, The D epartm ent of A rchaeology, The University o f L jubljana, The D ep artm en t o f A rchaeological Sciences, University o f B radford (G reat B ritain), The H v ar P roject, The C entre for the P rotection of the C u ltu ral H eritage o f the Island o f H v ar, The British C ouncil, The British A cadem y, The A rchaeological M useum in Split, The D epartm ent of A rchaeology, U niversity o f R eading (G reat B ritain), The U rban Institute of the Republic of C ro atia, D r. J. Bintliff, D r. F. C arter, D r. B. Slapsak, D r. J. H ayes, D r. G. Bozovic, D r. P. Sivic, Prof. M. F ulford, S. Levi, B. K irigin, M. K olum bic, M. Petrie, N. V ujnovic, J. K ovacic, N. Petrie, H. W atson, T. G rajf, K. Predovnik. Special thanks to G. Burrows for the cartoons. Finally, we w ould like to th an k all the staff o f the H var Project, who provided free access to the unpublished d ata used in the case study, and the students o f the uni versities o f L jubljana, B radford, Belgrade, Z agreb and Skopje w ho did all the real w ork, collecting the data. 9
PREFACE It is inco ntrovertible th at the study o f archaeology im plies, by its very nature, the investigation o f spatial distributions: archaeological cultures are associated with particu lar localities on a continental scale; sites o f past occupation have location w ithin regions; and artifacts have spatial positions within sites. It is also equally true th a t archaeologists generally are slow to incorporate new technologies into their research repertoires - we have an intense focus on the past, after all, which perhaps inhibits us from looking forw ard. There are notable ex ceptions to this rule, how ever, and the present volum e is a case in point. G IS A P P R O A C H E S TO R E G IO N A L A N A LY SIS: A CA SE STUDY O F T H E ISL A N D O F HVAR presents one o f the first concrete applications of a relatively new com pu ter technology know n as G eographic Inform ation Systems (G IS) in archaeo logy. G IS are softw are systems specifically designed for handling data th at have a spa tial, or m appable, com ponent. As such, they are ideally suited for the handling, m an ipu latio n , and analysis o f archaeological d ata regardless o f their context, scale, or setting. M oreover, since archaeologists have a long tradition of m a p m aking - m aps are m ade of artifact distributions within structures, structures within settlem ents, and settlem ents w ithin regions, for exam ple - they will appre ciate the cartographic capabilities o f G IS. As this volum e so am ply illustrates, G IS can produce m aps in a variety o f fo rm ats, scales, and colors th at greatly facilitate regional research because m aps can be obtained very rapidly allow ing ready p o r trayal o f d a ta , an d spatial relationships betw een various phenom ena can easily be recognized when they are viewed in m ap form . G affney and Stancic are greatly concerned with transm itting an understanding of the fund am en tal principles and concepts o f G IS. In Section One they present a know ledgeable overview o f the technology including descriptions of hardw are de vices, the various softw are com ponents, system design issues, data capture m e thods, and fundam ental G IS operations. They are to be com m ended for this effort which will be welcome reading for the novice. The real co n trib u tio n to w ard influencing archaeological opinion ab out the p o ten tial of G IS in regional studies lies in the excellent applications exam ples, which form Section Two o f the volum e. D raw ing from the diverse and w ell-docum ented archaeology o f the Island o f H var, on the D alm atian C oast of Yugoslavia, several case studies are presented th a t focus on various dom ains fundam ental to lands cape analysis and regional archaeology. Site C atchm ent A nalysis is applied to investigate the distributions of Bronze and Iro n Age hillforts and later, to N eolithic cave sites. In these applications G IS p ro vide a su b stan tial deviation from the trad itio n al ap p ro ach th a t relies on simple circular catchm ents. Using com puter m odels o f the terrain surface, m ovem ent dif ficulties, and travel tim es, m ore realistic ap p ro x im ations of travel cost catchm ents are achieved th a t often are irregularly shaped ow ing to the influence o f terrain on travel. The outcom e provides a new and im proved perspective on this form of 11
analysis th a t can yield pro fo u n d ly different conclusions. The authors are overly m odest when they suggest th a t these studies m ight have been undertaken m anual ly; w ithout G IS the sheer nu m b er o f com putations required to obtain an accurate result w ould be beyond m anual means. G IS also facilitate the statistical analysis o f site location tendencies, as illustrated by two case studies. In one, the distrib u tio n of stone cairns and tum uli, ranging in age from the early Bronze Age to the first century BC, are show n to bear a strong statistical relationship with the best agricultural lands. Since nearly 50 percent of these large stone piles bear no evidence o f burials when excavated, this association lends considerable su p p o rt to the hypothesis that m any of these features simply are the result of past agricultural field clearance practices rather than funerary m onum ents. Sim ilar analyses u n d ertak en for the later R om an Villa occupation il lustrate p ronounced statistical correlations with the best agricultural lands, clim at ic settings, and certain geologic conditions th at helped prom ote this largely agri cultural system. P erhaps the best exposition o f the pow er o f G IS for archaeological settlem ent stu dies lies in the analysis o f the G reek period occupation. The G reeks, confined principally to the settlem ent o f Pharos on H var, were apparently in a state o f per petual com petition and conflict with their Illyrian neighbors. Two w atchtow ers, located som e distance from P haros, quite likely provided a system w hereby the tow n could be alerted o f ap p ro ach in g danger, probably through the use of sm oke signals. G IS -b ased lin e-o f-sig h t and intervisibility studies using a digital represen tatio n o f landform clearly show th a t these towers were visually linked with Pharos and th at they provided a view o f su bstantial p o rtions of the surrounding region, thereby offering an early-w arning system. Judging from the enthusiasm o f the au th o rs and the m any archaeological insights they gain from their em ploym ent o f G IS, it seems clear that G IS -b ased regional studies will soon becom e a regular feature o f m odern archaeology. A rchaeologists m ust deal w ith vast am ounts o f spatial in fo rm ation in regional w ork and G IS are designed specifically for the handling and m anipulation of spatial data. C onse quently, GIS and archaeology m ay represent an ideal m arriage. K enneth L. Kvamme University of A rizona M ay, 1991
INTRODUCTION A recent review o f the use o f G eog rap h ic Info rm ation Systems (G IS) quoted a British G overnm ent rep o rt which stated th a t the im pact of G IS on spatial analysis was as significant as, »the invention o f the microscope and the telescope were to science, the computer to economics and the printing press to information dissemination. It is the biggest step forw ard in the handling o f geographic information since the invention o f the map.« (DoE. 1988,8 in Harris and L o ck 1990) One w ould think th a t any p ro d u ct with such a billing w ould have been w elcom ed with open arm s by archaeologists th ro u g h o u t the w orld. The m anipulation of spa tial data has, after all, been the bread and b u tter of archaeologists for decades. D espite this fact, w idespread ad o p tio n o f G IS has not been the case. There has been a significant delay betw een the developm ent of the techniques in N orth A m erica and their application elsewhere in the world. The reasons for this gap are m any. The initial cost of h ardw are an d softw are was undoubtedly a problem . Key institu tio n s have been resilient to the use o f G IS and w idespread ignorance o f the existence or the p o tential o f the technique am ongst archaeologists has been n o ta ble until very recently. This situation is changing. The falling cost o f both softw are and hardw are places som e form o f G IS w ithin the reach o f virtually all institutions and there are in creasing num bers o f com puter literate archaeologists w ho are bo th willing and capable o f using G IS to the full. D espite this, the progress of G IS within E u ro pean archaeology at least is likely to rem ain a slow process, a problem exacerbat ed by the arcane n ature o f the literature and the difficulty in acquiring so m uch of it. This m onograph is an attem pt to introduce G IS to a wider audience within E u rope. N o attem p t has been m ade to provide a h an d b o o k to G IS applications or a review o f available hardw are and softw are, (although the references within the text lead to such inform ation). The intention is simply to give the reader some insight into the p o ten tial o f G IS for archaeological application. The first section in tro d u ces basic com ponents and concepts o f G IS, som e o f which may be unfam iliar to the general reader. The second applies selected G RASS (G eographical Resources Analysis S upport System) G IS m odules to an archaeological and environm ental database relating to the island o f H v ar in D alm atia, Yugoslavia. The problem s approached w ithin this section include; territo rial boundary definition, the analy sis o f com m unication routes and the relationship of archaeological sites to agricul tural lan d within their econom ic territories. A lthough the data used is specific to Y ugoslavia an d the k arst region o f D alm atia, the research them es are general to m ost periods and areas o f archaeological research and will be fam iliar to m ost a r chaeologists. C onsequently, we hope th at readers will interpret the results we have achieved in the light o f th eir ow n interests. We should also stress th a t we have de liberately included several instances where the analyses were not as successful as 13
we had hoped, generally the result o f inadequacies in the archaeological or envir o nm ental databases. In doing so we hope th at we can help others avoid some of the pitfalls which we ran headlong into. V incent G affney D epartm ent o f A rchaeology U niversity o f Reading, G reat Britain
Z oran Stancic D epartm ent of A rchaeology University of Ljubljana, Yugoslavia
THE CONCEPTS AND COMPONENTS OF GEOGRAPHIC INFORMATION SYSTEMS 1. GIS - INTRODUCTION AND DEFINITION The presentation o f spatial d ata in m ap form has a long history. U ntil recently the p ro d u ctio n o f such m aps was often in the hands o f civil authorities or m ilitary in stitutions, a reflection o f the im portance placed u pon the possession of such in form ation. D ata collection for these early m aps was a slow and expensive m anual process. The graphical represention o f d ata w ithin such m aps was, how ever, generally considered ad equate because o f the relatively slow rate of change w ithin society. C onsequently, the m aps p roduced by such societies retained their value and m ight be used for decades. Today, the increased rate o f change w ithin m odern societies has created a need for faster and m ore efficient d ata collection and this has led to the developm ent of new collection techniques. P hoto g ram m etric plotting, for exam ple, was developed w ithin the arena o f to pographic m apping, but even this involved the presentation o f different d ata types as a series o f separate m aps. G radually the dem and for com puter storage o f spatial inform ation grew, along with the need for systems which allow ed the easy retrieval o f such d ata for the production of them atic m aps. This goal has only been possible as a result o f the startling developm ent of com pu ter design during the 1960’s and 1970’s. These changes allowed the initial devel opm ent o f G eographic Inform ation Systems (GIS). The origins o f G IS are to be found within the developm ent of C om puter Aided M apping (C A M ) during the 1970’s. CA M is a technique which allows fast and qualitative m ap production. It is prim arily directed tow ards quality graphic re presentatio n o f data. G IS goes beyond this and is a com puter aided system for the collection, storage, retrieval, analysis and presentation of spatial d ata (C larke 1986). It in corporates the capabilities o f CA M , com puterised databases and statis tical packages, b u t differs significantly in its structure and purpose. C A M for instance, is concerned with faster and cheaper m ap production. A l though early CA M program m es did allow lim ited analysis, m anipulation and o u t 15
p u t of spatial d ata th ro u g h line p rinters, the m ap rem ained the prim ary goal of in form ation storage and display. C om puter run databases, alternatively, enable the m anipulation o f spatial d ata but have lim ited capabilities, for collection, analysis and presentation. G IS, how ever, can be better understood as a com puter database with CAM capabilities b u t which incorporates the ability to carry out statistical analysis o f spatial d ata. G IS is fu rth er separated from these o ther systems by its ability to generate new inform ation based on the data held w ithin it (Cowen 1987). The increased dem and by m odern societies for collection, analysis and presenta tion o f rapidly u p d ated spatial inform ation has spurred on G IS developm ent, a process which has involved m any related disciplines (see P arent and C hurch 1987 for a discussion of this developm ent). Indeed it could be said th a t G IS should be viewed not as a system but a technology, a technology based upon developm ents w ithin cartography, com puter graphics, com puter aided design (C A D ), photogram m etry, geodesy, rem ote sensing and related fields. As a result o f this G IS has been rapidly adopted by disciplines with an interest in the analysis of space, for exam ple in the fields o f cadastral analysis, environm ental protection, docum enta tion o f service netw orks including electrical supplies and m ost aspects of urban planning. Some archaeologists have also been quick to apply G IS. The large am ounts o f d ata generated by archaeology has necessitated the application of com p u ter aided docum en tatio n . The spatial nature o f m uch of this data, artefacts w ithin a site, sites w ithin a region o r cultures distributed across a landm ass, invite G IS applications. Indeed the full p o ten tial of spatial analysis w ithin archaeology including intra site analysis, regional settlem ent studies and cultural heritage m an agem ent is probably not realisable w ithout the use of GIS.
2. THE COMPONENTS OF GIS W ithin this chapter we will outline the principal com ponents of G IS. In order to do this we m ust view G IS w ithin the context o f the hard w are/so ftw are configura tions which produce the best results. In this m onograph we will concentrate on the hardw are and softw are, fu rth er detail on G IS organisation can be found within B urrough (1986).
2.1. Hardware G IS, like every other com puter system , utilises a series of devices for d ata input, central processing, d ata storage and d ata o u tput (figure 1). W ith the exception of d ata input these devices are n o t specific to G IS, but they should be m entioned briefly. The central processing unit, the brains o f the system, controls d ata m anipulation as well as input, o u tp u t and storage. Storage devices such as diskettes, disks and tapes are m agnetically based. H ow ever, these are currently being replaced by op ti cal storage media. 16
1. G IS hardw are O u tp u t devices include m onitors, printers and plotters. W ithin G IS two types of m o n ito r are norm ally in use; a high resolution graphical m onitor and a text m oni tor. The text m o n ito r is used for basic co m p u te r/u se r com m unication. It enables basic text o u tp u t an d is m onochrom e. The high resolution graphic m onitor p ro vides quality images. Several types o f m o n ito r are currently available which vary in screen size, resolution and the num bers o f available colours. P rinters are used for text o u tp u t and m ap plotting. The resolution and m o noch rom e n atu re o f m any prin ters m eans th at o u tp u t is often not of a very high quali ty. Some colour printers are now available th at can provide better results. H ow ev er, the best o u tp u t is provided by plotters. Plotters produce high quality line m aps. The m ajor disadvantage o f such plotters is their relatively high price. 2.1.1. D ata input devices
Principal d ata input devices are the keyboard, the digitiser and data from rem ote sensing. A lthough the keyboard is the principal com m unication device, the ability to use high resolution d a ta w ithin G IS relegates it’s role to com m unication with the C PU and elem entary d ata entry. D ata input from m aps is carried out by digit isers.
2. The digitiser
D igitising devices m ay be either scanners or c o -o rd in a te digitisers. F lat board co -o rd in a te digitisers (figure 2) are usually equipped with a pointing device which can record the c o -o rd in a te s o f any desired point upon the board. B oard digitisers are produced in a variety o f sizes b u t they usually range betw een 30 x 40 cm. and 120 x 150 cm. and are accurate between 1 and 0.1mm. The most simple digitisers dem and th at every p oint is inputted individually via the pointer to the com puter. A shape is approxim ated as a set o f individually recorded short lines form ing a p o lygon. Available softw are can alleviate the tedium of data inputting. This arduous task is made easier if the digitiser uses a stream mode. H ere the pointer follows the line and co-o rd in ates are directly transferred to the com puter. Using this tech nique we do not have to discrim inate between the individual sections of the polyg on and digitise each p a rt separately. We do however have to choose the resolution o f the digitiser. This choice will be d ependant upon the com plexity of the line and the level of accuracy we seek. H aving m ade this choice we simply inform the com puter th at we are digitising in stream m ode and then follow the line. A »stream« of co -o rd in ate pairs will than be transferred to the com puter. Recent develop m ents in digitisers allow the m achine to follow the line by itself. The operator »teaches« the digitiser to recognise the line and then need only control the proce dure and act when the m achine needs help. The digitisation o f existing m aps is very m o notonous w ork. It is lab o u r intensive and is often a source o f errors (O tawa 1987). In particularly com plex situations m odern digitisers are not particularly useful, eg when digitising topo g rap h ic m aps. An alternative solution to this problem is the use of scanners. Scanners are au to m ated systems which can read in entire m aps as an image. They do not therefore store a series o f c o -ordinates of points or objects. Scanning is very fast but the resulting image has to be edited and cleaned. At this m om ent com puters often can n o t separate distinct structures such as rivers and roads on such images.
T here are a few scanner variants. The m ajority use a light sensitive device to scan the m ap in a series o f stripes (figure 3). O ther systems exist which enable input via video cam eras. A p art from the functional differences betw een scanners and digitisers and the dif fering lab o u r input dem anded by the two techniques, there is a wide difference be tween the costs of the respective hardw are. W hilst the sm aller, sim plest digitisers cost a b o u t the sam e as a k eyboard, the best m ay cost 100 tim es m ore and the bet ter scanners 1000 tim es m ore. A lthough sim ple scanners may also be obtained at costs sim ilar to the cheaper end o f the digitiser m arket, they usually dem and better softw are support and systems organisation (Blakem an 1987).
2.1.2. Remote Sensing
Up until now we have been concerned with hardw are relating to the in put of p re-existing graphical d ata in m ap form . W hen this inform ation is not available it may be necessary to resort to rem ote sensing d ata. This inform ation is usually ob tained by aeroplanes or space satellites. G iven the general confusion ab o u t the ap plication o f such d ata w ithin archaeology it is w orth considering the potential of such d ata in some detail. Rem ote sensing covers those techniques which obtain inform ation on objects, areas o r phenom ena via devices which have no contact with the subject under study. H ere we should stress the role o f n o n -p h o to g rap h ic images acquired by sensors and not cam eras. Such images have a variety of sources although satellite technology has been a m ajor c o n trib u to r to the developm ent o f rem ote sensing techniques and now produces the m ajority o f such images. E R T S-1 (E arth R esources Technology Satellite, renam ed LA N D SA T 1 in 1975) was launched in 1972 and began to gather system atic inform ation which is now freely available. This has been follow ed by a num ber of A m erican, Soviet and French satellites. A lthough we can n o t deal w ith the m inutiae of rem ote sensing technology here (see Colwell 1983 for fu rther details), we can discuss some of the m ain characteristics o f the images provided by such equipm ent. The quality o f the image is defined by their resolution, a quality based on the pixel size and their spectral resolution. O bjects sm aller than the pixel cannot be seen on the image. LA N D SA T 1 has a nom inal pixel size o f 57 x 79 m., LA N D SA T 4 and 5’ them atic sensors provide a 30 x 30 m. resolution an d the F rench satellite SPO T has a pixel size 10 x 10 m. and 20 x 20 m. The second characteristic o f n o n -p h o to g ra p h ic sensors is their spectral resolution. Spectral reso lu tio n is defined as the capability o f sensors to register certain bands of the electrom agnetic spectrum . Such sensors usually have the capability to m oni to r not only th at p a rt o f the electrom agnetic spectrum which is visible to the naked eye but also a m uch w ider b and, and are usually capable of m onitoring the near in fra-red part of the spectrum (figure 4). 19
humanm eye —h
photography U------- H multispectral scanner N-------------------------------------- H
radar waves H >|
”*----------T--------------T------------------------------------ »--------------------/ / --------- 1---------------------- 1------------------------►
300 nm 1000 nm
4. The electrom agnetic spectrum The potential o f satellite imagery was readily seen and applied in a num ber of fields including archaeology. An early exam ple of the exploration of satellite im agery was its use by Q uann and Bevan (1977) to identify the pyram ids. This ex am ple emphasises some o f the limits o f such images - the resolution o f the image (the pixel size) is usually larger th an the average archaeological site. Satellite im ages are therefore not very useful for the direct location of archaeological sites (see Lim p 1987; Farley et al. 1990 for fu rth er discussion of this point). D espite this, these images can be o f enorm ous help. A rchaeologists can use them to define phy siographic regions, soil zones etc. and this images can then be com bined with our know ledge o f archaeological sites and their distribution to produce predictive set tlem ent m odels (Lyons and Scovill 1978,9). We can therefore define two distinct
If those archaeologists knew the truth about the satellite images there'd be ftell on.
ap p roach es to archaeological d ata. One which is site based and a second which is problem oriented. In the first ap p ro ach we are generally asking where sites are, in the second why they are there. G iven the problem s associated with image resolu tion, it is within the latter area th at satellite im agery will eventually prove the m ost useful (C uster et al. 1986). D espite this, there are som e areas in which rem ote sensing can co ntribute to site oriented research. A irborne n o n -p h o to g rap h ic rem ote sensing, in particular, has potential w ithin site oriented research because o f the higher resolution o f such techniques (Perriset and T abbagh 1981; H em ans et al. 1987). W ithin G IS, satellite images are treated as a d a ta input source. W here ca rto g ra phic in form ation is not available or is not o f high enough quality the use of such images is usually the best solution. F o r a few tho u sand U.S. D ollars an individual can purchase a m ulti band im age o f the area o f the earth they are interested in. If correctly used these images can provide an enorm ous am ount o f inform ation ab o u t the environm ent.
2.2. Software Softw are is defined as the group of instructions which enable the execution o f a certain procedure by a com puter. A com puter w ithout softw are is a dead machine. W ithin this section we do not intend to discuss com puter operating systems, this is of little value to the general reader, rath er we will discuss characteristics which are shared by m ost G IS softw are packages. G IS usually has a series o f softw are m odules which can be broken dow n into the follow ing groups: -
the the the the
d ata acquisition m odules d ata processing m odules analytical modules d ata presentation m odules
2.2.1. The data acquisition modules
The d a ta acquisition m odules enable d ata input w ithin G IS. As we have already discussed, the inform ation used in G IS comes from a series of sources and types. Satellite images may be used, different databases and a variety of m aps, some of which m ay be o f different scales and even different geographic projections. The m odule which controls com m unication with these inputs, especially with the digit iser, and tran sfo rm s im ported info rm atio n into a form which is com patible with com puter m em ory storage is therefore very im p o rtant. This data m ust be collected in a form which can be edited and labelled in order to record not only spatial posi tion but also the nam e and quality o f data points. M odules for digitising have to be user friendly and allow the o p erato r to concentrate on digitising with editing and labelling being carried out th ro u g h the com puter m onitor. D ata acquisition m odules m ust also allow the direct input o f satellite data. This is m ost often held on m agnetic tapes. The images can then be re-processed via other modules. 21
These systems m ust also be able to in p u t d ata held on o ther databases. T herefore, the G IS system m ust be able to com m unicate w ith o ther com puters and to read and write d ata in a form th at can then be inputted and supported by other special ist systems. H ere we should em phasise the im portance of integration between G IS, databases and specialist statistical packages. Careful consideration needs to be given to the integration o f G IS and databases if they are to be used effectively (F arley 1989; P arker 1989). The com m unication process does not simply include the reading and w riting o f A SC II files. The system should be able to read d ata in such a form th at no fu rth er m anipulation is needed, eg when transferring data be tween different G IS packages or the im p o rtation o f them atic m aps which are al ready stored in a digitised form . In tegration in this case m eans the ability to use specialist packages w ithout the need to exit from the GIS. 2.2.2. D ata processing modules
These m odules process d a ta p rio r to their use in specific analyses. The use of maps o f different scales or cartographic projections dem ands the ability to transform the m aps. These m odules also transform d ata from vector to raster form and vice ver sa (see section 3.1. below). They will also allow data reclassification. F o r exam ple, a m ap with a large num ber of soil classifications can be simplified into a m ap with a sm aller num ber o f soil types based on the shared possession of soil qualities de fined by the user as significant. A lternatively, a to pographic m ap can easily be redefined if we seek to isolate associations between archaeological sites and p a r ticular altitude bands. Included within these m odules are procedures for redefining spatial areas o f inter est. One such procedure involves the definition of a »window« or a »mask« which contains an area o f interest chosen from a m uch larger area. The window is a sim ple rectangular area whilst a m ask is a polygon whose size and shape defines a p articu lar area chosen for specific research needs, eg the outline of a county or state. One of the m ost im p o rtan t aspects o f processing m odules are those involving the treatm en t of satellite images. Raw satellite images have to be processed in order to get out the inform ation we need for analysis. This involves radiom etric correction to im prove the image quality, geom etric correction to com pensate for the curve of the E arth , com pensation for irregularities in the geom etry of the sensor, atm os pheric refraction etc. A fter these corrections the image then has to be placed w ith in a usable c o -o rd in a te system . A fter all this the m ost difficult p a rt is the classifi cation o f d ata held within the image (H am lin 1977). The application o f these m odules allows the useful incorporation of data acquired from a wide variety o f sources w ithin a well organised system which can then be used w ithin detailed analyses. 2.2.3. Analytical modules
A nalytical m odules allow the m anipulation o f data. The m ajority o f this w ork could, with enough time, be carried out with a sheet of paper and a handful o f co loured pencils. F o r exam ple m aps p roduced through the application o f simple 22
Boolean logic. These allow com binations o f two or m ore them atic m aps using log ical operato rs; and, or and not. Simple scalar operations including adding, sub traction, division and m ultiplication m ay also be used for sim ilar operations. M ore com plex are m odules used in the m anipulation of the D igitial Elavation M odel (D EM ). The D E M is the digital representation of continuous changes of re lief w ithin space (B urrough 1986,39). Inform ation generated from the D E M is of critical im portance within m any G IS applications and is used to produce contours and m any o th er types o f inform ation including; intervisibility, slope, profiles, w a tersheds, aspect and the concavity and convexity o f a surface (figure 5). A num ber o f these techniques are used in the case studies presented later in this m onograph and it is w orth considering some o f these m odules in slightly m ore detail.
5. Examples o f inform ation derived from the D igital Elevation Model (D EM ) Intervisibility m odules generate a them atic m ap which incorporates all areas which can be seen from a specific point. The better G IS packages allow the s ta rt ing poin t to be defined as lying above the D E M ground surface if necessary. W ith in archaeology such inform ation m ight be o f interest to individuals studying the intervisibility o f burial m ounds. Slope m aps carry inform ation on user defined slope groups. This is essential inform ation if we are studying the im pact of erosion on past land use (Sheil and C hapm an 1988). A spect, often a key variable in site placem ent, is usually defined w ithin 8, 16 o r 24 com pass segments. W atersheds are often defined as suitable archaeological study areas and can be easily provided from the D EM . Using the D E M , G IS can calculate an optim al path between two points. This is re lated to the analysis o f cost surfaces. A cost surface analysis defines points which can be reached with the sam e consum ption o f energy. If we assume a hom ogenous flat surface, points which can be reached with a sim ilar consum ption o f energy will be a sim ilar distance from the initial point. A reas of constant energy con 23
sum ption will therefore be represented by a series of concentric circles. However, if the surface is not flat steeper surfaces will limit linear m ovem ent from the initial p oint. In its sim plest form such an analysis will only be concerned with elevation, how ever a totally artificial surface could also be created using another variable, eg vegetation cover or soil types as the Z axis. The cost surface in such an exam ple could then represent m any factors which circum scribe m an ’s ability to move w ith in the environm ent. Results from the m odules listed above can then be superim posed upon such surfaces. The last two m odules described above are often used during road planning. W ithin archaeology there are clear uses for such tools in the analysis and reconstruction o f past com m unication systems, predicting the routes o f w ater channels and the construction o f hypothetical site territories, especially site catchm ents. The enorm ous am ount o f inform ation which can be derived from the D EM means th at it is often the m ost basic and im portant layer held within the GIS. F inally we should consider the role o f statistical packages within G IS. M odules w ithin such systems are usually quite sim ple and are m ostly related to the general analysis of them atic m aps, areas covered by surfaces, and the distribution of points across such surfaces etc. Com plex operations such as m ultivariate analysis are not usually available w ithin the system. It is therefore very im portant that an o u tp u t m odule is available th at allows interaction with packages th at can carry out such specialist statistical functions (Farley 1987).
2.2.4. D ata presentation modules
D ata p resentation m odules control o u tp u t devices form ing p art of the G IS. These m odules enable the display o f them atic m aps on high resolution m onitors. A part from the d ata itself we also need the ability to present additional inform ation ab o u t the m ap including; the legend, co -o rd in ates of the grid, m ap title etc. These have to be presented using different styles and sizes o f lettering and different co lours. M ultiple sim ultaneous them atic images may also be needed perhaps to pres ent different projections o f study areas, for exam ple to provide an orthogonal and perspective view from a defined point. M ost G IS ’s will therefore include one or m ore m odules for the generation o f »3 dim ensional« images. These m odules usual ly allow the generation o f a perspective projection based on the D EM . W hilst li mited analytically such images are a po p u lar form of data presentation, probably resulting from their sim ilarity to the hum an visual concept of perspective. The im age produced is fam iliar and com paratively easier to understand th an orthogonal views. D ata presentation m odules include the facility for the o u tp u t of them atic m aps o n to paper. O n the cheaper system s this usually occurs via a m onochrom atic m a trix printer. These m odels also produce prin touts of statistical analysis in graphi cal and num eric form. Better systems allow the use of plotters. The principal guide in considering these o u tp u ts is th at the larger the num ber of outputs available, the b etter the system will be. All to o often the use o f specific printers dem ands th at additional com m unication m odules have to be specially written. 24
The com plexity o f the above m odules is variable. Some are very sim ple and som e very com plex. H ow ever, the m ajority can be used on the »black box« principle. We can generally p u t d a ta in and take the results o ut w ithout having to under stand the processes which link the two. C are, though, m ust be taken with some m odules for which it is essential to un d erstan d the basic lim itations and data de m ands. If these are not und ersto o d the o u tp u t may be inadequate or totally wrong. Every G IS should com e with adequate docum entation - use it!
3. GIS DATA The d ata held w ithin G IS differs from th at held in other systems because it also holds inform ation on the spatial location and attributes of each object or point docum ented. G eographical d ata can be reduced to three basic types; point, line and area. Each o f these units can be presented along with an attrib u te and an identifying tag, a num ber or a nam e. An archaeological find w ould therefore be represented by an X or Y c o -o rd in a te and a find num ber, whilst a ro ad w ould be recorded as a string o f c o -o rd in a te pairs and its nam e. A forested area w ould be defined as a string o f c o -o rd in a te s form ing a polygon su rro u n d in g the area along with a descriptive nam e or a toponym . Each m ap defined by the sum of such fea tures is com posed o f a group o f points, lines and areas defined by their spatial po sition and their n o n -sp atial attributes (B urrough 1986,13).
6. G IS data layers 25
Topographic m aps represent an enorm ous am ount of environm ental data on re lief, com m unications, hydrology etc. If we wish to transfer this to a G IS environ m ent we m ust divide this inform ation into m ap layers containing inform ation on individual environm ental variables. O ther types of data do not always exist in the form o f topo g rap h ic m aps eg clim ate, soils, and these m ust also be stored as se p arate data layers (figure 6). How then does GIS m anipulate such potentially large num bers of d ata layers? T here are two form s of organisation used in G IS - vector and raster based systems. The potential o f the data for m anipulation depends on the choice o f data organisation and it is worth considering the characteristics of the two systems.
3.1. Vector vs. Raster GIS W ithin vector based G IS all d ata is stored as points, lines and polygons. The aim o f the polygon is to define an area by enclosing it with a continuous line. The p oint is defined as a c o -o rd in ate pair and the line and polygon as a line defined by a string of co -o rd in ate pairs. Vector systems allow very accurate docum entation o f spatial data. This inform ation is stored accurately and econom ically with re spect to m em ory needs. These characteristics have resulted in vector systems often being used as the basis o f netw ork and land inform ation systems and within high quality cartographic projects. R aster system s, how ever, represent the area o f interest as a series of cells connect ed like the squares o f a chessboard. Each cell is identified through its position w ithin the rows and colum ns o f the grid. The point in such a system is therefore represented by a single cell, the line as a string o f connecting cells and an area as a group o f adjoining cells. A d ata layer recording vegetation, for exam ple, is there fore represented as a grid within which each cell contains inform ation on the vege-
grass oak forest pine forest vineyards
7. R aster representation of vegetation data layer 26
tation present at th at po in t (figure 7). D ifficulties occur if m ore than one vegeta tion type is present within a cell. In the example presented here, the cell has been assigned to the m ajority type. R aster based inform ation is sim ple to store b u t has greater m em ory dem ands. R aster based G IS ’s are m ost suited for d a ta groups whose edges are difficult to define or have been sm oothed in some way. They are particularly suitable for the analysis o f continuous surfaces such as environm ental data. R aster system s developed from the needs o f rem ote sensing systems and are still closely related to these systems. Vector systems, however, are m ore closely linked to com p u ter aided m apping. U ntil recently the two systems were not com patible. Recent developm ents now allow m ost raster based systems to utilise vector based data, although analysis is still perform ed in raster form . We can anticipate that fu ture developm ents will cause this distinction to blur or even disappear. W hat then is the form m ost suitable for archaeological application? There is no sim ple answ er to this question. A t the regional level of analysis we are often inter ested in the relationship between the archaeology and the environm ent. The m ost significant point is, therefore, the m anner in which environm ental data is stored. In such a situation, raster system s are the preferred option. Such a choice is also suggested because o f the problem s associated with the collection and analysis of palaeo -en v iro n m en tal d ata. The uncertainties resulting from sam pling procedures and analysis caution against attem pting to provide boundaries which are m ore ac curate th an is dictated by sam pling procedure. In m aking this assertion we are not stating th a t there are no specific archaeological problem s which dem and vector
Altitude, vegetation and slope shouldn't cause too many problems. 27
analysis, there certainly are. In tra site analysis for instance may dem and the in c o rp o ra tio n o f excavated feature plans which are m ore likely to be in the form of vector maps. In considering these problem s we are faced with a fundam ental problem in all GIS analysis - at w hat level o f accuracy do we have to organise a G IS system in order to carry out o u r analysis and w hat inform ation do we wish to incorporate. Some environm ental d ata, eg geology o r soil often exists as them atic m aps and some are available in digital form . O ther key elem ents, especially the D E M , will not be available in this form . The cost o f providing such inform ation may often be p ro hibitive and alternative m ethods m ust be sought. The simplest solution here would be to input d ata m anually from a to pographic m ap where a grid of a size suitable to the nature of the investigation has been overlaid. O ther alternatives could in clude the creation o f the D EM using photogram m etric stereo pairs. Using these techniques it is possible to read in the know n height of distinctive landscape fea tures, peaks, ridges, valleys etc. and interpolate the points in between. It is also possible to use stereo satellite images and a variety of digital image processing techniques to provide the sam e inform ation (D ay and M uller 1988). The im portance o f considering the required degree of resolution can be developed fu rth er if we hypothesise a situation in which we have chosen a raster based GIS system for an archaeological project. H ere we can sim plify the problem by saying th at the data resolution equals the size o f the raster cell. We, therefore, have to de cide how large the cell should be. The cell is an indivisable unit and is therefore dep en d an t upon the accuracy o f the carto graphic m ap used in digitisation. Such m aps are usually printed with a degree o f error o f 0.2 mm. in the m ap scale. An e rro r o f plus or m inus 10 m. on a m ap with a scale o f 1:50,000 can be assum ed if the digitiser is absolutely accurate. T hem atic m aps may well be even less accurate. It is not uncom m on for geological m aps produced through geophysical techniques to be inaccurate at a level o f plus o r m inus 100 m. In such circum stances it would seem illogical to choose a cell resolution equal to several m etres, not only because the d ata is unsuitable, but also because o f the huge m em ory com m itm ent that such a decision w ould dem and. F o r instance, if we decide to use a 10 x 10 m. cell size in a study area o f 10 x 10 km. we w ould have to store 1,000,000 cells. If we use only tw enty m ap layers and each cell uses only one byte, the to tal m em ory dem and is tw enty m egabytes. An am o u n t com fortably stored, perhaps, on a PC, b u t extrem ely slow to m anipulate on a small com puter. If, alternatively, we de cided th at 100 x 100 m. cells are adeq u ate, the whole database can be stored w ith in 200,000 kbytes. This am o u n t o f d a ta can be stored and m anipulated on quite a small com puter. The resolution or cell size is a key point in G IS and deserves care ful consideration as such decisions carry im portant im plications on the costs of digitisation, hardw are used and the speed, accuracy and value of results. O ptim al cell size is not simply a question o f getting results down to two decim al places, but follows from a careful consideration o f research aims and the quality of available data. A fu rth er com plication for archaeologists is the use of m odern natural and envir o nm ental d ata w ithin G IS studies. W hilst useful in m any form s of analysis of pa28
laeo-landscapes, the availability o f large am ounts of data on the m odern envir onm ent m ay be a trap for the unw ary. In an ideal w orld each study w ould come equipped w ith its own individual p alaeo -en v iro n m en tal research program m e. U n fortunately, this situation is rare and often we have to use m odern environm ental data albeit circum scribed by our lim ited knowledge of past environm ents provided through excavation and o ther form s o f sampling.
4. GIS AND ARCHAEOLOGY D espite m any successful G IS applications in the USA (K vam m e 1989; Allen et al. 1990), there are few instances o f such w ork in E urope (G reen 1990; M adry and C rum ley 1990; W ansleeben 1988; H arris 1986). H ow ever, now th at we have consi dered som e o f the basic principles o f G IS, we m ay begin to consider w hat the technique has to offer archaeology. The first and m ost obvious point is the ability o f G IS to handle large am o u n ts o f d ata. A rchaeology has only ju st begun to fully utilise com puter based spatial analysis in ord er to regulate data and test m odels. The com plexity o f some databases, especially those involving the integration of archaeological and environm ental databases is such th at work has been painfully slow or has eventually been lim ited to the visual analysis of simple distributions of sites across landscapes. It is invidious to criticise past approaches retrospectively, however, we can, after the exam ple given in G o ran et al. 1987, consider the case of the hypothetical archaeologist »X« w ho, in 1950, had been carrying o ut survey for the past tw enty five years w ithin a valley 10 x 10 km. in area. Every single site X has fou n d has been d ocum ented and the d a ta sto red in a card file. X know s his valley well. A fter tw enty five years he has realised th at the position of his prehis toric sites depends on n atu ral factors, not just relief, but distance to w ater, soil quality, aspect and so on. He therefore started to collect data on the natu ral en vironm ent with the intention o f creating a m odel of environm ental change. This w ould then be used in conjunction with the d istrib u tio n of site by period in order to investigate the effect of the environm ent on hum an activities. X, m eaning se rious business, considers at w hat level d ata collection should take place. Given the natu re o f environm ental change he decides on a 10 x 10 m. square - a m ere 1,000,000 cells. W ho is going to collect this inform ation, where will he store it and could he finish analysing it in the finite tim e before his grant body pulls the plug on the finances? He considers the problem s again and decides th at despite the loss o f som e detail a resolution of 100 x 100 m. will be adequate. H aving m ade this decision X spends a sleepless night trying to decide which data he should collect and which m ight be im p o rtan t for sites of all periods. A ltitude, relief vegetation, slope..., all have to be considered. Tw enty d ata types are eventu ally chosen. Tw enty variables for 10,000 cells. The next m orning, pencil and paper suggests th at a fully trained team w orking for a year might finish collecting the d a ta. A fu rth er glance at the project finances convinces him th at the whole concept was a beer induced fantasy and he quickly forgets it. A few decades later and we can carry out everything that X w anted with relative ease. Satellites provide a cheap and easy vehicle for d ata acquisition, m uch of 29
Information on ccll 1282045? Yes I think we've got it here somewhere.
which has already been converted into them atic maps. H uge quantities of data can now be stored on com puters which can carry out analyses which previously took years in a fraction o f the time. V irtually all of this can now be carried out using geographic inform ation systems. One oth er vitally im portant aspect o f the developm ent of G IS is the freedom it has given archaeologists to move aw ay from the artificial confines of the archaeologi cal site and to consider of the wider aspects of settlem ent studies. In the past m uch site location analysis has proceeded along the lines o f a study o f the physical a t tributes o f the site itself. Those attrib u tes which were physically present were then judged as central to the placem ent o f the site. F o r exam ple, the distance of a site to w ater o r the am o u n t o f arable land w ithin a site catchm ent. H ow ever, we have often missed the negative side of such argum ents. We have rarely been able to handle in form ation on situations w ithout sites and a sim ilar distance to w ater or w here there is a sim ilar am o u n t, or even m ore, arable land but no site. The result has been a situation in which we are unable to judge the real value o f specific a t trib u tes to site location. O ur failure to look at the o ther side of the coin is largely the result of o u r past inability to handle the very large am ounts of inform ation dem anded by such studies (K vam m e 1985). These situations dem and th a t we eith er study a random sam ple o f p oints th ro u g hout a study area or, we w ould suggest, analyse the environm ent o f sites and non-sites through GIS. If the in troduction of G IS into archaeology is as im portant as we believe it is, how should we use the techniques practically? We have already seen that G IS should be viewed as a tool to m anipulate spatial data. A rchaeological spatial data may be 30
viewed at a num ber o f different levels (W illiam s et al. 1990). At the m acro level we m ight study the d istrib u tio n o f cultural groups o r trade netw orks across C entral E urope. Below this we are interested in the analysis o f space within a p o litic a l/so cio-econom ic b o undary or a settlem ent p a tte rn within a region. At the lowest lev el we w ould p robably like to investigate the site and the spatial analysis o f objects w ithin a site. As we have discussed already, each o f these levels dem ands a differ ent level o f d ata resolution. R esolutions o f 1km. plus will be m ore norm al when investigating cultural p henom ena and centim etres when dealing with in tra-site analysis. H ow ever, w hilst the d a ta in such studies varies, the tools used by G IS to analyse them are essentially the same. T he specific n ature o f individual problem s w ithin G IS analyses as in other m a them atical m odels, dem ands a stru ctu red approach com prising of: problem defini tion, d a ta acquisition, d ata m anipulation and report generation (Ressler 1989). The process is not linear (figure 8). E arlier phases m ay need to be reviewed in the light o f results and fu rth er d ata sought if necessary. Even the original questions may be redefined at a later date, if not with im punity then, given the nature of G IS, w ith relative ease. A situation which could not have been entertained p rio r to the developm ent o f G IS techniques.
8. Flow chart representing G IS inform ation paths G iven the flexibility o f the technique, the list o f applications is alm ost limitless. Som e o f the p erm u tatio n s o f regional analysis will be explored in the following chapters devoted to d ata from the island o f H var. H ow ever, fu rth er exam ples can be found elsewhere in the literature (Allen et al. 1990), along with applications in 31
in tra-site analysis (Gill and (P ark er 1986; A ltschul 1990). am ples indicate th at after the ogists will find it difficult to niques (Peregrine 1988).
Howes 1985), and cultural heritage m anagem ent A p art from the w idth of applications, published ex first successful experience with G IS, m any archaeol im agine serious w ork w ithout access to such tech
5. CHOOSING A GEOGRAPHIC INFORMATION SYSTEM H aving, hopefully, convinced som e o f o u r readers to apply G IS w ithin their spe cialist fields, the choice has to be m ade o f a suitable system. A num ber of p ublica tions provide reviews o f available hardw are and softw are and there is no need to repeat such detailed inform ation here (The A m erican F arm land Trust 1985; E ast m an 1988; P ark er 1989), n o r to discuss the problem s of the organisation of such systems (B urrough 1986; M eckley 1987; McRae 1989). R ather, we feel th at it w ould be o f m ore use to consider som e o f the initial problem s faced by an indi vidual or group setting up a system. The price o f G IS softw are can vary from a free public dom ain package to com m ercial systems costing tens, o r even hundreds of thousand o f U.S. D ollars. Price, however, does not guarantee th at the system is suitable for the user. A t the lower end o f the m ark et a nu m b er o f system s are available th a t can be run on P C ’s and which require basic hardw are, a sm all h ard disk and a cheap digitiser. O utput can be achieved through an ord in ary d o t m atrix printer. These systems are not com m ercially oriented and are often the p roduct of research by universities. These sys tems m ay cost as little as a few hund red U.S. D ollars and the hardw are m ay im pose severe lim itations b u t m ay still be com pared with their bigger brothers with w hom they m ay have excellent com m unications, facilitating easy exchange of in form ation for m ore com plex analysis. A larger project will, quite naturally, create greater dem ands on the G IS and con siderable th o u g h t m ust be given to the system before any purchase is m ade. A part from academ ic considerations, care m ust be taken concerning the support p ro vided by the softw are for specific hardw are configurations, the existence o f a suit able custom er su p p o rt and training service. It is often advisable to look at systems which com e from reliable com panies w orking with governm ent agencies or estab lished ed ucational in stitu tio n s, as these softw are projects are m ore likely to con tinue and develop. The o rg an isatio n o f the-hardw are is critical w ithin large p ro jects and will involve considerable expenditure. At this level you should anticipate the use of graphic w orkstations with a large storage capacity and w ith tape drives. Such a h ardw are configuration will also su p p o rt the better quality data input and o u tp u t devices.
6. GIS SOFTWARE AND HARDWARE USED IN THE CASE STUDY The pilot study presented in this m o n o g rap h was carried out using equipm ent be longing to the A rkansas A rchaeological Survey (AAS) at the U niversity of A rk an sas (Fayetteville). The AAS has been involved in the developm ent o f new analyti cal m ethods w ithin archaeology for a num ber o f years and, since 1986, has been active in the application o f G IS within archaeological research and data m anage m ent. The G IS system used by the AAS and which was m ade available for this w ork is the G eographical Resources Analysis S upport System (GRASS). G R A SS was designed as a high perform ance interactive environm ent for geogra phic d ata m anagem ent, analysis and display. It was originally created for the U.S. A rm y and was intended to be applied in land m anagem ent program s associated with m ilitary installations. Its p rim ary aim is to allow the optim al use of available training areas and ranges, to m aintain land in a m anner suitable for long term mil itary use w hilst protecting valuable n atu ral and cultural resources and accom m o d ating secondary land uses including forestry, grazing, hunting and recreation (L ozar and G o ran 1987). The origins o f G RA SS lie in the use o f raster based softw are in the analysis o f the F o rt H o o d area in Texas (W estervelt 1988). G RA SS itself, however, has only been available since 1986 and is still undergoing developm ent. D espite this the softw are has now been released into the public dom ain and it can now be obtained w ithout cost from the A rm y C orps o f Engineers, C onstru ction Engineering Research L a b o ra to ry and a num ber o f associated federal agencies. A negative side of m any o th er public dom ain softw ares is th a t they suffer from p o o r docum entation and a lack o f consistent developm ent funding, training opportunities and system sup p o rt. H ow ever, this is offset in the case o f G R A SS by the fact th a t the num ber of users w ithin the U.S. establishm ent virtually ensures continuing developm ent of the system and the fact th a t som e private com panies and universities are now dis tributin g G RA SS com m ercially and will assist with training and installation o f the system. G RA SS is a U N IX based softw are w ritten in C. It is distributed in source code and is currently running on a num ber o f different w orkstations including; Sun, C o n curren t, In tergraph, Apple M acintosh, PC386 and 486’s, HP9000, AT&T 3B2, D E C , and IBM 6000. It has recently been released in the X -W indow s environ m ent increasing its p o rtab ility to any m achine running under such an environm ent (G ardels 1988; W estervelt 1990). G R A SS is a raster based G IS which allows the user to m anipulate, analyse and display d ata, and o u tp u t data as colour images or in ta b u la r statistical form . G R A SS allows digitisation of data layers m anually through a digitising table or alternatively to input d ata in digital form at either as a D E M , digitised aerial p h o to g rap h s o r satellite d ata including SPO T or L A N D SAT. In p u tted images can be processed using a variety of filters, geo-referenced and inform ation extracted via m ultispectral classification (M adry 1989). GRASS contains m odules for the analysis o f w atersheds, drainage netw orks, visibility a n a lyses and least cost surfaces and paths. Boolean and w eighted analyses can be car 33
ried out along w ith distance m easurem ents from points, lines and polygons. Pow erful m odules for univariate statistics are also included w ithin G RASS. M odules exist allow ing G R A SS to com m unicate with other G IS packages, however, the in tegration o f G R A SS with som e specific database m anagem ent systems and sta tistical packages allows the retrieval and interactive m anipulation o f d ata from re lational databases and the perform ance o f sophisticated m ultivariate analysis (Farley 1989; P arker 1989) Several different hardw are platform s were used during the study. A C om paq 386 PC with Altec digitiser was used for d ata input whilst M asscom p and C oncurrent m achines with larger m o n ito rs and greater resolution were used for analysis. Inkjet and therm al printers provided hardcopy output. The perform ance of G RA SS on these different units was essentially the same, the only difference oc curring as a result o f the mass storage units and the processing speed. In this re spect the older M asscom p was a relatively p o or perform er. Given the resolution of the raster d ata, nearly 4,000,000 20 x 20 m. cells per data layer, the greater speed of the newer m achines was o f great value. We should put on record the fact th at we found the softw are surprisingly easy to use. Each G RA SS m odule could be ap p roached from several routes. F or the be ginner, the easiest p ath is via a series of pull dow n m enus, whilst a m ore expe rienced user can use interactive com m ands to proceed th ro u g h an analysis. In the latter p ath , w henever a m odule is initiated, a series of questions will p ro m p t for inform ation necessary for the com pletion o f the exercise. The advanced GRASS user can execute m odules via direct com m and lines. The softw are design allows each user to ad o p t the execution m ode m ost appropriate to their knowledge of the system. All in all we were m ost satisfied by the perform ance of the system and emerged with the distinct feeling th a t G R A SS was the correct choice of softw are for our p articu lar applications. H ow ever, do rem em ber, different applications require dif ferent solutions. G RA SS is sim ply one possible option am ongst available raster based G IS and image processing systems.
THE HVAR CASE STUDY 1. THE STUDY AREA The area chosen as the subject of this pilot study was the island of H var in D alm a tia, Y ugoslavia (figure 9). At the nearest p o in t the island lies only 4 km. from the m ainland. It is c. 68 km . long and now here exceeds 15 km. in w idth. The long, narrow shape o f the island is d om inated by a high m ountainous spine which is topped over the m ost p a rt by a bevelled plain at c. 300 m. but rises to 626 m. at the highest peak nam ed Sv. N ikola. The coastline is precipitous but the n o rthern central section is dom inated by the low, fertile Stari G rad plain.
y / /• ■/••••/ ;■!■!■!
/ ! /•/■ /■ /
• i• / • .*• .*■i •: •/ • .*• / • f -1• / • i •t• .• •
i /■/■ t
'A W W /