- Email: [email protected]
METHODOLOGICAL ISSUES IN THE DIGITAL MAPPING OF ARCHAEOLOGICAL SITES
ARCHAEOLOGY, ETHNOLOGY & ANTHROPOLOGY OF EURASIA Archaeology Ethnology & Anthropology of Eurasia 37/3 (2009) 95–102 E-mail: [email protected]
95
THE METAL AGES AND MEDIEVAL PERIOD
E.P. Krupochkin Altai State University, Pr. Lenina 61, Barnaul, 656049, Russia E-mail: [email protected]
METHODOLOGICAL ISSUES IN THE DIGITAL MAPPING OF ARCHAEOLOGICAL SITES*
The study addresses the use of the geographic information system (GIS) combined with distance probing (DP) for generating archaeological maps. The principal problem was resolved and the digital technology for mapping archaeological sites was elaborated and tested. Layered digital maps for Yustyd, Ulandryk I and II, and Sary-Gabo sites in the Altai were constructed. Digital terrain models were used for analyzing the settlement patterns of these sites and the spatial organization of the economy, and for reconstructing these systems. A digital mapping framework was prepared including the cartographic database and the identi¿cation characteristics of the sites. The usefulness of DP for solving archaeological problems is demonstrated. Algorithms of automatically decoding multispectral images for identifying, recording, and describing archaeological objects were elaborated. The results of mapping (topographic and satellite scanning) are represented in the common GIS formats – MapInfo Pro and ArcView. Keywords: Digital mapping, GIS-technologies, distant mapping in archaeology, scanning, decoding of multispectral images.
Introduction One of the major shortcomings of Siberian archaeology is the absence of a detailed archaeological map of the Altai. To elaborate it, a unied methodology based on modern digital approaches is required. The distance probing technique provides a possibility of drawing detailed archaeological maps with a high degree of accuracy and reliability. In this article, I describe the use of GIS and DP techniques for elaborating an archeological map for part of the Chuya basin. The territory in question is the southeastern Altai including the Yustyd, Ulandryk, and Barburgazy valleys (Fig. 1). The predominant landscapes are of the mountainsteppe type. The concentration of archaeological sites *Supported by the Russian Foundation for the Humanities (Project 04-01-00470a “The Ancient Nomads of the Altai: The Structure, Functioning, and Evolution of Settlement Patterns (1st Millennium BC)”).
dating back to various periods is very high in this area. The best known are burial mounds of the Scythian era. Until the 1970s, however, not a single one of them was excavated (Kubarev, 1987, 1991). Since that time, quite a number of low-status burials in the Chuya steppe have been unearthed (Kubarev, 1987, 1991, 1992). Nevertheless the knowledge of the archaeology of the southeastern Altai, of the Chuya basin in particular, is inadequate since only separate areas and burial grounds have been excavated. The geographical position of most burial grounds and separate objects such as khereksurs, ritual enclosures, cairns, etc., remains rather vague. The present study is part of a joint project by the Dendrochronological Division of the Institute of Archaeology and Ethnography SB RAS (Novosibirsk) and the Altai State University Department of Geography (Barnaul). The principal objective is to map the archaeological sites in the Chuya basin using digital techniques. The mapping process includes the pinpointing of sites, the elaboration of digital topographic plans and of
Copyright © 2009, Siberian Branch of Russian Academy of Sciences, Institute of Archaeology & Ethnography of the Siberian Branch of the Russian Academy of Sciences. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.aeae.2009.11.010
96
E.P. Krupochkin / Archaeology Ethnology & Anthropology of Eurasia 37/3 (2009) 95–102
Fig. 1. The Ulandryk valley. Photograph by E.P. Krupochkin.
Materials and methods
Fig. 2. Deer-stone. Right bank of the Yustyd. Photograph by I.Y. Slyusarenko.
digital terrain models, and comparison with previous plans of burial grounds such as Ulandryk, Yustyd, Barburgazy, etc. with a view to reconstructing the topography of these sites. While being highly prospective, geographic information systems and digital probing have not yet been used in mapping the archaeological sites of the region.
I will presently discuss the methodology of digital mapping of archaeological sites in the Yustyd valley. Excavations here began in the late 1960s. Those largest in scale were conducted by the Altai Expedition headed by N.M. Zinyakov and the Eastern Altai Division of the Northern Asiatic Expedition from the Institute of Philology and Philosophy, the USSR Academy of Sciences (Novosibirsk), headed by V.D. Kubarev (Bykova, 2002). From the late 1960s to the early 1980s, entire burial grounds and separate mounds (Yustyd I– XXII) were discovered and unearthed, and sites related to metal and ceramic production as well as deer-stones were discovered on the right bank of the Yustyd (Fig. 2). No digital archaeological map of the area, however, was available. In 2004, a Belgian team from Ghent University proposed to do the work (Goossens et al., 2006). The area to be mapped spanned the right-bank stretch of the Yustyd from Kalan spring to the main road leading to the Kokorya Village (Fig. 3). The project had three objectives: (1) elaborating and testing the methodology of archaeological site mapping with the use of the DP satellite system CORONA; (2) mapping all the Bronze Age, Iron Age, and medieval sites in the area; and (3) supplementing the UNESCO World Heritage list by archaeological sites in the southeastern Altai. The principal task of DP is to recognize the patterns in the image. This involves a decoding system based on software such as Photomod, ENVI, etc. and on geoinformation systems supporting the use of raster images (MapInfo Pro, ArcGIS, etc.) (Krupochkin, 2004). The original negatives usually show multiple
E.P. Krupochkin / Archaeology Ethnology & Anthropology of Eurasia 37/3 (2009) 95–102
а
b
97
c
d
Fig. 3. Schematic map of the Yustyd archaeological area. a – area covered by the Belgian GPS-survey in 2004; b – GPS-points; c – area studied by the Dendrochronological Division of the Institute of Archaeology and Ethnography SB RAS in 2005–2008; d – eld road.
distortions caused by various factors (fluctuations in satellite trajectory, the shifting position of sensors, etc.). Therefore satellite images cannot be used in GIS directly without preliminary photogrammetric processing and transformation (orthophototransformation, calibration, geodesic coordinate gridding, etc.). After this has been done, the resulting images made in the orthogonal projection (without distortions), can be used for largescale archaeological surveys. One of the basic stages in image transformation is gridding. To specify the spatial coordinates under eld conditions, a grid of reference GPS-points was formed (Fig. 3) and temporally stable points were selected. Three systems were used for reading coordinates: C-Nav (a highly accurate geodesic system), the twelvechannel pocket receiver Garmin (accuracy, 5–10 m), and Motorola Oncore VP (accuracy, 15–30 m). The rst system, which is by far the most expensive, guarantees the best results. Two other systems may be used in certain instances to process only the images of objects no smaller than 2 m. As the Belgian studies indicated, the best results can be achieved with photographs made from QuickBird and Ikonos satellites (their resolution is 0.6 m and 1.0 m, respectively) (Fig. 4). Ideally, however, this requires
0
50 m
Fig. 4. Topographic plan of the Yustyd XIII burial ground. Fragment of the general plan compiled by the Belgian team (Goossens et al., 2006).
98
E.P. Krupochkin / Archaeology Ethnology & Anthropology of Eurasia 37/3 (2009) 95–102
an autonomous differential GPS-system such as C-Nav (Goossens et al., 2006). In our digital mapping practice we used a more economical approach. The first stage included reconnaissance with a comprehensive archaeological and geographical description of the area (left and right banks of the Yustyd valley) in the eld. Archaeological objects were pinpointed using two GPS-navigators, the Garmin Etrex whose accuracy is within 5 m, and the Garmin Map Cx60 with an accuracy within 2 m, allowing for factors distorting the satellite images: mechanical barriers, reecting objects, radio interference, refraction, etc. As the next step, tacheometric and theodolite mapping of burial grounds was carried out. The former method is quicker as no progression is required. Surveying was conducted with a sensitive 2T5K theodolite. At the same time, a eld description of the location was made. Regrettably, southeastern Altai is not covered by the State Geodesic Network (SGN). Also, the SGN stations, set up by Soviet-era standards of the State Surveying and Mapping Administration, gradually accumulate
30 cm
0
а
d
b
e
c
9 8 7 6 5 4 3 2 1а 1
Fig. 5. Topographic plan of Yustyd XIII according to the eld survey conducted by the Dendrochronological Division of the Institute of Archaeology and Ethnography SB RAS in 2005–2008. a – unexcavated mound; b – excavated mound; c – paved memorial platform; d – reference point of the topographic grid; e – Turkic burial enclosure.
the displacement of absolute coordinates of remote points up to many dozens of meters (Postnov, Vergunov, 2003), and branch stations are even less accurate. In addition, moving across the territory was restricted by two factors: rstly, this is a frontier zone, and second, the terrain is rugged. Therefore gridding was carried out using a three-point system (station plus two additional independent extreme points situated on the diagonal of the area). Point coordinates were assessed using the GPS receiver. During laboratory processing, and for drawing digital topographic plans, the Credo DAT, MapInfo Pro, and Spatial Analyst for ArcView were employed (Fig. 5). For transmitting GPS-data and guaranteeing the compatibility of GIS-formats, all the cartographic materials were represented in the universal geocentric system WGS-84, which was elaborated in 1984 and is currently used in the Navstar radio navigation system. Most topographic maps of the Altai Republic are made in the Gauss-Krüger transverse-cylindrical projection SK-42. The reason is that among the cartographic projections most often used in GIS, WGS-84 is the closest to SK-42 in terms of the basic properties of the quasi-geoid. Apart from topographic and archaeological mapping, digital terrain models (DTM) of burial grounds and other sites were prepared and corrected* (Krupochkin, 2007). The DTM are most often organized and represented by raster data models and the TIN-based models of spatial data approximating terrains by polyhedral surfaces with height marks in the nodes of the triangular grid. Methods and algorithms of generating and processing DTM are also applicable to other physical or statistical surfaces and elds such as buried topography in archaeology and baric topography in climatology, etc. In modern geoinformatics and cartography, digital elevation models (DEM-1) and digital terrain models (DTM), derived from DEM-1 are used. In this case, DTM is the totality of morphometric characteristics of the terrain (DEM and DTM are distinct under the US DEM-2 standard (Baranov et al., 1999). To generate DTM, we used two sources of data: elevation marks in the GPS Waypoints system and calculated values of the absolute heights of reference points derived by processing the tacheometric survey data. To resolve the technical problem of modeling and visualizing DTM, we used a functional approach based on approximating a surface by a function with the *DTM is a means of digital representation of spatial objects such as surfaces and terrains as three-dimensional data – the totality of height-marks and other z-coordinate values in nodes of the regular grid for generating the height matrix, the triangulated irregular network (TIN), or a totality of horizontals and other isolines (Baranov et al., 1999).
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help of another function:
N
¦V V cZ i i
i 1
of slope of the surface, and
min
, Vi being angles
N
¦ V cZ i
min
, a functional.
i 1
The approximation makes it possible to examine the numerical values along with qualitative (morphological) and quantitative (morphometric) properties of the terrain. The problem can be solved under the condition N
that
¦ [P(X Y ) – f (x k 1
k
k
k
yk)] = min, [f(xk yk) = Z] being
the differentiating function. Because the result must be represented as a map, the coordinates in plan (X, Y) were converted to geographic coordinates (χ; φ). The conversion to the geographic coordinate system was carried out by projecting the axes of the coordinate system where the Greenwich meridian is represented as χ = X, and the equator as φ = Y. The geodesic testing of the orientation of mounds was done on the basis of information from previously excavated sites in the southeastern Altai (Ulandryk, Yustyd, Barburgazy, etc.). The essence of the test is that geographic azimuths of the timber frame axes were assessed using the measured magnetic azimuth and the magnetic declination established by means of the topographic map. Seasonality of burials can be deduced from the takeoff angle. The higher it is the larger the sunrise azimuth. Takeoff angles were measured with a theodolite within one minute for each mound. Sunrise and sunset dates for each specic year were assessed using N.I. Bykov’s method (Bykov, Bykova, 2003; Bykov et al., 2004) and the Redschift software. The comparison of the two approaches, based on the Navstar radionavigation system and GPS stations on the one hand and on the combined use of traditional survey methods and GIS-technologies and distance probing on the other, has led to the following conclusions. (1) One should consider the possibility of replacing (fully or partially) the eld methods of archaeological survey by distance methods. The feasibility of this hinges on the balance between the cost of ordering a new satellite survey of the area concerned (or receiving archive materials) and that of the eld study. (2) The important factors are technical characteristics of the surveying apparatus (sensor) and those of the satellite images. In the rst place, attention should be paid to the spatial and radiometric resolution of the image, photogrammetric processing level including orthotransformation (removal of distortions caused by the ruggedness of terrain), geometric and radiometric calibration (removal of the effects of illumination differences caused by the geometry of surveying; removal of defects on the pimages; computer-aided correction of brightness values; calculation of calibrating coefcients,
etc.), converting the photogrammetric coordinate system to the geodesic system, etc. (3) A detailed assessment of the conditions under which satellite surveys are conducted at present, and the fact that DP materials are becoming cheaper and cheaper suggest that satellite imagery can be widely used for largescale archaeological surveys. The DP and digital mapping methods are preferable for archaeological studies since they offer a wide range of possibilities: – Generating maps with fewer details than on topographic maps of comparable scale; – Ordering high-coverage photographs; – Obtaining and analyzing low-coverage (below 25 sq. km) digital images; – Pinpointing archaeological sites which are either absent on topographic or other special maps and plans or are shown with insufcient accuracy and detail; – Generating reliable historical reconstructions based on digital maps (population density fields, maps of population dynamics, “retrospective prognoses”, etc.); – Assessing the stages in prehistoric settlement and dating the burials on the basis of the astronomic and geodesic information and of the phyto-indication method; – Compiling digital archaeological plans and subject maps; – Searching and identifying new archaeological sites with the help of automatic decoding algorithms; – Spatial 3D and animation modeling of archaeological sites and of their connection with the natural and anthropogenic environment. Decoded data of the multispectral image from QuickBird, covering part of the Yustyd valley, were compared with field observations. In the following, technical principles and stages of decoding will be outlined. Based on the information received from the image, the preferable way of decoding is to use not only the RGB (red-green-blue) channels, but also the IR (infrared) channel. Firstly, the reason is that a panchromatic image with a high (2.01 m) resolution is unavailable at present. Secondly, the terrain is of the “Mongolian” type, and all the details of burial constructions including circular enclosures, khereksurs, platforms and enclosures of separate mounds, elevations, depressions, etc., are visible. Thirdly, no stereophotographs are available. The classication was based on a long-wavelength infrared image (the optical range is narrow – 0.48– 0.83 μ). The transformation of the original image from the IR range was done by the Normalized Difference Vegetation Index (NDVI). At the rst stage, the transformations by classes of the IR channel were performed with regard to Red so that NDVI = IR + Red / IR – Red. On the resulting image, light stripes correspond to higher index values, meaning more active vegetation. It should be noted that
99
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vegetation indices are relative rather than absolute. The processed image shows relative vegetation activity in various parts of the area. At the second stage, algorithms of controlled image classication were used. After a comparative analysis of the decoded data the most efcient algorithms were selected (those which provide a possibility of selecting characteristic local areas showing the position of separate mounds and their chains along the major axes – north to
Point 2
Point 9
Point 1
Point 8
Point 10
Point 7
Fig. 6. Fragment of a composite image obtained by processing the satellite image with the Gauss-Laplace algorithm.
south, southwest to northeast. The algorithms are based on the Gauss-Laplace and State Variable Filter operators intended to smooth the images by removing “noises” and accenting object borders. The image processed with the Gauss-Laplace algorithm (Fig. 6) reveals the distinct outlines of burial structures. Direct and indirect decoding indicators clearly suggest that point 7 is a stone mound with indistinct borders. Its slopes are turfed, but dark stripes show areas with bare stones or uniform ground. The dark spot in the center of the mound evidences absence of vegetation, which is supported by eld observations (the presence of several small pits, whose depth is 30 cm on average). In the southwestern part, the predominant color does not stand out against the background, suggesting that the outer contour of the mound was disturbed in that area. Indeed, during eld observations, scattered artifacts were discovered in this part of the mound (Fig. 7). The State Variable Filter algorithm also revealed certain objects on a multispectral image. Thus, the chain of Pazyryk mounds, oriented along the southeast to northwest axis is visible (Fig. 8, points 20–21). However, detecting separate archaeological objects is virtually impossible here because of the absence of outward diagnostic traits and because the mounds arranged in a chain are small (2–5 m in diameter). Other classication methods removing noises and enhancing the quality of the image did not result in any improvement. Therefore the State Variable Filter can be recommended for detecting large objects that are “invisible” for standard visual decoding methods.
Fig. 7. Mound corresponding to coordinates of point 7 of the satellite image. Photograph by E.P. Krupochkin.
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An interesting result was achieved with the hyperspectral cube (“3D Cube”) algorithm. This threedimensional algorithm performs a multispectral analysis and creates a synthetic le which may be used for both spatial and spectral analysis (because the statistical characteristics of brightness values parameters of separate pixels are available). As a result, a composite 3D image was obtained, eventually (by combining RGB channels) resulting in a pseudo-hyperspectral cube. The Build 3D Cube analysis proved far more efcient than either the 2D black-and-white image or the RGB image in the 0–255 range (color or black-and-white image with 256 gradations of grey). The resulting image (Fig. 9) reveals distinct features of archaeological objects (size, shape, shade, etc.) – the khereksurs situated on open areas near the eld roads. The size of the mounds, their planimetry and morphology (outward structure of surfaces) can be evaluated. Whereas certain khereksurs show marked elevations in the center, others ones specically No. 16 and 17, reveal depressions, resulting either from the collapse of the internal structure or from articial disruption. The outer rim, supposedly composed of large stones, too, is distinct. Further processing of images will include the use of known and new automatic decoding algorithms based on controlled classication approaches, i.e. the elaboration of learning algorithms which the program uses for an automatic search and separation of classes by pattern. In sum, DTM appears to be a highly promising method for mapping archaeological objects. Discussion and conclusions Modern digital methods were used for mapping archaeological sites in the southeastern Altai (the Chuya basin). Cartographic layers were prepared for Yustyd, Ulandryk I and II, and Sary-Gabo burial grounds. Digital terrain models were elaborated which can be useful for analyzing settlement patterns, the territorial organization of an economy, and similar reconstructions. The work was done in parallel with compiling topographic plans. In the process of digital mapping, the convention system, ways of mapping archaeological sites, and automatic decoding algorithms were elaborated. The geographic information system for the Yustyd archaeological area includes a digital database with the identication characteristics of sites. The work was based on GPS mapping and instrumental surveying of sites in 2005–2007 and on the decoding of the multispectral image of the upper reaches of the river taken from the QuickBird satellite. The data are represented in GIS-formats MapInfo Pro and ArcView. The orientation of mounds at previously excavated burial grounds in the Ulandryk and Yustyd valleys was
101
Point 19
Point 21
Point 18
Point 23 Point 20 Point 22
Fig. 8. Fragment of a composite image obtained by processing the satellite image with the State Variable Filter algorithm.
Оbject 17 Оbject 16
Fig. 9. Fragment of a composite image obtained by processing the satellite image with the Build 3D Cube method.
geodesically tested to assess the orientation properties of these sites. Under eld conditions, takeoff angles were measured with a theodolite to evaluate the seasonality of burials. To summarize, the fieldwork conducted in 2005– 2008 in the Yustyd valley led to the following results: – Archaeological and geographic properties of sites were described on the basis of reference areas; – Preliminary results of decoding the satellite image were compared with those expected; – The relative error of the algorithms was evaluated and prospects for the sophistication of decoding techniques were assessed. Given the cost of high-resolution satellite imagery which is still high, it is reasonable to use it not only for evaluating the position and size of objects, but also for generating digital terrain models and for the analysis of terrain structure, etc., which will enhance economic efciency.
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References Baranov Y.B., Berlyant A.M., Kapralov E.G., Koshkarev A.V., Serapinas B.B., Filippov Y.A. 1999 Geoinformatika. Tolkovyi slovar osnovnyh terminov. Moscow: GIS-Assotsiatsiya. URL: http://www.gisa.ru/ geoinfoslovar.html Bykov N.I., Bykova V.A. 2003 Orientatsiya pogrebennykh lyudei v kurganakh skifskoi epokhi kak istochnik istoriko-geograficheskoi informatsii. Geogra¿ya i prirodopolzovanie Sibiri, iss. 6: 214–226. Bykov N.I., Bykova V.A., Panyushkina I.P., Slyusarenko I.Y. 2004 Dendrokhronologicheskaya i geodezichesko-astronomicheskaya otsenka posledovatelnosti sooruzheniya kurganov v mogilnikakh pazyrykskoi kultury Altaya. In Kompleksnye issledovaniya drevnikh i traditsionnykh obschestv Evrazii. Barnaul: Izd. Altai. Gos. Univ., pp. 258–264. Bykova V.A. 2002 Istoriya arkheologicheskoi izuchennosti basseina Chui. Geogra¿ya i prirodopolzovanie Sibiri, iss. 5: 245–255. Goossens R., De Wulf A., Bourgeois J., Gheyle W., Willems T. 2006 Satellite imagery and archaeology: The example of CORONA in the Altai Mountains. Journal of Archaeological Science, No. 33: 745–755. Kitov A.D. 2000 Kompiuternyi analiz i sintez geoizobrazhenii. Novosibirsk: Izd. SO RAN.
Krupochkin E.P. 2004 Geoinformatsionnyi podkhod k kartografirovaniyu arkheologicheskikh pamyatnikov (na primere territorii Respubliki Altai). In Problemy arkheologii, etnografii, antropologii Sibiri i sopredelnykh territorii, vol. 10, pt. 2. Novosibirsk: Izd. IAE SO RAN, pp. 218–222. Krupochkin E.P. 2007 Opyt ispolzovaniya GIS-tekhnologii dlya resheniya zadach kartograrovaniya arkheologicheskikh pamyatnikov. In Severnaya Evraziya v antropogene: Chelovek, paleotekhnologii, geoekologiya, etnologiya i antropologiya: Materialy Vseros. konf. s mezhdunar. uchastiem, posvyascennoi 100-letiyu so dnya rozhdeniya M.M. Gerasimova, vol. 1. Irkutsk: Ottisk, pp. 312–321. Kubarev V.D. 1987 Kurgany Ulandryka. Novosibirsk: Nauka. Kubarev V.D. 1991 Kurgany Yustyda. Novosibirsk: Nauka. Kubarev V.D. 1992 Kurgany Sailiugema. Novosibirsk: Nauka. Postnov A.V., Vergunov E.G. 2003 Osnovy geodezicheskogo obespecheniya arkheologicheskikh issledovanii s primeneniem sputnikovykh navigatsionnykh priemnikov. Novosibirsk: Svet.
Received October 17, 2008.
95
THE METAL AGES AND MEDIEVAL PERIOD
E.P. Krupochkin Altai State University, Pr. Lenina 61, Barnaul, 656049, Russia E-mail: [email protected]
METHODOLOGICAL ISSUES IN THE DIGITAL MAPPING OF ARCHAEOLOGICAL SITES*
The study addresses the use of the geographic information system (GIS) combined with distance probing (DP) for generating archaeological maps. The principal problem was resolved and the digital technology for mapping archaeological sites was elaborated and tested. Layered digital maps for Yustyd, Ulandryk I and II, and Sary-Gabo sites in the Altai were constructed. Digital terrain models were used for analyzing the settlement patterns of these sites and the spatial organization of the economy, and for reconstructing these systems. A digital mapping framework was prepared including the cartographic database and the identi¿cation characteristics of the sites. The usefulness of DP for solving archaeological problems is demonstrated. Algorithms of automatically decoding multispectral images for identifying, recording, and describing archaeological objects were elaborated. The results of mapping (topographic and satellite scanning) are represented in the common GIS formats – MapInfo Pro and ArcView. Keywords: Digital mapping, GIS-technologies, distant mapping in archaeology, scanning, decoding of multispectral images.
Introduction One of the major shortcomings of Siberian archaeology is the absence of a detailed archaeological map of the Altai. To elaborate it, a unied methodology based on modern digital approaches is required. The distance probing technique provides a possibility of drawing detailed archaeological maps with a high degree of accuracy and reliability. In this article, I describe the use of GIS and DP techniques for elaborating an archeological map for part of the Chuya basin. The territory in question is the southeastern Altai including the Yustyd, Ulandryk, and Barburgazy valleys (Fig. 1). The predominant landscapes are of the mountainsteppe type. The concentration of archaeological sites *Supported by the Russian Foundation for the Humanities (Project 04-01-00470a “The Ancient Nomads of the Altai: The Structure, Functioning, and Evolution of Settlement Patterns (1st Millennium BC)”).
dating back to various periods is very high in this area. The best known are burial mounds of the Scythian era. Until the 1970s, however, not a single one of them was excavated (Kubarev, 1987, 1991). Since that time, quite a number of low-status burials in the Chuya steppe have been unearthed (Kubarev, 1987, 1991, 1992). Nevertheless the knowledge of the archaeology of the southeastern Altai, of the Chuya basin in particular, is inadequate since only separate areas and burial grounds have been excavated. The geographical position of most burial grounds and separate objects such as khereksurs, ritual enclosures, cairns, etc., remains rather vague. The present study is part of a joint project by the Dendrochronological Division of the Institute of Archaeology and Ethnography SB RAS (Novosibirsk) and the Altai State University Department of Geography (Barnaul). The principal objective is to map the archaeological sites in the Chuya basin using digital techniques. The mapping process includes the pinpointing of sites, the elaboration of digital topographic plans and of
Copyright © 2009, Siberian Branch of Russian Academy of Sciences, Institute of Archaeology & Ethnography of the Siberian Branch of the Russian Academy of Sciences. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.aeae.2009.11.010
96
E.P. Krupochkin / Archaeology Ethnology & Anthropology of Eurasia 37/3 (2009) 95–102
Fig. 1. The Ulandryk valley. Photograph by E.P. Krupochkin.
Materials and methods
Fig. 2. Deer-stone. Right bank of the Yustyd. Photograph by I.Y. Slyusarenko.
digital terrain models, and comparison with previous plans of burial grounds such as Ulandryk, Yustyd, Barburgazy, etc. with a view to reconstructing the topography of these sites. While being highly prospective, geographic information systems and digital probing have not yet been used in mapping the archaeological sites of the region.
I will presently discuss the methodology of digital mapping of archaeological sites in the Yustyd valley. Excavations here began in the late 1960s. Those largest in scale were conducted by the Altai Expedition headed by N.M. Zinyakov and the Eastern Altai Division of the Northern Asiatic Expedition from the Institute of Philology and Philosophy, the USSR Academy of Sciences (Novosibirsk), headed by V.D. Kubarev (Bykova, 2002). From the late 1960s to the early 1980s, entire burial grounds and separate mounds (Yustyd I– XXII) were discovered and unearthed, and sites related to metal and ceramic production as well as deer-stones were discovered on the right bank of the Yustyd (Fig. 2). No digital archaeological map of the area, however, was available. In 2004, a Belgian team from Ghent University proposed to do the work (Goossens et al., 2006). The area to be mapped spanned the right-bank stretch of the Yustyd from Kalan spring to the main road leading to the Kokorya Village (Fig. 3). The project had three objectives: (1) elaborating and testing the methodology of archaeological site mapping with the use of the DP satellite system CORONA; (2) mapping all the Bronze Age, Iron Age, and medieval sites in the area; and (3) supplementing the UNESCO World Heritage list by archaeological sites in the southeastern Altai. The principal task of DP is to recognize the patterns in the image. This involves a decoding system based on software such as Photomod, ENVI, etc. and on geoinformation systems supporting the use of raster images (MapInfo Pro, ArcGIS, etc.) (Krupochkin, 2004). The original negatives usually show multiple
E.P. Krupochkin / Archaeology Ethnology & Anthropology of Eurasia 37/3 (2009) 95–102
а
b
97
c
d
Fig. 3. Schematic map of the Yustyd archaeological area. a – area covered by the Belgian GPS-survey in 2004; b – GPS-points; c – area studied by the Dendrochronological Division of the Institute of Archaeology and Ethnography SB RAS in 2005–2008; d – eld road.
distortions caused by various factors (fluctuations in satellite trajectory, the shifting position of sensors, etc.). Therefore satellite images cannot be used in GIS directly without preliminary photogrammetric processing and transformation (orthophototransformation, calibration, geodesic coordinate gridding, etc.). After this has been done, the resulting images made in the orthogonal projection (without distortions), can be used for largescale archaeological surveys. One of the basic stages in image transformation is gridding. To specify the spatial coordinates under eld conditions, a grid of reference GPS-points was formed (Fig. 3) and temporally stable points were selected. Three systems were used for reading coordinates: C-Nav (a highly accurate geodesic system), the twelvechannel pocket receiver Garmin (accuracy, 5–10 m), and Motorola Oncore VP (accuracy, 15–30 m). The rst system, which is by far the most expensive, guarantees the best results. Two other systems may be used in certain instances to process only the images of objects no smaller than 2 m. As the Belgian studies indicated, the best results can be achieved with photographs made from QuickBird and Ikonos satellites (their resolution is 0.6 m and 1.0 m, respectively) (Fig. 4). Ideally, however, this requires
0
50 m
Fig. 4. Topographic plan of the Yustyd XIII burial ground. Fragment of the general plan compiled by the Belgian team (Goossens et al., 2006).
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an autonomous differential GPS-system such as C-Nav (Goossens et al., 2006). In our digital mapping practice we used a more economical approach. The first stage included reconnaissance with a comprehensive archaeological and geographical description of the area (left and right banks of the Yustyd valley) in the eld. Archaeological objects were pinpointed using two GPS-navigators, the Garmin Etrex whose accuracy is within 5 m, and the Garmin Map Cx60 with an accuracy within 2 m, allowing for factors distorting the satellite images: mechanical barriers, reecting objects, radio interference, refraction, etc. As the next step, tacheometric and theodolite mapping of burial grounds was carried out. The former method is quicker as no progression is required. Surveying was conducted with a sensitive 2T5K theodolite. At the same time, a eld description of the location was made. Regrettably, southeastern Altai is not covered by the State Geodesic Network (SGN). Also, the SGN stations, set up by Soviet-era standards of the State Surveying and Mapping Administration, gradually accumulate
30 cm
0
а
d
b
e
c
9 8 7 6 5 4 3 2 1а 1
Fig. 5. Topographic plan of Yustyd XIII according to the eld survey conducted by the Dendrochronological Division of the Institute of Archaeology and Ethnography SB RAS in 2005–2008. a – unexcavated mound; b – excavated mound; c – paved memorial platform; d – reference point of the topographic grid; e – Turkic burial enclosure.
the displacement of absolute coordinates of remote points up to many dozens of meters (Postnov, Vergunov, 2003), and branch stations are even less accurate. In addition, moving across the territory was restricted by two factors: rstly, this is a frontier zone, and second, the terrain is rugged. Therefore gridding was carried out using a three-point system (station plus two additional independent extreme points situated on the diagonal of the area). Point coordinates were assessed using the GPS receiver. During laboratory processing, and for drawing digital topographic plans, the Credo DAT, MapInfo Pro, and Spatial Analyst for ArcView were employed (Fig. 5). For transmitting GPS-data and guaranteeing the compatibility of GIS-formats, all the cartographic materials were represented in the universal geocentric system WGS-84, which was elaborated in 1984 and is currently used in the Navstar radio navigation system. Most topographic maps of the Altai Republic are made in the Gauss-Krüger transverse-cylindrical projection SK-42. The reason is that among the cartographic projections most often used in GIS, WGS-84 is the closest to SK-42 in terms of the basic properties of the quasi-geoid. Apart from topographic and archaeological mapping, digital terrain models (DTM) of burial grounds and other sites were prepared and corrected* (Krupochkin, 2007). The DTM are most often organized and represented by raster data models and the TIN-based models of spatial data approximating terrains by polyhedral surfaces with height marks in the nodes of the triangular grid. Methods and algorithms of generating and processing DTM are also applicable to other physical or statistical surfaces and elds such as buried topography in archaeology and baric topography in climatology, etc. In modern geoinformatics and cartography, digital elevation models (DEM-1) and digital terrain models (DTM), derived from DEM-1 are used. In this case, DTM is the totality of morphometric characteristics of the terrain (DEM and DTM are distinct under the US DEM-2 standard (Baranov et al., 1999). To generate DTM, we used two sources of data: elevation marks in the GPS Waypoints system and calculated values of the absolute heights of reference points derived by processing the tacheometric survey data. To resolve the technical problem of modeling and visualizing DTM, we used a functional approach based on approximating a surface by a function with the *DTM is a means of digital representation of spatial objects such as surfaces and terrains as three-dimensional data – the totality of height-marks and other z-coordinate values in nodes of the regular grid for generating the height matrix, the triangulated irregular network (TIN), or a totality of horizontals and other isolines (Baranov et al., 1999).
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help of another function:
N
¦V V cZ i i
i 1
of slope of the surface, and
min
, Vi being angles
N
¦ V cZ i
min
, a functional.
i 1
The approximation makes it possible to examine the numerical values along with qualitative (morphological) and quantitative (morphometric) properties of the terrain. The problem can be solved under the condition N
that
¦ [P(X Y ) – f (x k 1
k
k
k
yk)] = min, [f(xk yk) = Z] being
the differentiating function. Because the result must be represented as a map, the coordinates in plan (X, Y) were converted to geographic coordinates (χ; φ). The conversion to the geographic coordinate system was carried out by projecting the axes of the coordinate system where the Greenwich meridian is represented as χ = X, and the equator as φ = Y. The geodesic testing of the orientation of mounds was done on the basis of information from previously excavated sites in the southeastern Altai (Ulandryk, Yustyd, Barburgazy, etc.). The essence of the test is that geographic azimuths of the timber frame axes were assessed using the measured magnetic azimuth and the magnetic declination established by means of the topographic map. Seasonality of burials can be deduced from the takeoff angle. The higher it is the larger the sunrise azimuth. Takeoff angles were measured with a theodolite within one minute for each mound. Sunrise and sunset dates for each specic year were assessed using N.I. Bykov’s method (Bykov, Bykova, 2003; Bykov et al., 2004) and the Redschift software. The comparison of the two approaches, based on the Navstar radionavigation system and GPS stations on the one hand and on the combined use of traditional survey methods and GIS-technologies and distance probing on the other, has led to the following conclusions. (1) One should consider the possibility of replacing (fully or partially) the eld methods of archaeological survey by distance methods. The feasibility of this hinges on the balance between the cost of ordering a new satellite survey of the area concerned (or receiving archive materials) and that of the eld study. (2) The important factors are technical characteristics of the surveying apparatus (sensor) and those of the satellite images. In the rst place, attention should be paid to the spatial and radiometric resolution of the image, photogrammetric processing level including orthotransformation (removal of distortions caused by the ruggedness of terrain), geometric and radiometric calibration (removal of the effects of illumination differences caused by the geometry of surveying; removal of defects on the pimages; computer-aided correction of brightness values; calculation of calibrating coefcients,
etc.), converting the photogrammetric coordinate system to the geodesic system, etc. (3) A detailed assessment of the conditions under which satellite surveys are conducted at present, and the fact that DP materials are becoming cheaper and cheaper suggest that satellite imagery can be widely used for largescale archaeological surveys. The DP and digital mapping methods are preferable for archaeological studies since they offer a wide range of possibilities: – Generating maps with fewer details than on topographic maps of comparable scale; – Ordering high-coverage photographs; – Obtaining and analyzing low-coverage (below 25 sq. km) digital images; – Pinpointing archaeological sites which are either absent on topographic or other special maps and plans or are shown with insufcient accuracy and detail; – Generating reliable historical reconstructions based on digital maps (population density fields, maps of population dynamics, “retrospective prognoses”, etc.); – Assessing the stages in prehistoric settlement and dating the burials on the basis of the astronomic and geodesic information and of the phyto-indication method; – Compiling digital archaeological plans and subject maps; – Searching and identifying new archaeological sites with the help of automatic decoding algorithms; – Spatial 3D and animation modeling of archaeological sites and of their connection with the natural and anthropogenic environment. Decoded data of the multispectral image from QuickBird, covering part of the Yustyd valley, were compared with field observations. In the following, technical principles and stages of decoding will be outlined. Based on the information received from the image, the preferable way of decoding is to use not only the RGB (red-green-blue) channels, but also the IR (infrared) channel. Firstly, the reason is that a panchromatic image with a high (2.01 m) resolution is unavailable at present. Secondly, the terrain is of the “Mongolian” type, and all the details of burial constructions including circular enclosures, khereksurs, platforms and enclosures of separate mounds, elevations, depressions, etc., are visible. Thirdly, no stereophotographs are available. The classication was based on a long-wavelength infrared image (the optical range is narrow – 0.48– 0.83 μ). The transformation of the original image from the IR range was done by the Normalized Difference Vegetation Index (NDVI). At the rst stage, the transformations by classes of the IR channel were performed with regard to Red so that NDVI = IR + Red / IR – Red. On the resulting image, light stripes correspond to higher index values, meaning more active vegetation. It should be noted that
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vegetation indices are relative rather than absolute. The processed image shows relative vegetation activity in various parts of the area. At the second stage, algorithms of controlled image classication were used. After a comparative analysis of the decoded data the most efcient algorithms were selected (those which provide a possibility of selecting characteristic local areas showing the position of separate mounds and their chains along the major axes – north to
Point 2
Point 9
Point 1
Point 8
Point 10
Point 7
Fig. 6. Fragment of a composite image obtained by processing the satellite image with the Gauss-Laplace algorithm.
south, southwest to northeast. The algorithms are based on the Gauss-Laplace and State Variable Filter operators intended to smooth the images by removing “noises” and accenting object borders. The image processed with the Gauss-Laplace algorithm (Fig. 6) reveals the distinct outlines of burial structures. Direct and indirect decoding indicators clearly suggest that point 7 is a stone mound with indistinct borders. Its slopes are turfed, but dark stripes show areas with bare stones or uniform ground. The dark spot in the center of the mound evidences absence of vegetation, which is supported by eld observations (the presence of several small pits, whose depth is 30 cm on average). In the southwestern part, the predominant color does not stand out against the background, suggesting that the outer contour of the mound was disturbed in that area. Indeed, during eld observations, scattered artifacts were discovered in this part of the mound (Fig. 7). The State Variable Filter algorithm also revealed certain objects on a multispectral image. Thus, the chain of Pazyryk mounds, oriented along the southeast to northwest axis is visible (Fig. 8, points 20–21). However, detecting separate archaeological objects is virtually impossible here because of the absence of outward diagnostic traits and because the mounds arranged in a chain are small (2–5 m in diameter). Other classication methods removing noises and enhancing the quality of the image did not result in any improvement. Therefore the State Variable Filter can be recommended for detecting large objects that are “invisible” for standard visual decoding methods.
Fig. 7. Mound corresponding to coordinates of point 7 of the satellite image. Photograph by E.P. Krupochkin.
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An interesting result was achieved with the hyperspectral cube (“3D Cube”) algorithm. This threedimensional algorithm performs a multispectral analysis and creates a synthetic le which may be used for both spatial and spectral analysis (because the statistical characteristics of brightness values parameters of separate pixels are available). As a result, a composite 3D image was obtained, eventually (by combining RGB channels) resulting in a pseudo-hyperspectral cube. The Build 3D Cube analysis proved far more efcient than either the 2D black-and-white image or the RGB image in the 0–255 range (color or black-and-white image with 256 gradations of grey). The resulting image (Fig. 9) reveals distinct features of archaeological objects (size, shape, shade, etc.) – the khereksurs situated on open areas near the eld roads. The size of the mounds, their planimetry and morphology (outward structure of surfaces) can be evaluated. Whereas certain khereksurs show marked elevations in the center, others ones specically No. 16 and 17, reveal depressions, resulting either from the collapse of the internal structure or from articial disruption. The outer rim, supposedly composed of large stones, too, is distinct. Further processing of images will include the use of known and new automatic decoding algorithms based on controlled classication approaches, i.e. the elaboration of learning algorithms which the program uses for an automatic search and separation of classes by pattern. In sum, DTM appears to be a highly promising method for mapping archaeological objects. Discussion and conclusions Modern digital methods were used for mapping archaeological sites in the southeastern Altai (the Chuya basin). Cartographic layers were prepared for Yustyd, Ulandryk I and II, and Sary-Gabo burial grounds. Digital terrain models were elaborated which can be useful for analyzing settlement patterns, the territorial organization of an economy, and similar reconstructions. The work was done in parallel with compiling topographic plans. In the process of digital mapping, the convention system, ways of mapping archaeological sites, and automatic decoding algorithms were elaborated. The geographic information system for the Yustyd archaeological area includes a digital database with the identication characteristics of sites. The work was based on GPS mapping and instrumental surveying of sites in 2005–2007 and on the decoding of the multispectral image of the upper reaches of the river taken from the QuickBird satellite. The data are represented in GIS-formats MapInfo Pro and ArcView. The orientation of mounds at previously excavated burial grounds in the Ulandryk and Yustyd valleys was
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Point 19
Point 21
Point 18
Point 23 Point 20 Point 22
Fig. 8. Fragment of a composite image obtained by processing the satellite image with the State Variable Filter algorithm.
Оbject 17 Оbject 16
Fig. 9. Fragment of a composite image obtained by processing the satellite image with the Build 3D Cube method.
geodesically tested to assess the orientation properties of these sites. Under eld conditions, takeoff angles were measured with a theodolite to evaluate the seasonality of burials. To summarize, the fieldwork conducted in 2005– 2008 in the Yustyd valley led to the following results: – Archaeological and geographic properties of sites were described on the basis of reference areas; – Preliminary results of decoding the satellite image were compared with those expected; – The relative error of the algorithms was evaluated and prospects for the sophistication of decoding techniques were assessed. Given the cost of high-resolution satellite imagery which is still high, it is reasonable to use it not only for evaluating the position and size of objects, but also for generating digital terrain models and for the analysis of terrain structure, etc., which will enhance economic efciency.
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Received October 17, 2008.