Integracja wyników projektu na platformie GIS i jej wpływ na strategię konserwatorską

Izabela Wilczyńska, Paweł Bronisław Dąbek, Bartłomiej Ćmielewski, Jacek Kościuk

doi:10.37190/arc200213

Streszczenie

System informacji geograficznej (GIS) stał się bardzo popularnym i użytecznym narzędziem do agregowania i przetwarzania danych przestrzennych. W niniejszym artykule przedstawiono implementację danych uzyskanych podczas sezonów badań na stanowisku archeologicznym El Fuerte de Samaipata (Boliwia) oraz wyniki analizy danych na platformie GIS. Oprócz warstw tematycznych do całego systemu dodano opis sektorów i zabytków archeologicznych. Zaimplementowane warstwy są powiązane z ortoobrazami utworzonymi z naziemnego skanowania laserowego (TLS), fotogrametrii bliskiego zasięgu (w świetle wizualnym, spektralnym i podczerwonym), surowych zdjęć petroglifów, bardzo szczegółowego planu wektorowego, map ryzyka, nowego podziału przestrzennego stanowiska, warstw opisowych oraz cyfrowego model terenu (DTM) opartego na wynikach TLS. Taki system przetwarzania danych z wdrożonym DTM pozwala na analizę spływu wody deszczowej i jej oddziaływania na stanowisko archeologiczne. W związku z tym w artykule przedstawiono badania niektórych warunków hydrologicznych skały Samaipata. Badania są częścią większego projektu „Badania architektoniczne i kompleksowa dokumentacja stanowiska Samaipata (Fuerte de Samaipata/Boliwia) z Listy Światowego Dziedzictwa”. Wyniki tych prac rozpatrywane są głównie z punktu widzenia zaleceń i strategii ochrony skały. Te same aspekty mogą jednawpłynąć na przyszłe badania dotyczące chronologii i przynależności kulturowej rzeźb skalnych Samaipata.

Podgląd pełnego artykułu jest możliwy wyłącznie na większych ekranach.

2020

2(62)

DOI: 10.37190/arc200213

Introduction

The geographic information system (GIS) is an im-

portant utility that can be considered as a perfect tool to

combine the study of the spatial dimension with the study

of human activities. In archaeology, GIS platforms have

been used since the early nineties of the last century [1].

The GIS environment allows large volumes of data to be

processed, spatial queries to be made, and dierent types

of datasets to be analysed, so it is a cost eective, fast

tool. It helps to organise documentation and is ecient

and precise in aggregating spatial data, especially in archi-

tectural and archaeological conservation [2]. This helps to

provide more information on the formation of a site and

its changes in time, which allows complex spatial analysis

to be conducted.

GIS environments are able to store, manipulate, and

combine multiple types of data sets, for example, satel-

lite images, LiDAR point clouds, TLS point clouds, CAD

les, photo images, GPS coordinates, multiple types of

Izabela Wilczyńska*, Paweł Bronisław Dąbek**,

Bartłomiej Ćmielewski***, Jacek Kościuk****

Integration of project results on a GIS platform

and its impact on conservation strategies

Integracja wyników projektu na platformie GIS

i jej wpływ na strategię konserwatorską

databases (SQL, Access, Oracle), raster images, DTMs,

DSMs, and 3D models. This diversity of data allows com-

plex analyses to be conducted and dierent possible scien-

tic hypothesis to be made. There are many publications

in the form of manuals for GIS technologies [1], [3], [4].

This paper presents the development of a complex 2.5D

GIS database, which was built for the project “Archi-

tectural examination and complex documentation of Sa-

maipata (El Fuerte de Samaipata/Bolivia) site from the

World Heritage List” funded by the Polish National Sci-

ence Centre. The current condition of Samaipata rock and

its progressing erosion

is caused by several factors. One

of these is precipitation and the impact of rainwater ow-

ing down the slopes of the rock or accumulating locally.

This problem has already been addressed by earlier stud-

ies [5]–[7], but a more general approach that also encom-

passes the detailed topography of Samaipata rock seems to

be necessary. The main features of the rock surface need

to be considered, especially the areas of local depressions

and natural cracks through which water seeps into the rock.

Methods

The main objective of this research was to combine

spatial data acquisition technologies and a GIS in order to

create multidisciplinary documentation and make a quan-

Cf. W. Bartz, J. Kościuk, M. Gąsior, T. Dziedzic, Petrographic,

mineralogical, and climatic analyses, and risk maps for conservation

strategies, in the same issue of “Architectus”.

* ORCID: 0000-0002-1397-8118. Institute of Geodesy and

Geoinformatics, Wroclaw University of Environmental and Life Sciences,

e-mail: izabela.wilczynska@upwr.edu.pl

** ORCID: 0000-0003-0203-3116. Institute of Environmental

Protection and Development, Wroclaw University of Environmental and

Life Sciences.

*** ORCID: 0000-0002-1035-3905. Faculty of Architecture,

Wro cław University of Science and Technology.

**** ORCID: 0000-0003-0623-8071. Faculty of Architecture,

Wrocław University of Science and Technology.

152 Izabela Wilczyńska, Paweł Bronisław Dąbek, Bartłomiej Ćmielewski, Jacek Kościuk

titative assessment of the damage to an archaeological site

caused by nature or human activity. The study followed

the typical process of information transmission, starting

with a topographic survey and nishing with analysis from

non-specialists. These typical steps are described below.

1. Survey and documentation.

There are several techniques for documenting archae-

ological sites. The most eective method for acquiring

spatial data is remote sensing technology [8], [9]. Over

the last twenty years, the development of ground, aerial,

and space equipment and technologies have proven the

eciency of remote sensing technology for documenting

archaeological sites and heritage monuments [10]–[12].

In particular, the fast and huge progress of space technolo-

gy, including a higher spatial resolution and hyperspectral

data, has created new opportunities for better and accurate

analysis, often resulting in many unexpected discoveries

[13]–[15].

2. Specialist interpretation.

The GIS environment can be treated as the best visual-

isation platform for combining dierent types of datasets

[16], [17]. It has a very big impact on multiple analyses

performed on cultural heritage [1], [3]. In particular, the

use of such platforms as ESRI or QGIS allows complex

models derived from laser scanning [18], [19] or photo-

grammetry [20] to be combined with more traditional da-

tasets. Such data overlays allow the broader context of the

analysed material to be seen.

3. Map development.

After analysis and summarising, the GIS environment

can create thematic maps (both 2D and 3D) of a very high

quality and with high spatial resolution.

4. Community.

The rst three steps require specialist knowledge and

skills; the last step is the work with the developed material

by the community, and the creation of their own analyses

and hypotheses.

Neha Gupta and Rodolphe Devillers [21] compare GIS

environments to the classic relationship between the col-

lection of data in the archaeological eld, information

integration, and data visualization and interpretation

(Fig. 1). This comparison shows the main advantage of

GIS databases is that they can integrate dierent types of

datasets. Even if we do not have geolocations due to spe-

cic types of data (for example, text descriptions), we can

easily add our data to a larger spatial database regarding

the particular project. Additionally, if in a text description

we can highlight some specic factors, later we can per-

form spatial analysis using them.

For example, hydrological analysis allows potential

surface runo routes made by natural erosion and people

to be identied [22], [23]. The ArcMap application with

the ArcHydro extension [24] was used in the hydrological

analysis of this study. The goal was to identify potential

surface runo routes in the natural terrain and those de-

veloped by people. The basis of the study was a digital

terrain model (DTM) with a 5 cm spatial resolution. Al-

titude data from TLS (point spacing 0.01, ca. 425 million

points

, were used to create a spatial spacing 5 cm DTM

in a grid format.

When preparing data for analyses, special attention

was paid to the hydrological correctness of the numeri-

cal terrain model [25], [26]. For this purpose, the function

Fill Sinks in ArcHydro [24] was used. This corresponds

to the Fill function in the Spatial Analyst extension [27].

The purpose of Fill Sinks is to ll in drainage areas, the

occurrence of which, even on a microscale, can limit the

continuity of runo routes. The Fill Sinks function aligns

and lls places with the biggest depressions to the level of

the surrounding area.

The natural step before Fill Sinks is the use of the

DTM Reconditioning function in ArcHydro. Its task is to

stamp the watercourse beds into the DTM to indicate the

main runo routes. However, due to the characteristics of

what was being analysed, this was abandoned in the rst

step and was used only after lling the drainage areas.

Using the DTM Reconditioning function identied nat-

ural cracks, terrain cracks, and intentional human-created

runo routes. It was decided to take this step simultane-

Cf. J. Kościuk, B. Ćmielewski, M. Telesińska, A. Kubicka, 3D

terrestrial laser scanning of El Fuerte de Samaipata, in the same issue

of “Architectus”.

Fig. 1. A representation

of the cyclical relationship

between collecting data from

the archaeological field,

information integration, and data

visualization and interpretation

(adopted from [21])

 IntegrationofprojectresultsonaGISplatform / IntegracjawynikówprojektunaplatformieGIS 153

ously to take into account runo through natural forms of

the terrain, and to demonstrate the ow of water channels

made by people. Then in ArcHydro, a runo direction

model was developed (Flow Direction [28]) based on the

DTM, and a runo accumulation model (Flow Accumula-

tion [27], [28]), was created to determine the hydrological

conditions of surface runo. By using subsequent mod-

ules in the ArcHydro extension, potential runo routes

were developed. Following this, the Stream Denition

and Stream Segmentation (to develop concentrated run-

o routes) and Catchment Grid Delineation (to determine

areas from which concentrated runo occurs) functions

were used.

The algorithm conditioning the accuracy of the results

obtained was the Stream Denition function, in which the

minimum surface area of the catchment area of a single

water route was taken into account. An even surface was

assumed to be 4000 pixels, which in the case of spatial

resolution in the DTM corresponds to an even surface

of 10 m

. Ultimately, potential runo routes were deter-

mined by taking into account natural forms of terrain, in-

cluding cracks formed over the years, and forms created

by people to manage water on the site. As a result, a layer

of microcatchment areas was created.

Results and discussion

GISinfieldwork

During the survey, especially during the photogram-

metric acquisitions of images, the mobile GIS was a very

useful supporting tool. Due to very bad atmospheric con-

ditions, especially extremely strong winds, it was not pos-

sible to y a drone, so we were forced to acquire images

from the ground by placing cameras on long telescopic

sticks ca. 3–4 m above our heads. Even when we created

virtual lines of walking on the rock, sometimes it was not

possible to avoid errors and create gaps or very poor lon-

gitudinal and transverse coverage. Due to this, every day,

we estimated the positions of images in the global coordi-

nate system and checked the coverage. If we found gaps,

we exported the .shp le to a mobile phone application

(Locus Map on Android) and navigated to this area using

mobile phone GPS.

A similar workow was used when we captured the

multispectral images. This workow forced us to create

temporary layers such as:

RGB camera position reconstructed each day (Fig. 2).

2. Temporary orthoimages from each day.

3. Position of multispectral images reconstructed each

day.

Additionally, during the eld survey and inspection

by Giuseppe Oreci, we created two temporary layers to

organize the data. One was the schematic plan of the site

(Fig. 3) and the second was used to collect data from anal-

ysis of objects found on the rock such as petroglyphs, wa-

ter tanks, seats and terraces, and other important features

(Fig. 4).

Cameralwork

After eldwork seasons were completed, nal docu-

mentation was prepared. Several groups of researchers

contributed to delivering data for particular thematic lay-

ers of the GIS. They all used three basic deliverables that

were prepared in advance: DEM, orthoimages from TLS,

and RGB and multispectral orthoimages from the photo-

grammetric project. The nal product was vector (CAD)

documentation of the site as well as detailed analysis of

more specic features such as unclear (eroded) petro-

glyphs. A description of the nal layers of the whole GIS

is presented in Table 1.

The basic set of data (layers from 1–23) presented above

was further used to produce more advanced analysis that

was also incorporated into the GIS project (layers 24–32).

Some of these analyses are presented below.

Fig. 2. RGB camera position reconstructed each day. Each day is shown with a different colour (elaborated by B. Ćmielewski)

154 Izabela Wilczyńska, Paweł Bronisław Dąbek, Bartłomiej Ćmielewski, Jacek Kościuk

Hydrological analysis

Local depressions were searched for in a Bentley Micro-

Station V8i environment – contour lines were generated

every 10 cm and those that formed enclosed areas were se-

lected. The results were presented in colour scale re ect

ing the maximum depth of accumulated water (Fig. 5).

The ArcMap environment was then used to automat-

ically select depressions without a drain and to smooth

them as required for hydrological analysis, for which the

rst step was the calculation of water catchments. The

biggest ones were of 719.08 m

, and the mean area was

164.42 m

. The number of catchments calculated for the

whole site of Samaipata rock is presented in Table 2. Most

of the catchment areas were between 0 and 300 m

The next step in the hydrological analysis was to deter-

mine the water ow direction. This resulted in the creation

of a drainage line model (Fig. 6) with lines along which

rainwater will most likely ow down.

Spatial analysis

The drainage line model was used to check the inter-

action between rainwater owing down the slope of the

hill and existing natural cracks of the rock. These places

are of particular interest for conservation because of the

negative impact of rainwater inltrating the rock. All the

main cracks were selected as well as the drainage lines,

and a 25 cm buer zone was automatically created around

their intersections, thus pointing to the places with the

highest risk of rainwater inltration (Fig. 7). This anal-

ysis was further used to prepare risk maps for conserva-

tion that could cumulatively calculate degradation factors.

This kind of data is of big importance for any conservation

Fig. 3. Schematic plan of the site during the 2016 survey season

(elaborated by G. Orefici)

Fig. 4. Organisation of iconographic fieldwork data during the 2016 survey season

(elaborated by I. Wilczyńska)

 IntegrationofprojectresultsonaGISplatform / IntegracjawynikówprojektunaplatformieGIS 155

Table 1. Final GIS layers developed for the project

(elaborated by I. Wilczyńska)

Numbers Final GIS layers Short description

1 Borders of examination Range of examination area

2 Sectors New borders of sectors were determined during office work

3 Sector name Each sector was given a name

4 RGB orthoimages RGB orthoimages from the photogrammetric project of Samaipata rock

5 Multispectral orthoimages Multispectral orthoimages from the photogrammetric project of Samaipata rock

6 TLS DTM hill-shade A hill-shaded DTM developed from a filtered 3D point cloud created using TLS

7 Niches and terraces Niches and terraces carved on the rock

8 Offering holes Offering pits

9 Water channels Traces of water channels

10 Inca walls Inca architecture built on Samaipata rock

11 Inca tracing lines Lines traced on the rock by Inca builders

12 Quincha walls Walls constructed using the quincha technique

13 Colonial walls Buildings from the colonial period

14 Stairs Stairs carved in the rock

15 Wall negatives Traces of no longer existing walls

16 Post holes Holes in the rock for the construction of quincha walls

17 Contemporary constructions Contemporary platforms for visitors

18 Landscape rock The rock formation

19 Petroglyphs Location of petroglyphs

20 Petroglyph description Text describing a petroglyph based on analysis from the iconographic survey in 2016

21 RAW image of petroglyphs Images taken during the iconographic survey in 2016

22 RTI/PTM models of selected petroglyphs Models from the RTI/PTM of selected petroglyphs

23 Main natural cracks Main lines of natural cracks

24 Hydrology major lines The main watercourses

25 Hydrology minor lines The minor watercourses

26 Depressions without drains Permanent deposits of rainwater

27 Mineralogical samples Places from where the mineralogical samples were collected

28 Risk map – green vegetation The areas of green vegetation

29 Risk map – lichens The areas attacked by lichens, fungi, and algae

30 Risk map – loose lithic material Deposits of loose lithic material

31 Risk map of thermal shock The areas exposed to the risk of thermal shock during daily temperature changes

32 Risk map of wind erosion The areas exposed to abrasive wind

33 Restoration risk zones The areas of particular restoration risks

strategy. For example, juxtaposing the petroglyphs and ar-

eas where many dierent degradation factors accumulate

can show which petroglyphs are most at risk from deg-

radation (Fig. 8). In the future, using our GIS can allow

further analysis of this kind to be developed in line with

any new requirements of site management.

Conclusions

In the last decades, the use of GIS platforms for cul-

tural heritage management has become very important.

These environments make it possible to develop an eec-

tive spatial database for archaeological sites and architec-

156 Izabela Wilczyńska, Paweł Bronisław Dąbek, Bartłomiej Ćmielewski, Jacek Kościuk

Fig. 5. Depressions without drains (elaborated by J. Kościuk)

Fig. 6. Model of drainage lines (where colours of drainage lines mean the size of catchment area: red 100 m

, green 40 m

, blue 10 m

)

(elaborated by P.B. Dąbek)

Table 2. Statistic of catchments on Samaipata rock

(elaborated by P. Dąbek)

Area [m

] Number of catchments

0–50 39

51–100 13

101–200 95

201–300 33

301–400 15

401–500 3

501–600 4

601–700 1

701–800 1

tural objects. This creates a powerful toolset of analytical

instruments both for a micro and macro scale. The case of

El Fuerte de Samaipata shows how eective a GIS can be,

both in eldwork during the data collection process and

later in oce analysis.

Using GIS environments allows very quick and precise

spatial analysis to be made, which is especially important

for conservation and site management strategies at all ar-

chaeological sites.

From the point of view of conservation strategy, the

study provided very important results. Risks related

to atmospheric precipitation consist of three dierent

factors:

– Rainwater accumulated on the rock surface for a long

time causes hydrolysis and the subsequent washing-out of

the binder of the sandstone rock;

 IntegrationofprojectresultsonaGISplatform / IntegracjawynikówprojektunaplatformieGIS 157

Fig. 7. Map of rainwater infiltration risk. Buffers around intersections between the main cracks (red) in the rock and rainwater runoff lines (blue)

(elaborated by B. Ćmielewski)

Fig. 8. Juxtaposition of petroglyphs (yellow) and zones of cumulative degradation factors (blue – low, green – medium, red – high)

(elaborated by B. Ćmielewski)

– Water leaking into the rock through natural cracks

also washes out the binder, and in addition, its local eu-

sions in the lower parts of the slopes are where rock-de-

stroying lichens, mosses, and algae develop;

– Water freezing in the rock crevices, which causes the

rock to break.

In the light of the described climatic and topographic

factors, as well as the results of petrographic and miner-

alogical studies of local sandstone [13], it is necessary to

consider the problem of water retained in local depres-

sions. The other recommendation to consider is to seal the

most important natural cracks in the rock (Fig. 7).

References /Bibliografia

[1] Geographical Information Systems in Archaeology, J. Conolly,

M. Lake (eds.), Cambridge Manuals in Archaeology, Cambridge

University Press, United Kingdom, 2006.

[2] Marwick B., Hiscock P., Sullivan M., Hughes P., Landform bound-

aryeects onHoloceneforager landscapeuse inarid SouthAus-

tralia, “Journal of Archaeological Science: Reports” 2017, Vol. 19,

864–874, doi: 10.1016/j.jasrep.2017.07.004.

[3] Spatial technology and archaeology: the archaeological applica-

tions of GIS, D. Wheatley, M. Gillings (eds.), Taylor & Francis,

London–New York 2002, doi: 10.4324/9780203302392.

[4] Mehrer M., Wescott K., GIS and archaeological site location mod-

eling, CRC Press, Boca Raton 2006, doi: 10.1201/9780203563359.

[5] Avilés S., Conservazione del tempio della rocca scolpita di Samai-

pata – Santa Cruz, Bolivia (Sudamerica), Tesi di Master: Università

di Bologna – Sede di Ravenna, Facoltà di Conservazione dei Beni

Culturali, Dipartimento di Storie e Metodi per la Conservazione dei

Beni Culturali, 2002, www.stonewatch.de/media/download/sc%20

04.pdf [accessed: 20.05.2019].

[6]

Avilés S., Introduzione alla conservazione della Roccia Scolpita di Sa-

maipata, Bolivia 2011, http://www.rupestreweb.info/samaipata.html

[accessed: 20.05.2019].

158 Izabela Wilczyńska, Paweł Bronisław Dąbek, Bartłomiej Ćmielewski, Jacek Kościuk

[7] Avilés S., LaconservacióndelaRocaSagradadeSamaipata, [in:]

A. Meyers, I. Combès (comp.), El Fuerte de Samaipata. Estu dios ar-

queológicos, Biblioteca del Museo de Historia, Universidad Autó-

noma Gabriel René Moreno, Santa Cruz de la Sierra 2015, 161–170.

[8] Spreaco M.C., Franci F., Bitelli G. et al., Remote sensing tech-

niques in a multidisciplinary approach for the preservation of cul-

tural heritage sites from natural hazard: The case of Valmarecchia

Rock Slabs (RN, Italy), “Engineering Geology for Society and

Territory” 2015, Vol. 8, 317–321, doi: 10.1007/978-3-319-09408-

3_5.

[9] Cigna F., Lasaponara R., Masini N., Milillo P., Tapete D., Persistent

scatterer interferometry processing of COSMO-SkyMed StripMap

HIMAGE time series to depict deformation of the historic centre of

Rome, Italy, “Remote Sensing” 2014, Vol. 6, Iss. 12, 12593–12618,

doi: 10.3390/rs61212593.

[10] Casana J., Kantner J., Wiewel A., Cothren J., Archaeological aerial

thermography: a case study at the Chaco-era Blue J community,

NewMexico, “Journal of Archaeological Science” 2014, Vol. 45,

207–219, doi: 10.1016/j.jas.2014.02.015.

[11] Agapiou A., Alexakis D.D., Sarris A., Hadjimitsis, D.G., Evalu-

ating the potentials of sentinel-2 for archaeological perspective,

“Remote Sensing” 2014, Vol. 6, Iss. 3, 2176–2194, doi: 10.3390/

rs6032176.

[12] Chase F.A., Chase Z.D., Weishampel F.J. et al., Airborne LiDAR,

archaeology, and the ancient Maya landscape at Caracol, Belize,

“Journal of Archaeological Science” 2011, Vol. 38, Iss. 2, 387–398,

doi: 10.1016/j.jas.2010.09.018.

[13] Sarris A., Papadopoulos N., Agapiou A. et al., Integration of geo-

physical surveys, ground hyperspectral measurements, aerial and

satellite imagery for archaeological prospection of prehistoric

sites:thecase study of Vésztő-Mágor Tell, Hungary, “Journal of

Archaeological Science” 2013, Vol. 40, Iss. 3, 1454–1470, doi:

10.1016/j.jas.2012.11.001.

[14] Aqdus S.A., Drummond J., Hanson W.S., Discovering archaeo-

logical cropmarks: A hyperspectral approach, “The Internation-

al Archives of the Photogrammetry, Remote Sensing and Spatial

Information Sciences” 2008, Vol. 37, 361–365, https://www.isprs.

org/proceedings/XXXVII/congress/5_pdf/64.pdf.

[15] Cavalli R.M., Colosi F., Palombo A., Pignatti S., Poscolieri M.,

Remote hyperspectral imagery as a support to archaeological

prospection, “Journal of Cultural Heritage” 2007, Vol. 8, Iss. 3,

272–283, doi: 10.1016/j.culher.2007.03.003.

[16] Dell’Unto N., Leander A.M., Dellepiane M. et al., Digital recon-

structionandvisualizationinarchaeology:Case-studydrawnfrom

the work of the Swedish Pompeii Project, “IEEE Xplore” 2013,

621–628, doi: 10.1109/DigitalHeritage.2013.6743804.

[17] De Reu J., Plets G., Verhoeven G. et al., Towardsathree-dimen-

sional cost eective registration of the archaeological heritage,

“Journal of Archaeological Science” 2013, Vol. 40, Iss. 2, 1108–

1121, doi: 10.1016/j.jas.2012.08.040.

[18] Dell’Unto N., Landeschi G., Leander Touati A.M. et al., Experienc-

ingAncient Buildings from a 3DGISPerspective: ACase Drawn

fromtheSwedishPompeiiProject, “Journal of Archaeological Meth-

od and Theory” 2016, 23, 73–94, doi: 10.1007/s10816-014-9226-7.

[19] Landeschi G., Dell’Unto N., Lundqvist K. et al., 3D-GIS as a Plat-

form for Visual Analysis: Investigating a Pompeian House, “Journal

of Archaeological Science” 2016, Vol. 65, 103–113, doi: 10.1016/

j.jas.2015.11.002.

[20] Larsson L., Trinks I., Söderberg B. et al., Interdisciplinary archae-

ologicalprospection,excavationand3Ddocumentationexempli-

edthroughtheinvestigationofaburialattheIronAgesettlement

site of Uppåkra in Sweden, “Archaeological Prospection” 2015,

Vol. 22, Iss. 3, 143–156, doi: 10.1002/arp.1504.

[21] Gupta N., Devillers R., Geographic Visualization in Archaeology,

“Journal of Archaeological Method and Theory” 2017, Vol. 24,

852–885, doi: 10.1007/s10816-016-9298-7.

[22] Woodrow K., Lindsay J.B., Berg A.A., Evaluating DEM condition-

ingtechniques,elevationsourcedataandgridresolutionforeld-

scalehydrologicalparameterextraction, “Journal of Hydrology”

2016, Vol. 540, 1022–1029, doi: 10.1016/j.jhydrol.2016.07.018.

[23] Dąbrowska J., Dąbek P.B., Lejcuś I., A GIS based approach for the

mitigationofsurfacerunotoashallowlowlandreservoir, “Eco-

hydrology and Hydrobiology” 2018, Vol. 18, Iss. 4, 420–430, doi:

10.1016/j.ecohyd.2018.07.002.

[24] Arc Hydro: GIS for Water Resources, D.R. Maidment (eds.), Envi-

ronmental Systems Research Institute, U.S., 2002.

[25] Brubaker K.M., Myers W.L., Drohan P.J., Miller D.A., Boyer E.W.,

The use of LiDAR terrain data in characterizing surface roughness

and microtopography, “Applied and Environmental Soil Science”

2013, 1–13, doi: 10.1155/2013/891534.

[26] Thomas I.A., Jordan P., Mellander P.E. et al., Improving the iden-

ticationofhydrologicallysensitiveareasusingLiDARDEMsfor

the delineation and mitigation of critical source areas of diuse

pollution, “Science of The Total Environment” 2016, Vol. 556,

276–290, doi: 10.1016/j.scitotenv.2016.02.183.

[27] Tarboton D.G., Bras R.L., Rodriguez-Iturbe I., OntheExtractionof

ChannelNetworksfromDigitalElevationData, “Hydrological Pro-

cesses” 1991, Vol. 5, Iss. 1, 81–100, doi: 10.1002/hyp.3360050107.

[28] Jenson S.K., Domingue, J.O., Extracting Topographic Structure

from Digital Elevation Data for Geographic Information System

Analysis, “Photogrammetric Engineering and Remote Sensing”

1988, Vol. 54, No. 11, 1593–1600.

Abstract

The geographic information system (GIS) has become a very popular and useful tool to aggregate and process spatial data. In this paper, the im-

plementation of data obtained during survey seasons at the El Fuerte de Samaipata (Bolivia) archaeological site and results of data analysis on the

GIS platform are presented. In addition to the thematic layers, a description of the sectors and archaeological relics was added to the whole system.

The implemented layers are related to orthoimages created from terrestrial laser scanning (TLS) and from close range photogrammetry (in visual,

spectral, and infrared light), raw photos of petroglyphs, a highly detailed vector plan of the site, conservation risk maps, new spatial divisions, descrip-

tion layers, and a digital terrain model (DTM) based on the results of TLS. Such a system, with an implemented DTM, allows rainwater runo and

its impact on the archaeological site to be analysed. Thus, the paper presents a study on some hydrological conditions of the Samaipata rock. It is part

of the larger research project “Architectural examination and complex documentation of Samaipata (El Fuerte de Samaipata/Bolivia) site from the

World Heritage List”. The results of this study are considered mainly from the point of view of conservation recommendations and strategies. Same

aspects, however, may inuence future studies on the chronology and cultural aliation of the Samaipata rock carvings.

Key words: GIS, spatial analysis, data integration, conservation, hydrology

Acknowledgements /Podziękowania

Thepresentedworkisapartoftheresearchsponsoredbythegrantgiv-

entotheWrocławUniversityofScienceandTechnologybythePolish

National Science Centre (grant No. 2014/15/B/HS2/01108). Additio-

nally,themunicipalityofSamaipata,representedbyMayorFalvioLó-

pes Escalera, contributed to this research by providing the accommo-

dationduringthe eldwork in Juneand July 2016, aswellas in July

2017. The Ministry of Culture and Tourism of Bolivia kindly granted

all necessary permits (UDAM No. 014/2016; UDAM No. 060/2017).

The research was conducted in close cooperation with the Centrefor

Pre-Columbian Studies of the University of Warsaw in Cusco. Spe-

cialists from many other universities and research centres also joined

the project.

 IntegrationofprojectresultsonaGISplatform / IntegracjawynikówprojektunaplatformieGIS 159

Streszczenie

System informacji geogracznej (GIS) stał się bardzo popularnym i użytecznym narzędziem do agregowania i przetwarzania danych przestrzennych.

W niniejszym artykule przedstawiono implementację danych uzyskanych podczas sezonów badań na stanowisku archeologicznym El Fuerte de

Samaipata (Boliwia) oraz wyniki analizy danych na platformie GIS. Oprócz warstw tematycznych do całego systemu dodano opis sektorów i za-

bytków archeologicznych. Zaimplementowane warstwy są powiązane z ortoobrazami utworzonymi z naziemnego skanowania laserowego (TLS),

fotogrametrii bliskiego zasięgu (w świetle wizualnym, spektralnym i podczerwonym), surowych zdjęć petroglifów, bardzo szczegółowego planu

wektorowego, map ryzyka, nowego podziału przestrzennego stanowiska, warstw opisowych oraz cyfrowego model terenu (DTM) opartego na wy-

nikach TLS. Taki system przetwarzania danych z wdrożonym DTM pozwala na analizę spływu wody deszczowej i jej oddziaływania na stanowisko

archeologiczne. W związku z tym w artykule przedstawiono badania niektórych warunków hydrologicznych skały Samaipata. Badania są częścią

większego projektu „Badania architektoniczne i kompleksowa dokumentacja stanowiska Samaipata (Fuerte de Samaipata/Boliwia) z Listy Świato-

wego Dziedzictwa”. Wyniki tych prac rozpatrywane są głównie z punktu widzenia zaleceń i strategii ochrony skały. Te same aspekty mogą jednak

wpłynąć na przyszłe badania dotyczące chronologii i przynależności kulturowej rzeźb skalnych Samaipata.

Słowa kluczowe: GIS, analizy przestrzenne, integracja danych, konserwacja zabytków, hydrologia

Measuring GPS cooridates

(photo by M. Gąsior)

Pomiar współrzędnych GPS

(fot. M. Gąsior)