Geographic information systems in archaeological analysis: a predictive model in the detection of rural Roman villae

Journal of Archaeological Science 36 (2009) 224–235

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Journal of Archaeological Science journal homepage: http://www.elsevier.com/locate/jas

Geographic information systems in archaeological analysis: a predictive model in the detection of rural Roman villae Helena Rua* ICIST-IST-UTL, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon, Portugal

a r t i c l e i n f o

a b s t r a c t

Article history: Received 14 September 2007 Received in revised form 3 September 2008 Accepted 5 September 2008

This paper describes the experimental model that formed the basis for the author’s PhD thesis. The main goal of the work is the implementation of Geographic Information Systems (GIS) in archaeological research. A survey of the state of the art was undertaken to enable an assessment of the model to be tried out and how implementation should be undertaken. The problem encountered then, and which still persists, is that data that are sufficiently reliable for archaeological purposes are hard to come by, in digital format. Ó 2008 Elsevier Ltd. All rights reserved.

Keywords: Geographic–Archaeological Information System GisArchaeo Binary overlays Weighted sums

1. Introduction Assessing how GIS models can be used in Archaeology showed that various kinds of implementation, e.g. Cultural Resources Management (Quesada et al., 1998), Site Location and the Reconstruction of Ancient Landscapes (Stine and Decker, 1990), have been regarded as corresponding to the different phases of the research, according to the availability and processing of the data, more than a division between inductive and deductive models as they are usually classified (Dalla Bona, 1994). The option of developing an automatic research model for locating sites based on environmental data (Rua, 2004), as presented here, is partly the result of the quality of information obtained at the time. An attempt was made to overcome this initial problem by establishing a data hierarchization structure that is flexible enough to be constantly updated. This was found to be the best option, since it provides a procedural methodology that can be used in subsequent implementations. The era chosen to implement the analysis, the Roman period, is the author’s area of expertise. The building type to be analysed, villae in a rural environment, was chosen because of the need to use a construction with its own clearly defined features, detectable on a regional scale. The south of Portugal was chosen because it is an area where such constructions predominate. These choices led to the use of data covering a broad time span and buildings associated

* Tel.: þ351 218 418 349; fax: þ351 218 418 260. E-mail address: [email protected] 0305-4403/$ – see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.jas.2008.09.003

with different productions and functions, which it afterwards became important to define.1 On these grounds, the aim was to determine how buildings of this type were a pattern in the territory to which they belonged, since any appropriation of an area or a social entity remains linked to the place where it existed, even after it has vanished. So the main goal of the work was to find out which factors influenced Roman construction systems, and then to identify other sites with the same set of features, based on the characteristics dominant in the environment. Previously selected case studies were used to glean this information. Establishing these factors would both help in the organization of new campaigns and, more importantly, it would provide a warning for any urban expansion that may be planned for these zones, thereby helping to protect cultural heritage. 2. Project and research method In order to determine the pattern of occupation as proposed, we began by collecting information for selecting case studies, and

1 Villae in the rural environment are buildings erected in the Roman era and they are self-sufficient in that they secure the basic needs of their users. They are not unlike the Quintas (estates) of today. They may be agricultural, industrial or administrative, depending on whether they are basically farms, or produce garum or are engaged in mining, and the nature of the activity would influence the type of construction, the size and location of its activity. Their usage time is also important to how these structures were adapted to new demands. The economics of the Iberian Peninsula (Spain and Portugal) were based on cereal production (Europe’s granary), but this generalization does not apply to local production: horse rearing was an important source of income.

H. Rua / Journal of Archaeological Science 36 (2009) 224–235

Name

Features

Cardílio

Agricultural villa (with important spa installations)

225

2ndC- 4thC A.D. (horse raising/trading)

Torre de Palma

Agricultural villa (with spa, temple and horse breeding) 1stC- 13thC A.D. (animals raising/trading, wine and oil prodution)

Santa Vitória do Ameixial Freiria

Agricultural villa (with spa) 1stC B.C.-3rdC A.D. (fruit)

Agricultural villa (with granary and spa) 1stC- 6thC A.D. (fruit)

São Cucufate

Agricultural villa (with spa, temple and farm) 1stC-18thC A.D. (fruit)

Agricultural villa (with spa)

Pisões

1stC B.C.-4thC A.D. (fruit and animals raising/trading)

Manuel Galo

Fortified villa 1stC B.C.-2ndC A.D. (mining)

Laranjeiras

Agricultural villa 1stC-12thC A.D. (fruit)

Industrial villa

Abicada

1stC- 4thC A.D. (garum)

Agricultural villa (with spa and temple)

Milreu

1stC-10thC A.D. (fruit)

Fig. 1. Georeferencing of the classified Roman heritage and the identification of case studies.

Table 1 Subjects and covers used in the GisArchaeo model Assignment

Subject

Description

NASC ALT HID TEMP SOLO SISM RADI PRET PRED PAIS

Localization of sites of study Hydrological under-basin Limit of rectangle involving the hydrological underbasin Map of mineral Springs Altimetry on scale 1: 25.000 Hydrography on scale 1:25.000 Temperature Constitution of terrain Historical earth tremor Solar radiation Precipitation (total amount) Precipitation (number of days in the year) Landscape

14 15 16 17 18 19 20 21 22

INSO HUMI ESCO LITO ECOL BACI AQUI ACID (NAME)

Isolation Air humidity Draining Map of lithology Ecological map Main hydrological basins Underground aquifers Acidity and alkalinity of terrain Archaeological survey

23

(NAME) Satellite image

24 25 26

(NAME) Local topographic survey VIAS Roman roads FREG Parish–Mainland–Parish

27 28 29

CONC DIST CONT

Localization of the central point of each site Points Area of the under-basin containing the central point of each site Polygon Area added to hydrographic under-basin to determining the Polygon area of influence of each site List of the main explorations Points Section of the military map Lines Section of the military map Lines Medium annual values, in degrees Celsius Polygon Representative areas of dominant pedological units Polygon Account of seismic incidence since 1956 Polygon Polygon Medium annual values (kcal/cm2) of the total quantity Medium annual values (mm) of the total quantity Polygon Medium annual values of days with precipitation  1 mm Polygon Separation of the levels of information in the Map of the natural Polygon regions of the territory according to types of landscape Medium values in hours Polygon Medium values (%) of the humidity at 9 G.M.T. Polygon Annual values (mm) of the quantity of water in the hydrographic network Polygon Lithological units Polygon Ecological Zones (phyto-edaphic-climatic) Polygon Limits of the main hydrographic basins Polygon Polygon Medium productivity (m3/km2/day) pH classes in water Polygon Data given by archaeological survey of the architectural structures Polygon of the places under study Photography (infra-red false colour film) rasterized and orthorectified Raster (from: military map 1:25 000) on the scale 1:40,000 (maximum admissible error image 10 m) Utilization of data to a more approximated scale Lines Integration of published information, without local correction Lines Administrative map of Portugal (2nd edition), administrative division Polygon by Parishes, Councils and Districts Limits of Councils Polygon Limits of Districts Polygon Limits of Mainland Polygon

1 2 3

SIT BAC LIM

4 5 6 7 8 9 10 11 12 13

Council–Mainland–Council District–Mainland–District Limit of Continent

Type

226

H. Rua / Journal of Archaeological Science 36 (2009) 224–235

Fig. 2. Areas of influence and limits attributed to each site, for use in the Predictive Model. Scale standardized for comparison purposes.

every effort was made to use sites that already had a georeference. The Roman heritage was surveyed (Carta Arqueolo´gica de Portugal, 1995) so that the options from the available remains could be considered, and the southern region of Portugal was chosen. This is a zone which is sufficiently wide and relatively homogeneous from a geomorphological point of view. Although many villae have been identified through the location of building remains, those which have been excavated enough for us to be able to make an idea of their overall extent (Alarca˜o,1988a,1)dpars urbana and pars rusticadare rare.2 This is why we have tried to see if there are any similarities between these constructions by looking at other items, such as pottery and mosaics, etc., which would reveal any cultural and economic affinity in relation to the occupants, assuming that the same would be true in terms of the land. To check and validate the predictive model, 10 case studies were selected (Fig. 1).3 The number of cases selected is a compromise between all the cases found in the literature review (Alarca˜o, 1973) (Alarca˜o, 1988b: 2), with preference being given to georeferenced sites [IPAdPortuguese Institute of Archaeology. http://www.ipa. min-cultura.pt (consulted between January 1999 and October

2 The overall extent of a villa is the combination of the residential and rural parts. As there are no written documents that could show the boundaries of the property, the elements that do exist are related to theories and are based on research of the urban centre. The centuriation (Lopes, 1997) does not necessarily correspond to the limits of the property. This lack of certainty has been increasing since then, thanks to the nature of subsequent occupations in this territory. Furthermore, theoretical approximations, like establishing what could be regarded as the parcelling up of the area by Thiessen polygons, for instance, can only be implemented if the total number of structures in confined zones is known. This has yet to be done. 3 This initial modelling omitted the kinds of productiondagricultural, industrial or administrative functiondassociated with each villa in a rural setting, and this may have affected the final outcome.

2001)], and the smallest number of cases needed to be considered representative for a study with statistical inferences. We also considered the availability of data on the physical environment and how they relate to cultural characteristics, assuming that human behaviour and the use of the land is recorded locally. Furthermore, as the case studies chosen are sites which did not suffer major environmental change since the Roman occupation (though, as already mentioned, they have not been fully excavated yet), it can be anticipated that using them will help to locate other, similar, sites, i.e. ones that also correspond to zones whose environmental factors have been preserved. Based on this assumption we can thus find common patterns that help to guide and rationalize archaeological discovery in the Roman period. Efforts have therefore always been directed to finding environmental patterns that typify human behaviour (Kamermans and Wansleeben, 1999), temporarily disregarding non-typical sites or other exceptions (Altschul, 1990). Information related to the case studies was then gathered, focusing particularly on topographical and hydrographical data, and graphical evidence of architectural and environmental features. The different sites were compared by taking data from different sources that could afterwards be superimposed (Paredes, 1994). So, for data relating to the topography of the sites, digital cartography on a scale 1:25,000 was used (IgeoE; http://www.igeoe.pt/ consulted between January 1999 and October 2001). The graphics relating to the survey of architectural structures came from other sources and were processed differently. For those cases for which there was drawn/graphic information, this information was digitized: from field drawings on a 1:20 scale, because it was possible to access these data in one of the case studiesdFreiriadwhich resulted in a more rigorous approach, to converting information obtained from references relating to two study casesdMilreu and Sa˜o Cucufatedeven though the margin of error is wide for archaeological

purposes. Sufficiently flexible data could not be found for the remaining seven cases, for this model. The sites/locations were georeferenced in relation to the central point, with a view to using them in the future for obtaining other data for establishing the extent of properties, and even to develop theories for the virtual reconstruction of the archaeological site. But it became important to consider aspects concerned with standardizing graphical survey procedures and the reproduction of this information. Since there is so little information on environmental aspects suitable for archaeological purposes, parameters from the alreadyexisting GIS Data Base that could be implemented in the predictive model were used. The topics are taken from the Environmental Atlas (CNIG; http://snig.cnig.pt 4 consulted between January 1999 and May 2001). This has the advantage of being available in digital format, and the disadvantage that the scale is too large, corresponding to records which are statistically much more condensed. Table 1 shows that the information gathered was so varied that topics had to be considered both individually and in groups, and to safeguard the superimposition of information from similar scales, from the general to the particular. But having national-scale information is in keeping with the automatic research that it is hoped to implement for a wider area. To take measurements and superimpose data in relation to the topics selected, a limit had to be defined. This would simulate the extent of the rural property of the ten case studies, thereby eliminating the vagueness of the land boundaries and establishing values for each GisArchaeo indicator under consideration. The boundaries of each villa were determined by measuring the hydrological sub-basin in each site, from the central point to the nearest water line, using a map scale of 1:25,000 (Ribeiro, 1994). The area corresponding to the regularization of the geometric figure (Fig. 2) was added to the resulting polygon. This formed the basis of the work’s hypothesis and some quite promising results were obtained from the implementation of the predictive model. Differences arising from the different locations of the central point were overcome, thus compensating for any errors, omissions, and difficulties caused by the uncertainties associated with the determination of the proposed area, which was designated as the area of influence. Despite the uncertainties relating to the hypothesis formulated, which allowed us to go beyond the true extent of the pars rustica, the results obtained are interesting because they reflect areas classed as big estates, according to criteria which would define a large farm before agricultural mechanization, with dimensions perfectly compatible with footpaths typical of rural zones. Based on the pre-established conditions, ten rural properties were selected. They can be classified as being one large (Freiria), three medium (Milreu, Abicada e Piso˜es) and six small properties (Torre de Palma is in transition), and these made it possible to establish the characteristic environment values of each study case. The data of the villae were thus measured and compared and comparative tables of environmental factors were drawn up. The information was weighted to determine the indices which could be implemented in the automated research (Tables 2A and 2B). Once this had been done it was ascertained that any changes to the property’s boundaries would have little impact on the figures. In addition, the specification of the indices would have no equivalence in the automated research carried out on a wider area because of the generalized nature of the scale of the environmental data used, in digital format. As the topics under examination varied widely, overlay criteria had to be established that would be relevant to an approach to the Roman era. They were organized, as far as possible, to be related to the environmental concerns of that period: land, air, fire and

4 Currently, the same information can be found at: http://www.iambiente.pt/ atlas/est/index.jsp.

75.0 100.0 100.0 100.0 50.0 75.0 75.0 75.2 75.0 100.0

584.992 700.000 724.995 732.913 500.000 500.000 625.749 699.897 700.000 600.000

120.726 200.000 197.537 244.034 86.920 100.000 141.233 193.856 200.000 150.494

5833.907 27434.678 19967.720 6401.911 18670.072 8647.890 13995.105 5510.000 17916.822 11224.522

80.0 70.0 80.0 80.0 84.4 75.0 75.0 80.0 79.5 70.0

200.0 142.6 500.0 100.0 43.5 50.0 200.0 73.3 300.0 196.5

Several 1 1 1þSeveral 1 1 Several 1 1þ1 1

18.779 17.302 17.500 16.343 17.500 17.500 20.000 16.000 17.500 17.500

3195.04 2900.00 2788.43 3044.28 3073.84 3000.00 3125.10 3000.00 3000.00 2900.00

161.69 155.00 149.46 159.98 160.00 160.00 165.00 160.00 155.00 155.00

1867.174 350.810 355.606 3328.830 141.647 2434.739 551.161 2226.360 4185.204 1165.150

158778.8100 239555.0000 165978.4200 96511.4724 258327.0400 230000.0000 220398.4000 216170.0000 225170.0000 255763.6000

20704.7100 214765.3000 276180.8200 195510.1927 55955.8700 63803.0000 14396.2500 114500.0000 139620.0000 232890.4000

10.00 8.00 9.00 9.14 8.00 8.00 10.00 7.00 7.00 7.72 97.343 94.003 83.832 83.355 45.951 19.797 136.864 20.483 92.854 80.281

P M

Underground water resources (medium productivities in m3/km2/ day) Air humidity (medium annual values in %) Mineral water springs (distance to the nearby spring, in meters) Draining (medium annual values in mm) Precipitation, no. of days in the year (medium annual values-days)

Total precipitation (medium annual values in mm)

Table 2A Hydrologic resources

227

Abicada Amerixial Cardilio Freiria Laranjeiras M_galo Milreu Pisoes S_cucufate T_palma

Social factors Effect of sun

Temperature (annual average values in degrees Celsius) Hydrologic net (distance to the near line water, in meters)

Main hydrological basins in the study area) Hydrologic resources

Insulation (medium annual values in hours)

Solar radiation (medium annual values in kcal/cm2)

Roman roads (distance to the nearest roman, road, in meters)

Archaeological survey (localization of the central point)

Historical earth tremor (curves of maximum intensities, modified Mercalli scale)

H. Rua / Journal of Archaeological Science 36 (2009) 224–235

Table 2B Constitution of terrain Slopes (levels of inclination in percentage: cells of 2  2 m)

Aspect (medium local values in percentage: cells of 2  2 m)

0–1

1–2

2–3

3–4

4–8

8–20

20–36

>36

Flat

N

NE

E

SE

S

SW

W

NW

Terrains (totologic units)

Acidity and alkalinity of terrains (pH classes in water)

Map of lithology (typological rock complexes, geologic periods)

Ecological map (ecological zones)

Landscape (types of landscape)

Abicda

3.37

0.12

0.10

0.09

0.20

0.11

0.01

0.00

0.10

0.03

0.04

0.07

0.13

0.13

0.12

0.13

0.15

51% Exchangeterrains þ 49% Luvidi-terrains

12.23

96% Sediment þ 4% Sediment and metamorph

51% Phytoclimatic þ 47% Edapho climatic

0.23

0.23

100% Luviditerrains

11.00

100% Sediment and metamorph

100% Phytoclimatic

0.11

0.12

0.11

5.51

100% Sediment

100% Phytoclimatic

0.15

0.16

0.16

0.13

100% Exchangeterrains 82% Luviditerrains þ 18% Verti-terrains

51% Polyculture from Algarve (EuroMediterranean) þ 25% Lakes and frogs formations þ 16% Mediterraneans marshland and irrigated lands þ 8% rivers, lakes and lagoons 70% Prairie (extreme dry) þ 30% polyculture under-Mediterraneans 100% Polyculture under-Mediterraneans

Ameixial

0.17

0.16

0.13

0.08

0.18

0.28

0.01

0.00

0.05

0.03

0.04

0.03

0.04

0.07

0.14

Cardilio

0.22

0.13

0.12

0.11

0.26

0.16

0.01

0.00

0.08

0.04

0.03

0.14

0.19

0.13

Freiria

0.18

0.10

0.11

0.11

0.31

0.17

0.00

0.02

0.11

0.02

0.02

0.07

0.13

11.48

100% Phytoclimatic

100% Polyculture under-Mediterraneans

0.18

0.09

0.08

0.08

0.09

87% Lithoterrains

4.35

84% Sediment þ 3% Eruptives and vulcanics rocks 97% Sediment and metamorph

Lanranjeiras

0.21

0.02

0.02

0.03

0.08

0.31

0.02

0.00

0.10

0.07

0.07

0.15

87% Phytoclimatic

0.17

0.08

0.05

0.06

0.11

0.11

5.00

0.02

0.06

0.09

0.12

0.19

0.21

0.14

100% Lithoterrains 65% Exchange terrains þ 35% Luviditerrains þ 13% Verti-terrains

100% Sediment and metamorph 100% Sediment

100% Phytoclimatic 100% Edaphoclimatic

0.03

0.03

0.04

0.05

0.12

0.15

0.18

0.16

87% Prairie (extremely dry) þHSP13% rivers, lakes and lagoons 100% Prairie (extremely dry) 93% Polyculture from Algarve (EuroMediterraneans) þ 7% Mediterranean marshland and irrigated lands 100% Prairie (extremely dry)

M_galo

0.27

0.08

0.07

0.07

0.26

0.24

0.00

0.02

0.15

0.08

0.08

Milreu

0.22

0.12

0.10

0.08

0.22

0.22

0.00

0.00

0.07

0.02

Pisoes

0.50

0.23

0.11

0.07

0.07

0.02

0.00

0.00

0.12

S_cucufate

0.25

0.08

0.08

0.08

0.30

0.21

0.00

0.00

0.15

0.03

0.03

0.04

0.07

0.12

0.19

0.19

0.13

T_palma

0.18

0.25

0.18

0.11

0.19

0.09

0.00

0.00

0.08

0.01

0.01

0.04

0.07

0.08

0.14

0.28

0.22

11.62

50% Prairieterrains þ 37% Luviditerrains þ 13% Verti terrains 99% Exchangeterrains þ 1% Luvidi-terrains

5.33

84% Sediment and metamorph

100% Phytoclimatic

5.06

100% Phytoclimatic

83% Polyculture underMediterranean þ 17% prairie (extremely dry)

100% Luvidi terrains

5.00

57% Eruptive plutonics rocks þ 43% Sediment and metamorph 81% Sediment þ 19% Eruptive and plutonic rocks

100% Phytoclimatic

100% Prairie (extremely dry)

H. Rua / Journal of Archaeological Science 36 (2009) 224–235

waterdthe four elements of nature, ‘‘the foundation of everything’’ (Rua, 1998). But these items were organized so that the dominant factors influencing the choice of a suitable site for a rural villa could be determined. The information was studied by topic, in four groups (with a very general scope so that all the selected topics could be catalogued), in such a way that information could be superposed on each axis, and later between axes. Characteristic values could then be determined for agricultural production and water resources, or for urban occupation, thereby meeting the proposed goal (Fig. 3). The creation of this tree of values (Veiga, 1999) shows that the first three items are linked to quantitative information, where the chosen values are given by statistical treatment. The fourth concerns qualitative values which are considered in accordance with how often the topic was found in the case studies. The analysis of the information in accordance with how often it occurred in the topics established for the case studies yielded clues in successive phases of the investigation which characterize the correlation between the various items. When the index of the water resources, the management of the water and the action of the sun is related to the index of agricultural production (resulting from the make-up of the soils), this gives an indication of the rural occupation of the villa. When cross-checked with the residential occupation (the pars urbana of the villa), given by social and other factors, the probable occupation of the villa over its whole area could be worked out. Even though this first modelling did not (yet) enable the determination of a characteristic value for a villa in the countryside, it was possible to establish a hierarchy. A model was then built up that is flexible enough to consider new topics and compare values so that they can be constantly renewed. For the overlaying of the information the topics and intervals were weighted in accordance with the importance ascribed to them for the cultural period in question. They were established in terms of affinity and by direct consultation with experts in the area, so that they could be exhaustively classified as shown in Table 3. Understanding the data structure and its level of detail was the main motive for the weight given to each of these topics. The use of these admittedly generalist parameters allows us to understand the natural trend of the analytical sequence and to detail, in successive modellings, the topics shown to be most suitable for the purpose of the analysis. Ongoing comparison with any new data which becomes available in the meantime is also possible with GisArchaeo. These procedures (topic systematization in terms of the environmental concerns of the season of the research, and use of

229

weighting factors according to the measurements taken in the case studies) led to the establishment of the parameters to be used in the automatic research. The information is overlaid in two ways: by binary overlay, and by the weighted sum method. In both cases the same topics and orders of magnitude were employed. The automatic research was also implemented on the same terms throughout (mainland Portugal). 3. Systematization of overlay operations Gis ArcView version 3.1 was used to overlay information, partly because of product accessibility and also because different data formats can be combined: vector and raster. Operations were implemented on the same sort of data, after due preparation, and they were carried out in two ways: – by binary overlays, to determine the occurrence of similar indicators that might deduce potential sites; – by weighted sums, which establishes areas of equal preference for the combination of weighted factors of the considered themes.

3.1. Binary overlays In the binary overlay method, the information (a simple search of 0-or-1), hierarchized to carry out overlay operations on and between items, provided an area where an analysis was made of the aspects and slopes most favourable for the installation of a villa in a rural setting. This process identified six locations, potential archaeological sites, which satisfied the environmental variables initially selected (Fig. 4). The measurement of the environmental characteristics of archaeological sites makes it possible to identify new sites, but obtaining results implies corroborating the correlation between the model and reality, which can be done by a literature search of existing facts and by on-site confirmation. For the results obtained, the overlay used existing records: bibliographic, such as the Archaeological Map and IPA data, which confirmed the predominance of fortified villae in the region, and graphic records, such as maps and aerial imagery (Fig. 5). This resulted in good correlation of the alignments between the model and the real-world site, indicating the existence of roads (Agache,

Fig. 3. The topics used in the automated research.

Table 3 Subjects, order of magnitude and factors of balance in the GisArchaeo model Weights Subjects Intervals 10

Hydrologic resources

Weights

Effect of sun

Subjects Intervals

Hydrologic net (distance 8 to the near line water, in meters) 10 9 8 7

10 8 6 4

10 5

1: 75  x  100 days 2: 50  x  75 days and x  100 days

10 9

3

3: x  50 days

8 6 4 2 1

8

Total precipitation (medium annual value in mm).

5

10

1: 500  x  700 mm

10

7

2: x  500 mm and

8

6

700  x  1000 mm 3: 1000  x  1400 mm

6

5 3 1

4: 1400  x  2000 mm 5: 2000  x  2800 mm 6: x  2800 mm

7

Draining (median annual values in mm) 10 7 5 4 3 1

5

Social factors

Subjects Intervals Temperature (medium 8 annual values in degrees Celsius).

1: x  100 m 2:þ100 m 3:þ100 m 4:þ100 m Precipitationdn. of days 7 in the year (medium annual values-days)

9

Weights

1: x  16.0  C 2: 12.5  x  16.0  C 3: 7.5  x  12.5  C 4: x  7.5  C Insulation (medium annual values in hours)

10

1: x  3500 m 2:þ3500 m

10 5 4

3

Archaeological survey (localization of the central point)

1: 2800  x  3000 h 2: 2600  x  2800 h and x  3000 h 3: 2400  x  2600 h 4: 2200  x  2400 h 5: 2000  x  2200 h 6: 10800  x  2000 h 7: x  1800 h 2 Solar radiation (medium annual values in kcal/cm2) 1: 150  x  160 kcal/ cm2 2: 140  x  150 kcal/ cm2 and x  160 kcal/cm2 3: x  140 kcal/cm2

Subjects Intervals Roman roads (distance to the next Roman road, in meters)

10 5

Weights

4

Historical earth tremor (curves of maxinum intensities, modified Mercalli scale) 1: Intensity zone of 8

3

2: Intensity zone of 7 and Intensity zone of 9

2

3: Intensity zone of 6 and Intensity zone of 10

1

4: Intensity zone of 5

9

5: 1400  x  2200 mm 6: x  2200 mm Mineral water springs (distance to the nearby spring, in meters)

1: SE  x  NW

5 4

x ¼ Flat 2: E  x  SE 3: NW  x  E

Terrains (footologic units)

10

1: Luvidi-terrains

9

2: Exchange-terrains

8 7

3: Litho-terrains 4: Verti-terrains

6 5 4 3 2 1

5: Plane-terrains 6: River-terrain 7: Solonchaks 8: Podzois 9: Rego-terrains 10: Rankers Acidity and alkalinity of terrains (pH classes in water) 1: 5.6  x  6.5 2: 4.6  x  5.5 e 5.6  x  7.3 3: x  4.5 e 6.6  x  8.5 4: 7.4  x  8.5þ(5.6 a 6.5)

6

10 8 5 2

5

10

1: 7000  x  14000m

10

9 7

2: x  7000 3:14000  x  21000 m

9

5

4: þ7000 m

7

3

5: þ7000 m

5

10

Air humidity (medium annual values in%) 1: 75  x  80%

8

2: 70  x  75% and

8

80  x  85%

5

3: 65  x  70% and x  85%

2

4

7

4 10

1 5

4: x  65%

Slope (levels of inclination in percentagedcells of 2  2 m) 1: 0 < ¼ x  3 4 < ¼ x  20 2: 3  x  4 3: x  20 Aspect (medium local values in percentagedcells of 2  2 m)

10

8

1: 100  x  200 mm 2: 25  x  100 mm and 200  x  400 mm 3: x  25 mm and 400  x  800 mm 4: 800  x  1400 mm

Constitution of terrain

Typological rock map (typological rock complexes, geological periods) 1: Sedimentary and metamorphic formations 2: Sedimentary formations 3: Plutonic eruptive rocks 4: Volcanic eruptive rocks Ecological map (ecological zones) 1: Basal (inferior to 400 m) 2: Under mountain (400–700 m) 3: Mountain (700– 1000 m) 4: Above mountain (1000 to 1300 m) 5: Erminiano (superior to 1300 m)

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231

Table 3 (continued ) Weights Subjects Intervals 3

Hydrologic resources

10

Underground water resources medium productivity in m3/km2/day 1: 100  x  200

8

2: 250  x  300

7

3: 400  x  500

6

4: x  50

3

Main hydrologic bassins (counting) 1: 1

1

2: Several

2

Weights

Effect of sun

Subjects Intervals

Weights

Social factors

Subjects Intervals

Weights Subjects Intervals 3

Landscape (types of landscape)

10

9

7

5

4

3

2

1

1970). The field walk analysis of the most promising zones revealed that: – the results excluded zones with traces of more recent occupation, particularly Medieval-Islamic; – the type of ground was of crucial importance in the research, since zones with buildings were also excluded; – supporting rural infrastructures were detected, probably preexisting ones; – the alignments resulted from different growth patterns in local vegetation (different constitution of the surface layers of the soil). The existence of buried archaeological vestiges can only be confirmed by excavation work.

Constitution of terrain

1: Prairie (extremely dry) Polyculture underMediterraneans Polyculture from Algarve (Euro– Mediterraneans) 2: Mediterraneans irrigated and marshland Lakes and frog formations Rivers, lakes and lagoons 3:Moorland (durifolia low forest) Oak grave (cork-oak and holm-oak Metropolitans areas 4: Atlantic river (extreme irrigated land) Under-Atlantic river (dominated irrigated land) Under-Atlantic river (dominated irrigated land) 5: Coastal dunes Erminiana undermountain Sea (dense pine tree plantation in dunes) 6: Granite and shale mountains (forest lev) Granite and shale mountains (shepherd lev) Douro wine (mono culture) 7: Limy reliefs Wasteland (gorse, north undermountain) 8: Tramoutane hot land (polyculture) Half hillside northeastern Tramoutane cold land

3.2. Weighted sums method Overlaying the information using the weighted sums method corresponds to the areas being split up according to the class assigned, as shown in Fig. 6. Despite the level of generalization of the information considered, this type of analysis allows the determination of areas of equal archaeological potential and their preselection, so that they can be researched in greater detail in subsequent stages. The overlay of information defined areas of equal preference for the combination of factors of the weighted topics (demarcated by archaeological isolines). This weighting varied between 1 and 75, and for the purposes of the study the first 20% were validated, that is, values between 60 and 75. The areas which corresponded to

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H. Rua / Journal of Archaeological Science 36 (2009) 224–235

Fig. 4. Result of the automated research: six sites to prospect.

these first classifications were intersected by a cartographic division on a scale of 1:25,000, which resulted in an overlay of 529 maps. The 10% of these with the highest classification were chosen, corresponding to 53 maps (2% of the total), so that a more detailed analysis could begin. The ultimate objective will be to establish procedures to permit the analysis of all these areas. The intermediate result now achieved, in spite of relating to a much greater area than that of the first model (binary overlay), validated the same zones as being of great potential (Fig. 7). These 53 maps were examined in terms of slope and aspect, and those that revealed greater affinity in factors such as predominately southerly and easterly orientations (maps 412, 539 and 574) were examined more specifically for the Roman environmental characteristics guiding the choice of the best location for an estate (pars rustica), including soil quality for farming and size, and then the best for a house (pars urbana), meeting the technical needs of a construction of this nature (Fig. 8). This phase of the analysis can be researched on a more detailed scale. Guided by Roman environmental concerns about where to set up a villa in the countrysidedfor farmingdthe three maps

with a predominance of the most favourable factors were taken and the localities whose mixture of factors rated highest for farm produce was selected, using information on a 1:25,000 scale. As more detailed information was available, it was decided to assess these three maps in the same way. The highest values were thus limited by a square of 6  6, equivalent to a medium-sized property. Within these zones, we selected those factors which matched Roman environmental criteria for the installation of the pars urbana of a villa: a gentle slope, back to the river, if possible a view of the sea/river, and good winds (Fig. 9). Finally, the results obtained by the weighted sums method were superimposed on the existing records, either the literature references or the local researchdfield walk.5

5 An English expression commonly used in Portugal. It distinguishes the surface assessment of the land from prospecting and surveys. This is because artefacts and traces of past eras can often be found on the surface of the ground in remote, untouched areas.

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Fig. 6. Graphical equivalence of the weighted sums method.

Fig. 5. Orthophoto overlay of potential areas of site location with respective orthophoto: suggested prospecting areas.

Consulting the database of the IPA made it possible to prove the existence of many Roman remains in the zone, especially outhouses.6 In turn, the field research on the Me´rtola site disclosed the existence of buildings, constructed using the traditional local methodsdshale masonryddifficult to date, and near one of the possible locations of the Roman house a small fortified Islamic structure (Relı´quias) was found. Surface finds date back to the 5th century AD, probably corresponding to the continuation of earlier Roman occupation, a very common occurrence in the region. Onsite excavations will be needed to validate these hypotheses.

4. Comparison of the interim results With the implementation of the present GisArchaeo model it was found that the structuring and manipulation of the information available do provide indications as to the archaeological potential of a region. This is despite the fact that certain aspects of the case studies are not specified, such as whether the main product associated with each villa was rural or industrial. This would influence the villa’s social and structural organization, and determine the extent of the pars rustica, which in turn would help quantify the weighting coefficients of the topics used. In effect, the sites determined by binary overlay are those most likely to occur under the weighted sums method. This may be due to the use of the same facts, their level of generalization or the need for better specification, which might clarify the persistence of the results and class a region with such particular characteristics as being of high archaeological potential, where fortified villae predominate. Although the two methods led to similar results, it can be concluded that binary overlays are suitable for determining sitesdareas with specific environmental factors (archaeological research). In other words, it is a good method when a very specific result is sought. The weighted sums method, meanwhile, has a leading place within the hierarchy of archaeological potential

6

Which may well have served as tool-sheds.

(archaeological planning), that is, as an instrument supporting the preparation of maps of a region’s conditioning features. For benchmarking in future developments, in addition to specifying the production associated with each villa, it would be equally useful to outline research at local level using data more consistent with the archaeological scale. In particular, if this type of research is placed at the disposal of archaeological teams working under the auspices of local authorities, when properly pooled, it will help to accomplish a single, joint, enterprise. Along with the details of the information to be used in future projects, but as yet lacking suggestions as to how this might be obtained, it would be useful to compare the data with the era to which they relate: ascertaining of proxy variables (Ebert and Singer, 2004). The use of current data, based on the assumption that the environmental conditions have not greatly changed since then,7 will only reveal places where the same combination of factors has been preserved, and this will lead to unreliable results. This drawback can be overcome by fostering a more direct link between the potential of Geographic Information Systems and archaeological fieldwork.

5. Conclusions GIS is an essential tool in the management of archaeological resources. The monitoring of remains in the time and space to which they intrinsically belong, specifically through the georeferencing of structures and artefacts, the determination of classes and types within their environment, and by measuring densities and distributions of occurrences of articles found during excavations, are authoritative new ways of deducing the past. As a result, it contributes to the integrated management of cultural resources and to archaeological research into different past scenarios. The proposed objectives were achieved by establishing a set of procedures which, it is hoped, may become standard in any archaeological operation, especially at the survey phase, so that information collected in different places and at different times can be added to information considered in the GisArchaeo model. The sequence of operations implemented in the model, yielding the conclusions and achieving the goal, whether in relation to theories about archaeological occupations or the determination of local and regional archaeological potential, is both effective and sufficiently flexible to be used and optimized in works of this nature. It could also become a standard procedure, fundamental to enabling comparisons to be drawn between distinct developments. It should then be possible to base decisions on environmental impact analysis and planning studies. This is relevant both in zones of urban expansion, in order to minimize the destruction of possible archaeological remains, and to Municipal Master Plans, as a way of safeguarding land planning and use in the context of urban planning. Advantage can especially be taken of instruments provided by the National Land Management System, which establishes levels of approximation to land use planning through regional, inter-municipal and municipal plans, ranging from the macro to the most detailed scale. Being able to foresee the

7

Which can be confirmed by archaeological campaigns.

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Fig. 7. Result of the weighted values research. Determination of areas of equal preference and selection of zones of greatest accumulation based on cartographic division on a scale of 1:25,000.

integration of different archaeological operations, at local level, on a single map, helps to correct the dysfunction of plans drawn up at regional level, such as are established in the present legal system.

Fig. 8. Roman Environmental Concerns, for pars rustica and pars urbana (Columella, 1960).

But other developments that could expand the scope of these instruments beyond the limits so far established can be explored too. An example is analysis based on the recording of phenomena and the updating of this information which, for this specific topic, is reflected in the Archaeological Map, where cultural conditions are recorded in terms of historic period. With the inclusion of data collected by the Observatory of the National Territorial Information System, areas with similar patterns of environmental/cultural indicators could be identified, so that areas of high archaeological potential can be determined. This information ought to be integrated into Zoning Maps. The simultaneous consideration of both existing and potential historic data may be a more rigorous method of analysing information relating to earlier eras that would be likely to result in more objective analyses, contributing crucially to the definition of the guiding principles for controlling land use. This would then be reflected in the terms and conditions applied to the approval of projects, according to the potential of the area in which they are located, thereby guaranteeing the protection and recovery of future heritage. At local level, apart from supporting fieldwork, GisArchaeo models can be proposed for wide usage in virtual reconstruction applications (Fig. 10), integrating the collected information showing a potential for territorial occupation, and for facilitating access to archaeological information, permitting new research according to new inferences which may emerge in the meantime.

H. Rua / Journal of Archaeological Science 36 (2009) 224–235

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Fig. 10. Theoretical reconstruction of the granary in Casal da Freiria, incorporating information from the archaeological survey of architectural structures.

References

Fig. 9. Digital Terrain Model image of the areas of greater potential in Maps 412, 539 and 574 (data scale 1:25,000).

Acknowledgements The author would like to thank all her colleagues, and her two supervisors for their constant commitment and for being on hand at all stages of the work. They have shown more than the merely professional, academic interest needed to bring this work to a successful conclusion.

Agache, R., 1970. De´tection Ae´rienne de Vestiges Protohistoriques Gallo-Romains et Me´die´vaux Dans le Bassins de la Somme et ses Abords. Bulletin de la Socie´te´ de Pre´histoire, spe´cial issue, 7, Paris. Alarca˜o, J., 1973. Portugal Romano. Historia Mundi. Editorial Verbo, Lisboa. Alarca˜o, J., 1988a. O Domı´nio Romano em Portugal. Fo´rum da Histo´ria, Publicaço˜es Europa–Ame´rica, 3a Ediça˜o, Mira-Sintra, Mem Martins, pp. 107. Alarca˜o, J., 1988b. Roman Portugal. Aris & Phillips Ltd, Warminster, England. Altschul, J., 1990. Red Flag Models: the use of modeling in management contexts. In: Allen, K.M.S., Green, S.W., Zubrow, E.B.W. (Eds.), Interpreting Space: GIS and Archaeology. Taylor and Francis, London, pp. 226–238. Carta Arqueolo´gica de Portugal, 1995, Instituto Portugueˆs do Patrimo´nio Arquitecto´nico e Arqueolo´gico, Departamento de Arqueologia. Columella, L.J.M., 1960. De Re Rustica Libri XII. ex off. Roberti Stephani, Paris 1543. Dalla Bona, L., 1994. Cultural Heritage Resource Predictive Modeling Project. In: Methodological Considerations, Vol. 3. Centre For Archaeological Resource Prediction, Thunder Bay, ON. Ebert, D., Singer, M., 2004. GIS, Predictive Modelling, Erosion, Site Monitoring. Assemblage 8. On-line journal. http://www.assemblage.group.shef.ac.uk/ issue8/ebertandsinger.html. Kamermans, H., Wansleeben, M., 1999. Predictive modeling in Dutch archaeology, joining forces. In: Barcelo, J.A., Briz, I., Vila, A. (Eds.), New Techniques for Old Times: Computer Applications and Quantitative Methods in Archaeology. Tempus Reparatum, Oxford, pp. 225–229. Lopes, C., 1997. Itine´raires Lusitaniens. Trente anne´es de collaboration arche´ologique luso-française. Actes de la re´union tenue a` Bordeaux les 7 et 8 avril 1995, a` l’occasion du trentie`me anniversaire de la Mission Arche´ologique Française au Portugal. e´dite´s par Robert E´tienne et Françoise Mayet, Diffusion E. de Boccard, Paris. Paredes, E.A., 1994. Sistemas de Informaça˜o Geogra´fica. Ed. Erica, Sa˜o Paulo. Quesada, F., Gabaldo´n, M., Herrero, P.P., 1998. Equus Data Management System (SGDE): a Research Tool for the Study of the Horse in the Iberian Iron Age. Computer Applications and Quantitative Methods in Archaeology, CAA 1997, the 25th Anniversary Conference, BAR S. 750, http://www.ffil.uam.es/equus. Ribeiro, C.T., 1994. Impacte da Urbanizaça˜o e Uso do Solo nos Recursos Hı´dricos, documento po´licopiado. IST, DEC, Lisboa. Rua, H., 1998. Os Dez livros de Arquitectura de Vitru´vio. Ed. ICIST, Lisboa. Rua, H., 2004. Os Sistemas de Informaça˜o Geogra´fica na Detecça˜o de Villae no Portugal Romano: Um Modelo Preditivo [The Geographical Information Systems on the Location of Villae in Rural Roman Portugal: A Predictive Model], documento po´licopiado. IST, DEC, Lisboa. Stine, R.S., Decker, T.D., 1990. Archaeology, data integration and GIS. In: Allen, K.M.S., Green, S.W., Zubrow, E.B.W. (Eds.), Interpreting Space: GIS and Archaeology. Taylor and Francis, London, pp. 73–79. Veiga, R., 1999. Ana´lise Multi-crite´riodCase Study: Lisbon Metropolitan Region Road Network, Concepça˜o e Gesta˜o de Sistemas de Informaça˜o Geogra´fica, Vol. 3. FUNDEC, IST, Lisboa.