the archaeological site of sagalassos (turkey): exploring...

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The archaeological site of Sagalassos (Turkey): exploring the mysteries of the invisible layers using geophysical methods Lara De Giorgi 1 Giovanni Leucci 1,2 1 Institute for Archaeological and Monumental Heritage (IBAM), National Research Council (CNR), Prov. le Lecce-Monteroni, 73100 Lecce, Italy. 2 Corresponding author. Email: [email protected] Abstract. The archaeological site of Sagalassos is a very important settlement located in a magnicent mountain landscape, 7 km north from a village named A glasun (province of Burdur, south-west Turkey). Since 1990, the University of Leuven (Belgium) has carried out an interdisciplinary archaeological research program that studies >1000 years of uninterrupted human occupation in Sagalassos, concerning all historical aspects of daily life from architecture, to trade and its mechanisms and environmental conditions. The ancient Roman city is covered by layers of eroded soil that has preserved many secrets waiting to be revealed. A geophysical campaign was planned along the south facing terraces of the mountain slopes to highlight the structure of the city that remains covered in soil. Site conditions (high slope, high grass, several obstacles) and the need to investigate to depths greater than 20 m inuenced the choice of geophysical methods; we chose to use both passive and active electrical resistivity tomography. Three different areas, labelled Area 1, Area 2 and Area 3, were investigated, with results revealing information about the location, depth, size and extent of buried archaeological features. Of particular interest is the presence of: (i) a deep depression in Area 1, thought to be a clay quarry; (ii) a number of tombs related to the Byzantine period in Area 2; and (iii) defensive walls in Area 3. Key words: archaeology, ERT, Sagalassos, SP, tensor resistivity. Received 19 September 2016, accepted 3 September 2017, published online 12 October 2017 Introduction The ancient Roman city of Sagalassos is located in the south- western part of Turkey (Figure 1), ~7 km from the village A glasun. The site is located on Mount Akda g at an altitude ranging between 1450 and 1700 m above sea level (masl). The city was the rst town of Pisidia in Roman Imperial times, in the region currently known as the Turkish Lakes Region, and was an important urban centre of the Roman imperial cult. Two earthquakes devastated the city, rst in 518 BC and then again in the middle of the seventh century, the later of which destroyed the town and led to abandonment of the village. Since 1990, the University of Leuven (Belgium) has operated in this archaeological site. The studies, including numerous geophysical investigations, performed by a multidisciplinary team revealed that since the middle of the seventh century the ruins of Sagalossos have been buried by eroded soil (for more information see: www.sagalassos.be). Geophysical measurements were undertaken in the summer of 2014 to obtain information about the location, depth, size and extent of buried archaeological features. Site conditions (steep slopes, high grass, obstacles, depth of investigation) determined the electrical active and passive geophysical methods to be the most suitable geophysical methods. The active electrical method is one of the most commonly applied techniques for geophysical investigations in archaeological sites Schmidt (2013). This is due to the characteristic ability of this method to detect walls, voids, graves and other deeper man-made structures (Clark, 1980; Burger and Burger, 1992; El-Gamili et al., 1999; Drahor, 2004; Schmidt, 2013). Furthermore, this relatively low-cost method is important for identifying the relatively high electrical resistivity contrast between the structures of archaeological interest and the surrounding soil (Grifths and Barker, 1994; Negri et al., 2008). The electrical passive method, used to identify the self- potential (SP), has had a smaller development in the archaeological eld, most likely due to the fact that the subsoil phenomena related to SP phenomena are not very well known (Leucci et al., 2014). Nevertheless, the electrical passive method is one of the oldest methods used in geophysical exploration (Reynolds, 2011; Drahor et al., 1996; Drahor, 2004; De Giorgi and Leucci, 2015). Electrical active and passive measurements were performed in three areas named Area 1, Area 2 and Area 3. In Area 3, a new method of imaging resistivity data was used. The new method, described by Di Fiore et al. (2002) and Mauriello and Patella (2005), is the 3D probability tomography imaging approach based on the apparent resistivity tensor concept (Mauriello and Patella, 2005). This approach, applied for the rst time in a large area and in the archaeological eld, gave interesting results. Data acquisition, processing and interpretation Geophysical measurements were undertaken in three areas labelled respectively Area 1, Area 2 and Area 3 (Figure 2). The three study areas were chosen to specically resolve a series of unanswered archaeological questions: (1) Does the depression in the hypothesised pottery quarterof Area 1 represent a clay quarry (Degryse et al., 2003; Figure 3)? (2) Are there tombs present in the hypothesised stadiumarea between the two Byzantine churches of Area 2 (Vermoere et al., 2003)? CSIRO PUBLISHING Exploration Geophysics https://doi.org/10.1071/EG16154 Journal compilation Ó ASEG 2017 www.publish.csiro.au/journals/eg

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Page 1: The archaeological site of Sagalassos (Turkey): exploring ...depto.sismos.udec.cl/geofisica/degiorgi2017.pdf · The archaeological site of Sagalassos (Turkey): exploring the mysteries

The archaeological site of Sagalassos (Turkey): exploringthe mysteries of the invisible layers using geophysical methods

Lara De Giorgi1 Giovanni Leucci1,2

1Institute for Archaeological and Monumental Heritage (IBAM), National Research Council (CNR),Prov. le Lecce-Monteroni, 73100 Lecce, Italy.

2Corresponding author. Email: [email protected]

Abstract. The archaeological site of Sagalassos is a very important settlement located in a magnificent mountainlandscape, 7 km north from a village named A�glasun (province of Burdur, south-west Turkey). Since 1990, theUniversity of Leuven (Belgium) has carried out an interdisciplinary archaeological research program that studies>1000 years of uninterrupted human occupation in Sagalassos, concerning all historical aspects of daily life fromarchitecture, to trade and its mechanisms and environmental conditions. The ancient Roman city is covered by layers oferoded soil that has preserved many secrets waiting to be revealed. A geophysical campaign was planned along the southfacing terraces of the mountain slopes to highlight the structure of the city that remains covered in soil. Site conditions(high slope, high grass, several obstacles) and the need to investigate to depths greater than 20m influenced the choiceof geophysical methods; we chose to use both passive and active electrical resistivity tomography. Three different areas,labelled Area 1, Area 2 and Area 3, were investigated, with results revealing information about the location, depth, sizeand extent of buried archaeological features. Of particular interest is the presence of: (i) a deep depression in Area 1, thoughtto be a clay quarry; (ii) a number of tombs related to the Byzantine period in Area 2; and (iii) defensive walls in Area 3.

Key words: archaeology, ERT, Sagalassos, SP, tensor resistivity.

Received 19 September 2016, accepted 3 September 2017, published online 12 October 2017

Introduction

The ancient Roman city of Sagalassos is located in the south-western part of Turkey (Figure 1), ~7 km from the villageA�glasun. The site is located on Mount Akda�g at an altituderanging between 1450 and 1700m above sea level (masl).

The city was the first town of Pisidia in Roman Imperial times,in the region currently known as the Turkish Lakes Region,and was an important urban centre of the Roman ‘imperialcult’. Two earthquakes devastated the city, first in 518 BC andthen again in the middle of the seventh century, the later ofwhich destroyed the town and led to abandonment of the village.Since 1990, the University of Leuven (Belgium) has operatedin this archaeological site. The studies, including numerousgeophysical investigations, performed by a multidisciplinaryteam revealed that since the middle of the seventh century theruins of Sagalossos have been buried by eroded soil (for moreinformation see: www.sagalassos.be).

Geophysical measurements were undertaken in the summerof 2014 to obtain information about the location, depth, sizeand extent of buried archaeological features. Site conditions(steep slopes, high grass, obstacles, depth of investigation)determined the electrical active and passive geophysical methodsto be the most suitable geophysical methods. The activeelectrical method is one of the most commonly appliedtechniques for geophysical investigations in archaeologicalsites Schmidt (2013). This is due to the characteristic abilityof this method to detect walls, voids, graves and other deeperman-made structures (Clark, 1980; Burger and Burger, 1992;El-Gamili et al., 1999; Drahor, 2004; Schmidt, 2013).Furthermore, this relatively low-cost method is important for

identifying the relatively high electrical resistivity contrastbetween the structures of archaeological interest and thesurrounding soil (Griffiths and Barker, 1994; Negri et al., 2008).

The electrical passive method, used to identify the self-potential (SP), has had a smaller development in thearchaeological field, most likely due to the fact that the subsoilphenomena related to SP phenomena are not very well known(Leucci et al., 2014). Nevertheless, the electrical passive methodis one of the oldest methods used in geophysical exploration(Reynolds, 2011; Drahor et al., 1996; Drahor, 2004; De Giorgiand Leucci, 2015).

Electrical active and passive measurements were performedin three areas named Area 1, Area 2 and Area 3. In Area 3,a new method of imaging resistivity data was used. The newmethod, described by Di Fiore et al. (2002) and Mauriello andPatella (2005), is the 3D probability tomography imagingapproach based on the apparent resistivity tensor concept(Mauriello and Patella, 2005). This approach, applied for thefirst time in a large area and in the archaeological field, gaveinteresting results.

Data acquisition, processing and interpretation

Geophysical measurements were undertaken in three areaslabelled respectively Area 1, Area 2 and Area 3 (Figure 2).The three study areas were chosen to specifically resolvea series of unanswered archaeological questions: (1) Doesthe depression in the hypothesised ‘pottery quarter’ of Area 1represent a clay quarry (Degryse et al., 2003; Figure 3)? (2) Arethere tombs present in the hypothesised ‘stadium’ area betweenthe two Byzantine churches of Area 2 (Vermoere et al., 2003)?

CSIRO PUBLISHING

Exploration Geophysicshttps://doi.org/10.1071/EG16154

Journal compilation � ASEG 2017 www.publish.csiro.au/journals/eg

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(3) Are there defensive walls in Area 3 near the temple ofAntoninus Pius (Vermoere et al., 2003)?

To answer these questions, we used an Iris Syscal Kidresistivity meter (appropriately modified for the storage of SP)with 24 active channels for geoelectrical measurements. Thedipole–dipole array was applied because of its sensitivity tolateral changes in resistivity (Loke, 2001).

Area 1

With the aim of understanding the geological–archaeologicalsignificance of a deep depression located near the Romantheatre in Area 1, a 3D electrical resistivity tomography (ERT)survey in a 117� 143m grid was undertaken inside thedepression (Figure 3).

The measurements were collected along 16 lines positionedin a ray mode (Figure 3). The length of the lines varied from 143(max) to 117m (min), with electrode spacing ranging from 5 to6.5m. A total of 300 000 apparent resistivity measurementswere collected (n= 1 to n= 9, where n is the level numberrelated to the ERT survey and the hypothetical depth in thesubsoil). The relative standard deviation for each stack isa good indicator of the quality of the data, and therefore, itwas checked during each measurement. When the relativestandard deviation of the stacked data was greater than 3%, thevertical stack was increased to six. The standard deviation ofthe measurements was mostly below 1%. As the first step in

the ERT data processing, we applied a 2D inversion methodto obtain a more reliable image of the subsurface using theRes2Dinv software (Loke, 2001). This software iterativelycalculates a resistivity model to minimise the difference betweenthe observed apparent resistivity values and those calculatedfrom the model. The maximum number of iterations was set to4 or 11 for all profiles in order to avoid overfitting the data. Theinversion process resulted a satisfactory fit with a root meansquare (RMS) error between 4% and 12%. Due to low RMSerror, the obtained results can be considered as a reliablerepresentation of the true resistivity distribution of thesubsurface. In order to reduce disturbance related to thetopography effect, the distorted finite-element mesh (Loke,2001) was implemented in the Res2Dinv software. In thismethod, the amount that the subsurface nodes are shifted isreduced exponentially with depth so that at a sufficiently greatdepth, the nodes remain unshifted. This comes from theexpectation that the effect of the topography is reduced ordampened with depth (Loke, 2001).

Figure 4 shows the results of the 2D inversion from ERTprofile 1 in Figure 3. It is possible to see a layered resistivityprofile in the top 25–30m. A zone of low resistivity (~30 to300 Wm) extends from the surface to ~18m depth (1565 masl),which is underlain by a high resistivity zone (500 Wm) anda deeper layer with higher resistivity values (~1300 Wm) andlateral discontinuities at the ends. The geological model,established by means of a 2D resistivity imaging profile

(a)

(b)

Fig. 1. The archaeological site of Sagalassos (Turkey). (a) Geographical location (source: Google Earth). (b) Panoramic photo of thearchaeological site (source: G. Leucci).

B Exploration Geophysics L. De Giorgi and G. Leucci

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(Figure 4), allows for three distinct geological zones to bedetected. The first zone (upper 18m) is interpreted as a zonefilled with weathered material eroded and cemented over thecenturies. In some parts of this first zone, there are anomalieswith high resistivity values (1000–1200 Wm) that couldbe related to ‘stone objects’. The second zone, labelled the

‘quarry line’, could be related to rock of poor quality(fractured rock filled with clay) indicated by low resistivityvalues (Leucci et al., 2016). The third zone clearly indicatesthe presence of the bedrock. The close proximity of the bedrockto the ceramic quarter and the precise cuts in the bedrock suggestthe presence of a clay quarry.

Area 1Area 2

0 50 100 200 m

Area 3

Fig. 2. The surveyed areas at the archaeological site of Sagalassos (source: Google Earth).

Theatre

0 50 m25

Fig. 3. Area 1: ERT profiles.

Geophysics at Sagalassos, Turkey Exploration Geophysics C

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Following the 2D inversion, the resistivity distribution asfunction of depth was processed using a 3D software ‘ErtLab’,manufactured by Multi-Phase Technologies (http://www.geostudiastier.it/index_en.asp). Its numerical core is based onthe tetrahedral finite-element method and a robust inversion wasperformed (data variance iterative reweighting). The results ofthe inversion of the electrical dataset, given as horizontal depthslices (parallel to the surface), are shown in Figure 5.

Figure 5 shows the electrical resistivity model at fourdifferent depths. It is possible to note an area of highresistivity (1300–1400 Wm) surrounding an area (inside the

dashed red line) with resistivity values ranging from 50 to1500 Wm. The red dashed line marks the boundaries ofthe probable quarry. Clearly visible in the centre part of thesurveyed area is low resistivity (~15 Wm) zone ‘A’.The dimensions of this zone are ~20m length� 10mwidth� 4m depth, and the resistivity values could be relatedto clay materials. Also visible is a high resistivity (~1500 Wm)anomaly ‘B’ that could be related to stone materials.

The 3D images of electrical resistivity can easily bevisualised by 3D contouring of iso-resistivity volumes(Figure 6). In this representation, the transparency function is

Model resistivity with topographyIteration 11 Abs. error = 12.2

Inverse Model Resistivity Section

Horizontal scale is 28.59 pixels per unit spacingVertical exaggeration in model section display = 1.04

Resistivity in Ωm

Elevation (masl)

1585 0

26.0

52.078.0 104 130

1580

1575

1570

1565

1560

1555

1550

1545 10.0 22.5 50.6 114 256 577 1297 2919

NW SE

Bedrock

Fig. 4. Area 1: electrical resistivity distribution in the subsoil related to ERT profile 1.

117

87

58

29

00

1570 masl (14 m in depth fromthe high point of 1584 masl)

1568 masl (16 m in depth fromthe high point of 1584 masl)

1566 masl (18 m in depth fromthe high point of 1584 masl)

1564 masl (20 m in depth fromthe high point of 1584 masl)

36 72 107 143

Resistivity(Ωm)

2.20e+003

1.65e+003

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558.

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NW-SE direction (m)

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-NE

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NW-SE direction (m)

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-NE

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NW-SE direction (m)

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n (m

)

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00 36 72 107 143

NW-SE direction (m)

SW

-NE

dire

ctio

n (m

)

Fig. 5. Area 1: 3D electrical resistivity distribution in the subsoil presented as horizontal depth slices (parallel tothe surface). The dashed red line marks the boundaries of a possible quarry. ‘A’ indicates a low resistivity zone thatcould be related to clay materials. ‘B’ indicates a high resistivity zone that could be related to stone materials.

D Exploration Geophysics L. De Giorgi and G. Leucci

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defined by two threshold values of the electrical resistivity (r),r1 and r2 (r < r2). In the intervals r < r1 and r > r2, data arerendered as transparent, and therefore, only the data in theinterval r1< r < r2 are visualised. The threshold calibration isa very delicate task. In fact, by lowering the threshold value,not only is the visibility of the main anomaly raised, but alsothe visibility and noise of the smaller objects. In Figure 6, ther dataset is displayed with iso-r volumes using a thresholdvalue ranging from 2500 to 3000 Wm. The continuous highr anomaly are more visible. This kind of visualisation emphasisesthe variation in bedrock depth. As shown in Figure 6, the depthof the bedrock in the depression varies from ~14 to ~20m.

Another useful 3D visualisation is through the individual 2Dsections within the total 3D volume (Figure 7). From Figure 7

it is possible to recognise a layered area with stratification linkedto the values of resistivity at different depths. This stratificationcould be related to the weathered materials being eroded andcemented over the centuries.

In order to avoid edge effects of space domain filters, SP datawere processed using a low pass filter in the frequency domain,so that high frequencies were eliminated and low frequencieswere preserved. A least-squares analysis was used to estimatedepth, shape and the horizontal position of a buried structure.The processed data were used to build the SP maps shown inFigure 8. Using the above-mentioned method, the SP anomalieswere positioned at depths between ~22 and 28m. The resultsshow that the SP values vary between –100 and 100mV.Observing Figure 8, it is possible to note a probable waterflow from the positive SP values to negative SP values, whichcould hint at a possible palaeo-river bed.

Area 2

Area 2 is located in the hypothesised ‘stadium’ area betweentwo churches of Byzantine period (Vermoere et al., 2003). Inthis area we performed two ERT surveys in a 55� 95m grid(Figure 9). The measurements were collected along threelines. Lines 1 and 2 were perpendicular to each other and are65 and 115m long, respectively. Line 3 was acquired in a ‘snakeroll’ mode in order to cover the whole area. For this line,the electrode spacing was 2.5m. A total of 700 000 apparentresistivity measurements were collected (n= 1 to n= 9).

The relative standard deviation for each stack is a goodindicator of the quality of the data. When the relative standarddeviation of the stacked data was greater than 5%, the verticalstack was increased to six. The standard deviation of themeasurements was below 5%. As a first step in the ERTdata processing, we applied a 2D inversion method using theRes2Dinv software to obtain a more reliable image of thesubsurface.

Figure 10 shows the results of 2D inversion related tothe ERT profiles 1 and 2 in Figure 9. The geological model,established by means of a 2D resistivity imaging profile, allowsthree different zones to be detected. Thefirst zone is interpreted asa zone filled with weathered material that had collapsed andcemented during the past centuries. In some parts of this firstzone there are anomalies with high resistivity values (1000–1500 Wm) that could be related to ‘stone objects’. The second

NW

Stones

SE

2.20e+003

1.65e+003

1.11e+003

558.

10.0

Resistivity(Ωm)

Fig. 6. Area 1: 3D iso-resistivity volume using a threshold value rangingfrom 2500 to 3000Wm. The continuous high r anomaly is related to variationin bedrock depth.

NW

SE

2.20e+003

1.65e+003

1.11e+003

558.

10.0

Resistivity(Ωm)

Fig. 7. Area 1: Individual 2D sections within the total 3D volume. It ispossible to recognise a layered area with stratification linked to the valuesof resistivity at different depths.

Self potential (mV)

200.

125.

50.0

–25.0

–100.1556 masl (28 m in depth fromthe high quote of 1548 masl)

117

87

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00 36 72 107 143

NE

dire

ctio

n (m

)

SW direction (m)

Fig. 8. Area 1: SP map at 1556 masl. It is possible to note a probablewater flow (e.g. a possible palaeo-river bed) from the positive SP values tonegative SP values.

Geophysics at Sagalassos, Turkey Exploration Geophysics E

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zone, labelled ‘stone base’, could be related to a stone block(500–1800 Wm) located at depth of ~4m in Figure 10a and~5–6m in Figure 10b. The third zone clearly indicates thepresence of the bedrock (4500–5000 Wm) at depth of ~10m.

ERT data were then processed in 3D mode and presented ashorizontal depth slices (parallel to the surface), as shown in

Figure 11. Figure 11 shows the electrical resistivity model at2m depth, where it is possible to note a low resistivity zone(100–150 Wm) inside the dashed rectangles in the western sideof the area. The dimensions of this zone are ~2m long� 1mwide, and the resistivity values could be related to voids filledwith soil materials, possibly indicating the presence of tombs.

0 50 100 m

Fig. 9. Area 2: ERT profiles (source: Google Earth).

SE

SW

Horizontal scale is 27.98 pixels per unit spacingVertical exaggeration in model section display = 1.05

Horizontal scale is 28.26 pixels per unit spacingVertical exaggeration in model section display = 1.05

Model resistivity with topographyIteration 5 Abs. error = 4.8Elevation (masl)

1525

1520

0 20.0

2.35 7.10 21.5 65.0 197 595 54481801

40.0

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1510

1505

1500

1515

NW

NE

Elevation (masl) Model resistivity with topographyIteration 8 Abs. error = 6.2

20.001526

(b)

(a)

15241522152015181516151415121510

2.35 7.10 21.5 65.0 197 595 1801 5448

40.0 60.0 80.0 100

Unit electrode spacing = 2.50 m.

Unit electrode spacing = 2.50 m.Resistivity in Ωm

Resistivity in Ωm

Fig. 10. Area 2: electrical resistivity distribution in the subsoil related to ERT profiles (a) 1 and (b) 2.

F Exploration Geophysics L. De Giorgi and G. Leucci

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Some regular structures are clearly visible (dashed dark line).Resistivity values ranging from 1000 to 1200Wm likely indicatethe presence of walls.

In this area, the analysis of SP data was performed usingthe algorithm proposed by Eppelbaum et al. (2001, 2004), which

uses the similarities between magnetic and SP field data. Theresults, presented as horizontal depth slices (Figure 12), showSP values ranging from –80 to 100mV. At depths of 0.5 and1.0m, there appear traces of structures of archaeological interestin the form of positive values of SP (80–100mV). At a depth

65

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06560 7570 8580 90555045403530252015105

4.00e+003

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2.01e+003

1.01e+003

10.0

Resistivity(Ωm)

X distance (m)

–2 m

Y d

ista

nce

(m)

Fig. 11. Area 2: 3D electrical resistivity distribution in the subsoil.

65605550454035302520151050

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

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X distance (m)

0.5 m 1.0 m

9.0 m2.0 m

SP (mV)300

200

–100

100

–200

0

Fig. 12. Area 2: SP maps at several depths.

Geophysics at Sagalassos, Turkey Exploration Geophysics G

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of 2.0m it is possible to compare the SP values to the ERT depthslice at the same depth (Figure 11). Negative SP values couldbe related to probable traces of tombs and probable traces ofwater flow from the positive SP values to the negative SP valuesat ~9m in depth (Figure 12).

Area 3

In this area, two ERT surveys were performed in a 104� 128mgrid (Figure 13). The measurements were collected along twolines. Line 1 was a 115m long ERT profile that crossed the hill,while Line 2 circled around the hill in a ‘roll along’mode in orderto cover the whole area. The effectiveness of this acquisition

mode was discussed in Chavez et al. (2011), Argote-Espino et al.(2013), Tejero-Andrade et al. (2015) and Leucci et al. (2017).

Initially, a 2D survey was conducted along each perpendicularline or transect. In the next step, the current electrodes remainat the end of one line, while the potential electrodes are movedalong the line. Afterwards, the current electrodes are moved oneelectrode position and the potential electrodes are movedas previously described. The process is repeated until thecurrent and potential electrodes cover the circular geometry.This sequence of observations produces a series of apparentresistivity observations towards and beneath the central portionof the array. The coloured circles in Figure 14 represent theattribution pointswhere the apparent resistivities aremeasured for

0 50 100 m

Fig. 13. Area 3: ERT profiles (source: Google Earth).

(1.5;63.7;16.)

(1.5;63.7;0.)

(87.9;4.8;16.)

(87.9;4.8;0.)

0.9 42.2 1906.7 86239.7 3900710. Resistivity(Ωm)

Fig. 14. Area 3: apparent resistivity measured points.

H Exploration Geophysics L. De Giorgi and G. Leucci

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the ERT array. This process is discussed in detail by Tejero-Andrade et al. (2015).

The profile labelled 2 in Figure 13 is 320m long and consistsof five lines, each 64m long. The electrode spacing varied from2 to 3m due to the site inaccessibility (bushes, stones etc.).A total of 300 000 apparent resistivity measurements werecollected (n= 1 to n= 9).

The relative standard deviation for each stack is a goodindicator of the quality of the data. In the site, we notedseveral poor data points with high relative standard deviation(greater than 12%). This was due to the high values of theresistance contact between the electrode and soil.

In the ERT data processing, we applied a 2D inversionmethod to obtain a more reliable image of the subsurface

using the Res2Dinv software. Figure 15 shows the results of2D inversion related to ERTprofile 1 in Figure 13. The geologicalmodel, established by means of a 2D resistivity imaging profile(Figure 15), allows two different zones to be detected. Similarto Areas 1 and 2, the first zone was interpreted as a zone filledwith weathered material that collapsed and cemented over thecenturies. In some parts of this first zone, there are anomalies,labelled ‘A’, with high resistivity values (4000–4500 Wm)that could be related to structures of archaeological interest.The second zone clearly indicates the presence of bedrock(3000–3500 Wm) at ~4m depth.

Area 3 was chosen to test the applicability of the 3Dresistivity anomaly probability tomography method in anactual archaeological context (Di Fiore et al., 2002; Mauriello

WNWESE

Bedrock

Elevation (masl) Model resistivity with topographyIteration 5 RMS error = 12.7

1470

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ert1-corr-topo.bin

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Horizontal scale is 28.95 pixels per unit spacingVertical exaggeration in model section display = 1.03First electrode is located at 0.0 m.Last electrode is located at 115.0 m.

24.0 57.7 139 333 800 1923 4620

Unit electrode spacing = 2.50 m.Resistivity in Ωm

Fig. 15. Area 3: electrical resistivity distribution in the subsoil related to ERT profile 1.

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)

0

26

52

78

1040 32 64 96 128

S-N

dire

ctio

n (m

)

Apparent resistivity tensor(Ωm)

250

150

50

200

100

W-E direction (m)1.0 m depth

W-E direction (m)2.0 m depth

W-E direction (m)4.0 m depth

Bedrock

Fig. 16. Area 3: 3D apparent resistivity tensor distribution in the subsoil.

Geophysics at Sagalassos, Turkey Exploration Geophysics I

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and Patella, 2005). Apparent resistivity tensor was calculatedin 3D mode from the measured apparent resistivity data throughan algorithm written in Matlab. The results were presented ashorizontal depth slices (parallel to the surface) (Figure 16).

Figure 16 shows the apparent resistivity tensor model at fourdifferent depths. It is possible to note several anomalous zones(dashed lines) with a moderately high apparent resistivitytensor (150–200 Wm). The shape of these anomalies suggeststhe presence of structures of archaeological interest at depthsranging between 0.5 and 2.0m. At 4.0m in depth, the apparentresistivity tensor values increase to 250 Wm, possibly indicatingthe presence of bedrock.

The 3D images of apparent resistivity tensor can easily bevisualised by 3D contouring of iso-volumes (Figure 17). InFigure 17, the apparent resistivity tensor dataset is displayedwith iso-volumes using a threshold value ranging from 50 to250 Wm.

Conclusions

In this study, geophysical campaigns reveal some interestingresults that helped archaeologists interpret the history of theancient city of Sagalassos.

Area 1 is located near the ‘pottery quarter’. The characteristiclarge, and somewhat spherical, depression in this area has beena mystery for several years, with several hypotheses about itsformation, including a meteorite impact. Our results, however,indicate that the depression is about 70 000m3 and wasprobably used for centuries as a ‘quarry’; ERT results fromthe depression indicate anomalies of high resistivity that couldbe from man-made cuts inside the area, and traces of very lowresistivity values may be related to clay materials.

In Area 2, used as a ‘stadium’ during the time of the RomanEmpire, our results indicate that it was probably used as burialzone in the Byzantine period. In fact, the shape (rectangular)and dimension (~1� 2m) of low resistivity zones suggests thepossible presence of voids filled with soil materials that couldrepresent ancient tombs.

In the both Areas 1 and 2, SP analysis indicates the traces ofa water flow at depth.

Data acquisition from Area 3 was very difficult due to thepresence of many obstacles such as bushes, rocks, and fear of

snakes, spiders and scorpions. The ERT method was alsounsuitable in this area due to the high contact resistancebetween the soil and electrodes. Despite this, the ERT datawas not disregarded. Instead, a new approach was appliedthat considered the apparent resistivity tensor parameters anddemonstrated that the trace of the apparent resistivity tensorsmapped anomalies closely confined to the source bodies. Thisstrongly enhanced the performance of the high resolution,target-oriented probability tomography that was proposedin this paper. Our results indicate several anomalous zonesprobably related to archaeological structures which, accordingto the shape (rectangular and dimensions of approximately50� 70m), could be related to fortification walls.

Finally, in all three areas, 3D visualisation techniques aidedthe interpretation of resistivity datasets.

Conflicts of interest

The authors declare no conflicts of interest.

Acknowledgements

The authors warmly thank Professor Jeroen Poblom, Director of the Belgianarchaeological mission in Sagalassos, for the opportunity to performgeophysical measurements and for his valuable help during the surveys.A very special thank you is due to Dr George Metcalf for his usefulsuggestions in the writing of this manuscript. The authors would also liketo thank the reviewers and editor for their precious suggestions that havecontributed to the improvement of the paper.

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