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The Characterization of the Lower Town of the UNESCO Archaeological Site of Arslantepe (Malatya, Türkiye) Using the Geophysical E-PERTI Method (Extended Data-Adaptive Probability-Based Electrical Resistivity Tomography Inversion Method)

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05 December 2024

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06 December 2024

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Abstract
The UNESCO site of Arslantepe is located in Eastern Anatolia in the Malatya Plain (Türkiye) about 10km from the Euphrates River. Here for about a century archaeological excavations have been carried out reconstructing a long sequence of human frequentation starting from 5000 years BC up to the Middle Ages. The settlement, one of the most important and largest in the region, has undergone numerous changes over time resulting in a complex superposition of structures, palac-es, temples and burials concentrated on the hill. With the aim of extending the knowledge of the site, in 2022 geophysical surveys were carried out through the application of electrical resistivity tomography, covering a surface of approximately 4,300 m2 in an unexplored area at the foot of the hill. In this paper, the Extended data-adaptive Probability-based Electrical Resistivity Tomog-raphy Inversion approach (E-PERTI), recently published as development of the probability to-mography imaging approach, has been applied to a large apparent resistivity field dataset providing the best estimate of the most probable estimate of the resistivity distribution through an intrinsic linear regression model implementing standard least squares routines. Results seem to prove the effectiveness of the E-PERTI approach in noise dejection enhancing associated resistivity highs that can be ascribable to the trace of a potential fortification. The obtained information rep-resents new unexpected data that opens new frontiers of archaeological research adding value to the knowledge of the site.
Keywords: 
Subject: Arts and Humanities  -   Archaeology

1. Introduction

Electrical Resistivity Tomography (ERT) is a non-invasive geophysical method used for the characterization of the subsoil in terms of electrical resistivity distribution with the aim of obtaining information about the location and geometry of targets buried into the subsoil through measurements carried out mainly from the surface. Over the years, different authors have shown the potentiality of the method in archaeological applications [1,2,3,4,5,6,7,8,9,10]. An apparent resistivity dataset (measured in Ohm*m, Ωm) is collected along a profile using a device consisting of two energizing electrodes that inject the current (measured in Ampere, A) into the soil and two potentiometric electrodes that measure the potential difference (measured in Volt, V) generated by the current input. Commonly, different parallel profiles are acquired in a grid in order to test the extension and dimensions of any buried target. Therefore, a three-dimensional dataset of the volume under the surveyed surface is gained allowing extracting horizontal sections at various after proper systematic processing. Additionally, through the solution of the inversion problem, the intrinsic resistivity values are estimated from the observed and collected apparent resistivity data.
The problem of resistivity inversion is a nonlinear, ill-posed and underdetermined problem [11,12,13,14,15]. To develop a numerical model that fits observed data, the finite-difference [16,17] or finite-element methods [18] are frequently employed. Due to their applicability and their robustness the Gauss-Newton least-squared inversion [19] and the Occam’s inversion [20,21] are among the most often applied methods. Iterative linear approaches of the nonlinear problem have been also proposed for 2D and 3D data processing [22,23,24,25,26] such as the smoothness-constrained least-squares inversion [23]. Other mathematic solutions have defined for resistivity inversion by a number of authors using various methodologies [27,28,29,30,31,32].
To treat data acquired for archeological purposes, the Extended data-adaptive Probability-based Electrical Resistivity Tomography Inversion (E-PERTI) [33] has been proposed in this study. The method is not a typical deterministic inversion routine following a probability tomography approach in resistivity methods. The initial algorithm was formulated for the self-potential method and subsequently adjusted for processing resistivity data [34,35]. Without calculating the intrinsic resistivities, the procedure provided the probability of a high or low resistivity anomaly taking in account a reference model, the average apparent resistivity value of the entire dataset. The method was successfully applied in order to describe the geometry of potential sources in volcanic areas, to map buried archaeological structures and, to detect faults. Subsequently, in order to estimate the true resistivities, the algorithm [34] was modified and the data-adaptive probability-based ERT inversion method (PERTI) [36] was defined. From a probabilistic point of view, the procedure identifies within the set of possible solutions the most probable one that is compatible with the data set acquisition scheme. In this regards, the approach can be considered as a linearization of the problem. In the literature, numerous applications of the PERTI approach can be found in near-surface prospection to solve archaeological research questions. At last, the E-PERTI method has been developed to improve robustness to noise concerning the original PERTI and to obtain the maximum possible result from the apparent resistivity dataset. . The process involves extracting subsets of data from the observed resistivity data randomly by selecting horizontal or vertical windows of the datum space [33]. The result is the best estimate of the most probable resistivity through an intrinsic linear regression model implementing standard least squares routines. The first application of the E-PERTI scheme is related to the characterization of a buried ancient ditch.
In this paper, the method is applied to a large dataset acquired at the archaeological site of Arslantepe (Malatya, Türkiye), a masterpiece of ancient culture included in the UNESCO World Heritage List. The focal goal of the study was the creation of a novel comprehensive plot of hidden archaeological structures in an unmapped and unexplored area located in the northern part of the site.
The ERT survey was carried out using a dipole-dipole (DD) electrode configuration being more sensitive to surface inhomogeneities and capable to obtain lateral localization of anomaly sources [37].
In the following sections, at first, an outline of the E-PERTI method is provided starting from the original PERTI theory, then the test site is introduced and the results obtained from the application of the method to the ra,n (the apparent resistivity for the generic n-th measurement) values of the pseudosections are shown. Furthermore, by assembling all DD profiles, a 3D ERT model is provided and interpreted from an archeological point of view. The collected evidence represents a novelty in the study and an unchallenged advantageous for planning projects of archaeological investigation and initiatives of conservation and fruition of the area.

2. Outline of the E-PERTI Method

E-PERTI [33] is an extension version of the PERTI routine [36] that was developed from the resistivity probability tomography approach [34]. The initial basic form [34] involved calculating the resistivity anomaly occurrence probability function η m , which may be seen as a dataset likelihood. The area beneath the surface was divided in M nearby cubic cells with the same volume ΔV. These cells were centered in a point center ( x m , y m , z m ) (m = 1, 2, …, M), and had intrinsic resistivity ρ m . Furthermore, a running index n (n = 1, 2, …, N) that represented the electrode array’s location on the surface was expected to identify each of the N apparent resistivity measurements, ρ a , n that were supposed to make up the dataset. The subsequent PERTI method [36] assumes that the reference uniform resistivity is the unknown value ρ m . It follows that if at a point ( x m , y m , z m ) η m = 0 , then became obvious that the probability to have a variation in the cell placed at x m , y m , z m in relation to ρ m is zero. Stated otherwise, the intrinsic resistivity is same to is ρ m . By changing the coordinates ( x m , y m , z m ), point by point, the resistivity pattern within V is determined [36].
Afterwards, the Bernoulli distributions in probability [38] where taken into consideration when formulating extension of PERTI (E-PERTI) [33]. Thus, the occurrence of specific set of conditions that originates an elementary event of a space U of elementary events, the test space, is what makes each geoelectrical measurement a “test”. Considering a new test space, UN, made of arbitrary points of U, is obtained by taking into account N tests of a resistivity dataset. Additionally, the N-given tests can be regarded as independent since each nth geoelectric measurement can be assessed as a separate process. Consequently, any Q tests that are arbitrarily taken from the N-given test are hence likewise independent [38]. A set of Nq data (tests) is extracted from the N accessible data assuming Nq ≤ N for q = 1, 2, …, Q and Q are arbitrarily big. For every Nq set, η m , q is:
η m , q = C m , q ∑ k = 1 N q ρ a , k − ρ m , q ∂ ρ a , k r e f / ∂ ρ m , q ,
where
C m , q = ∑ k = 1 N q ∆ ρ a , k 2 ∑ n = 1 N q ∂ ρ a , k r e f / ∂ ρ m , q 2 − 1 / 2 .
In the Equation, ∆ ρ a , k is the difference between ρ a , k and the reference apparent resistivity ρ a , k r e f , computed at the same node as for ρ a , k using a reference model. Therefore, setting up
η m , q = 0 for   each   q = 1 ,   2 ,   … ,   Q ,
Q estimates of ρ m are obtained as follows
ρ m , q = ∑ k = 1 N q ρ a , k ∂ ρ a , k r e f / ∂ ρ m , q / ∑ k = 1 N q ∂ ρ a , k r e f / ∂ ρ m , q .
This allows the best estimator of ρ m to be obtained, for instance, by applying the conventional least squares method for determining the slope of a linear equation of the type
y = ρ m , q x
where
x = ∑ k = 1 N q ∂ ρ a , k r e f / ∂ ρ m , q
y = ∑ k = 1 N q ρ a , k ∂ ρ a , k r e f / ∂ ρ m , q .

3. Test Site: Arslantepe (Malatya, Türkiye)

Arslantepe is a multi-stratified mound located in south-eastern Anatolia a few kilometres east of the Euphrates river and close to the modern city of Malatya (Figure 1).
The site lies 912 meters above sea level at the south-eastern edge of the Malatya plain, a very fertile region rich in water sources and surrounded by the Taurus mountains. In the regional geological context, the investigated site Arslantepe is located in a fault-bounded extensional basin occupied by Neogenic alluvial and lacustrine deposits [39,40]. The superficial sediments (Pleistocene or Holocene) around the mound have been recently analyzed [41] documenting fluvial activity during the late glacial periods and frequently after the Roman period. Slope and soil erosion occurred in the early and mid-late Holocene and during the last 1000 years. The early Holocene erosion phases predate the start of settlement at the tell so far.
Since 1961, the site has been investigated with continuity by the Italian Archaeological Expedition in Eastern Anatolia (MAIAO) from Sapienza University of Rome, following the excavations by two French teams that took place in the 1930s and 1940s respectively [42]. The mound has an oval shape and has an extension of about 4.5 ha with a 30 m thick archaeological deposit. The uninterrupted excavation activities allowed the reconstruction of a very detailed and continuous sequence that, supported by numerous sets of C14 dates, stretches from the late 5th millennium BCE to the Medieval period, even though the continuous and most substantial occupation is the one up to 712BCE; when the site is destroyed by the Neo-Assyrian army. After this moment, the occupation in the plain will move nearer to the Euphrates river, where a roman military camp will take up the name of Melitene [43,44,45]. Besides being the most important excavated site in the region, Arslantepe is also commonly considered one of the most valuable sites for the comprehension of the processes of development that have affected the ancient civilizations of South-western Asia. Indeed, discoveries of incomparable importance for the understanding of the formation of the first centralized states and societies have been made since the beginning of the 1970s, including the astonishing and unique remains of the renowned Late Chalcolithic palace that recently led to the site’s inclusion in the UNESCO World Heritage List [46,47].
However, only few preliminary activities have been so far undertaken in the off-mound and catchment areas, in order to reconstruct a more comprehensive view of the site and its surrounding territory. The Archaeological Survey Project in the Malatya Plain, which was conducted from 2003 to 2007 in the territory immediately south of the Euphrates, also included an intensive field activity carried out in the 500 meters surrounding the site, that has shown a significant scarcity of surface material [48]. However, the low visibility due to both recent alluvial deposits and intensive and long-lasting modern horticulture should be taken into account.
In this perspective, geoarchaeological investigations, conducted between 2009 and 2011, have allowed collecting coring soil samples from wells dug in the alluvial sediments north-west of Arslantepe that provided layers with pottery fragments and charcoals that mostly date to the Iron Age and Roman periods; these are at a varying depth well below today’s surface, confirming the presence of thick alluvium which could have covered the ancient remains surrounding the mound [48,49].
A project investigating primarily cultural and natural heritage around Arslantepe to evaluate accurately the use, protection, conservation, and valorisation of the site with its surroundings has been also carried out in the years 2017-2020 [49,50]. In the framework of the project and with the intent of creating the “Arslantepe Archaeological Park”, the existence of different degrees of protection to contain the increasing rate of urbanization around the mound has been ratified. This brought to the realization, between 2019 and 2020, of a first round of large-scale magnetic prospections and widely spaced electrical resistivity profiles which revealed the presence of high magnetic anomalies all around the mound and particularly at the bottom of its northern slopes.

4. Results

Following the premises, during the 2022 and 2023 excavation seasons, a wider geophysical prospection was conducted at the bottom of the mound, where the prospections of 2019 and 2020 revealed the highest resistive anomalies and with the intention to set up a clearer picture of some of the potential buried remains. Geophysical surveys were performed on an area extending from the bottom of the northern slopes of the hill to cover a surface of approximately 4.300 m2 (Figure 1) and 111 profiles were arranged as in Figure 2a. In each set of parallel profiles (Lines 1-6, Lines 7-24, Lines 25-40, Lines 41-44, Lines 45-77, Lines 78-11), contiguous lines were placed at a mutual distance of 1.5 m on which 16 electrodes were fixed with a dipolar spread of 1.5 m, giving a total length of 22.5 m. In few cases, a lower number of electrodes was adopted for logistical reasons. Furthermore, each set overlapped to the next one of 7.5 m in order to have a good coverage of measurement in depth. Data acquisition was performed through the multi-electrode MAE A3000TM resistivity meter (www.mae-srl.it) (Figure 2b). Implementing the dipole–dipole array for increasing values of n the signal strength and the signal-to-noise ratio decrease [51]. In order to solve this matter, three solutions can be adopted [52]: to increase the intensity of the injected current, to use stacking process of the voltage at the receiving dipole, to increase the sensitivity of the array with depth enlarging dipole lengths [51]. Considering the features of the adopted instrument, all of the three approaches have been adopted. In this way, data were acquired following the plan shown in figure 2a.
The measured apparent resistivity values are included in a wide range between 10 Ωm and 500 Ωm. In Appendix A (Figure A1, Figure A2, Figure A3, Figure A4, Figure A5, Figure A6, Figure A7, Figure A8, Figure A9, Figure A10 and Figure A11), the pseudosection and the final E-PERTI section resulting from the estimation of ρ m with a linear best-fit procedure applied point by point to the resistivity values belonging to the PERTI sections obtained by vertical scanning are shown for each profile. Apparent resistivity and modeled real resistivity maps are expressed in logarithmic scale and a uniform color sequence within the same [ ρ a , m i n , ρ a , m a x ] interval has been used for each section. In this case, it is not useful to calculate the RMS error between the measured and modeled apparent resistivity values as the method does not require a priori information and iterative processes. In order to Therefore, one way to evaluate the ability of modeling of E-PERTI is to make a comparison of the results with those of other deterministic inversion algorithms as shown in [36].
The E-PERTI sections demonstrate the ability to reconstruct a satisfactory subsurface model by eliminating the dragging effects resulting from the array used. In detail, the E-PERTI sections allow to enhance the presence of a well bounded resistive bodies with resistivity that vary from 130 Ωm to 500 Ωm. This is clear in numerous profiles: L1-L15 (Figure A1 and Figure A2), L28-L37 (Figure A3 and Figure A4), L41-L44 (Figure A5), L53-L58 (Figure A6) and L103-L111 (Figure A11). In the figures, the A and B letters are used to highlight the location of the high resistivity bodies. Elsewhere, the stratigraphy appears quite homogenous and, considering the typology of sediments exposed at the surface, it can be assumed to be composed by alluvial deposits [41]. Furthermore, the correlation between the newly acquired geophysical data and the magnetic data collected between 2019 and 2020 is not fruitful since the latter were sampled according to a very sparse grid with station points spaced 25-50 m and therefore with insufficient detail.
Finally, by assembling all E-PERTI profiles, a 3D model has been obtained. In Figure 3, as series of horizontal slices at growing depth from 1.5 m down to 3.75 m under the surface is located on a satellite image. The high-resistivity volumes (A to the west, B to the east) are about 5 m large and 50 m long. They are distributed along a regular route that circles the hill. This does not happen through a curved line but through two broken segments that form an angle slightly wider than 90 degrees. In Figure 4 the 3D ERT model is depicted in the full compact form (Figure 5a, b) showing also some vertical (Figure 4c, d) and horizontal slices (Figure 4e, f). In Figure 4b, in order to better highlight the resistivity highs, the color scale has been adapted by constricting the right-hand half of the logarithmic scale below the value 2.1 and setting up the left-hand half colorless.

5. Discussion

The analysis has shown very promising outcomes that need to be combined with the well-established data coming from the excavations and to be compared to other known contexts to build some broader reconstructions and hypotheses that can be especially useful in a framework of future perspectives.
The important challenge is to first of all establish the typology of any buried architectural structure and its potential chronology in the broad spectrum of occupation of the archaeological site. The analysis has highlighted the existence of coherent evidence that, archaeologically, immediately brings to mind a massive fortification, or retaining wall, with its continuous foundations on the lower level and elevation on the upper level with the potential existence of one or even two passages. In order to give more value to this interpretation, the data are integrated into the wider picture of the Arslantepe᾽s settlement pattern. Other fortifications are present at the site, all located on the mound itself [44]. Of course, the fact that in several phases of the history of Arslantepe, there is evidence to highlight that the mound was enclosed by different sorts of defensive systems does not necessarily imply the presence of fortifications in the off-mound area. However, this is also a hint that cannot be neglected, considering that the reasons to protect some parts of the settlement could have also affected the foot of the hill.
The phases on which to focus particular attention are those belonging to the later part of the sequence, which approximately runs from the mid-2nd to the mid-1st millennium BCE. Indeed, it is known that the northern part of the mound, that is the portion of the hill in the proximity of the surveyed area, was mostly occupied during this time-span. It is also important to note that the mound, or part of it, was systematically fortified throughout these thousand years.
In this framework, special emphasis needs to be placed on the construction of the fortification wall and possibly associated monumental gate that were built to surround the northern portion of the mound during the Early Iron Age (ca. 1250-850 BCE) [53]. Noteworthy, the defensive system shows the same size, position, and orientation of our off-mound geophysical evidence, with a difference in elevation of slightly less than 15 meters and a distance of around 60 meters.
It is also possible that a ramp brought to light in the 1960 excavations was linking the abovementioned inner wall with our findings at the foot of the hill [54]. This consisted of the alternation of rows of stones and wooden beams, recognizable by the empty spaces left after decomposition. Despite the fact that no direct association between the fortification and the ramp has been evidenced, its position and orientation allow us to assume that the latter provided access from the lower town to the Iron Age citadel.
A few more insights concerning the Iron Age occupation at the site can be useful to set the analysis in a more detailed and comprehensive historical and archaeological context. The significant political and cultural role of Arslantepe during the Iron Age is well-known, considering that the site was the capital of the Syro-Anatolian kingdom of Malizi/Melid, as is renowned by many local inscriptions distributed over its territory [53].
It is also important to shortly consider the abovementioned observations within the broader studies on the settlement patterns of the main Iron Age Syro-Anatolian cities. Indeed, during the last decades, these have developed increasing interest and underlined the existence of a shared idea of urban planning that shows the presence of a hierarchical and composite concept of the settlement layout [55,56].
The main cities or capitals of the Iron Age Syro-Anatolian region were characterized not only by the existence of fortified citadels but also by the presence of a bi-partite, or sometimes even tri-partite organization of these. The different parts were not only separated from each other using fortifications, but also in terms of height, with a significant dissimilarity in elevation between them. The peripheral location of the citadels, meaning that these were not necessarily centred compared to the whole fortified settlement, is also a characteristic feature and not only for those cases of cities whose layout was forced by the vicinity of a river.

6. Conclusions

In this paper, for the first time, the E-PERTI method was applied to process and interpret a large dataset relating to an archaeological case study. The objective was to obtain information in an unexplored portion of territory around the site of Arslantepe, a masterpiece of ancient culture included in the UNESCO World Heritage List.
As in previous methodological studies [33,34,36], the method proved to be a robust approach in noise detection and effective in modeling buried archaeological structures as any standard interactive inversion process. In detail, results showed the presence of high-resistivity volumes distributed along a regular route that circles the hill. They form an angle slightly wider than 90 degrees with regular dimensions (5 m large and 50 m long).
The analysis has highlighted the existence of coherent evidence that might be interpreted archaeologically as a massive fortification dated to the Iron Age (Figure 5). This would not be surprising, considering what is already known about the important political role covered by Arslantepe during this period and its related archaeological evidence within the framework of the urban layout of the Syro-Anatolian city-states.
It is clear that pushing any interpretation about the layout of the wall elevation and especially the potential presence of a passage would be completely speculative. Indeed, it is impossible at the current state to confirm if some of those elements visible in the horizontal section could really fit in the coherent layout of a gate. However, it is also useful to remark that comparisons with the main Iron Age Syro-Anatolian urban centres show us that the citadels, because of their ideological and symbolic relevance, requested prominent visibility, both from outside the city and along the path that led to them. The fact that at Arslantepe the gate to the Iron Age citadel was positioned right on top of the potential access located at the foot of the hill – that means that the lower and upper gates were literarily facing each other – seems to fit again very well with this pattern.
With the full awareness that the results here presented are totally preliminary and also based on a restricted part of the settlement, we would like to conclude stressing again the importance of this research in finally bringing results on the existence of off-mound evidence at Arslantepe and developing new food for thought for further future perspective of work. It is advisable to plan targeted excavations, surveys and trench sampling to understand the sequence of habitation and land use or activity in the area, combining standard field archaeology approaches with chemical and grain size characterisation to reveal patterns associated with environmental or anthropogenic events [57].

Author Contributions

Conceptualization, F.B.R., M.C., F.M. and P.M.; methodology, M.C. and P.M..; software, M.C. and P.M.; investigation, M.C. and F. M.; data curation, M.C. and P.M.; writing—original draft preparation, M.C., F.M. and P. M.; writing—review and editing F.B.R., M.C., F.M. and P.M.; project administration, F.B.R. and P.M.; funding acquisition, F.B.R. and F.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Grandi Scavi Sapienza, Ministero degli Affari Esteri e della Cooperazione Internazionale (MAECI), Fondo Ordinario Enti di Ricerca (CNR-FOE).

Acknowledgments

We are grateful to the Kazılar ve Arastırmalar Daire Baskanlıgı of the Kültür Varlıkları ve Müzeler Genel Müdürlügü (General Directorate of Cultural Heritage and Museums) of the Republic of Türkiye for the fruitful collaboration and for permitting to carry out the fieldwork. We thank landowners Recai Daǧdelen and Battal Çelik, who agreed to perform the remote sensing on their land. We are very grateful to Aysun Tuna for having shared with us the results of preliminary work around the site of Arslantepe that helped choose the investigation area.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

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Figure A1. Lines 1-10: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
Figure A1. Lines 1-10: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
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Figure A2. Lines 11-20: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
Figure A2. Lines 11-20: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
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Figure A3. Lines 21-30: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
Figure A3. Lines 21-30: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
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Figure A4. Lines 31-40: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
Figure A4. Lines 31-40: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
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Figure A5. Lines 41-50: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
Figure A5. Lines 41-50: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
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Figure A6. Lines 51-60: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
Figure A6. Lines 51-60: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
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Figure A7. Lines 61-70: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
Figure A7. Lines 61-70: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
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Figure A8. Lines 71-80: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
Figure A8. Lines 71-80: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
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Figure A9. Lines 81-90: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
Figure A9. Lines 81-90: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
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Figure A10. Lines 91-100: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
Figure A10. Lines 91-100: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
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Figure A11. Lines 101-111: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
Figure A11. Lines 101-111: Measured apparent resistivity pseudosection (left) and E-PERTI section resulting from the estimation of rm with a linear best-fit procedure (right).
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Figure 1. Position of Arslantepe on a physical map of Türkiye and the eastern Mediterranean basin and location of the survey area on an aerial view of the hill.
Figure 1. Position of Arslantepe on a physical map of Türkiye and the eastern Mediterranean basin and location of the survey area on an aerial view of the hill.
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Figure 2. The ERT survey planning at the northern foot of the hill of Arslantepe (a), and data acquisition with MAE A3000TM resistivity meter along Line 9 (b).
Figure 2. The ERT survey planning at the northern foot of the hill of Arslantepe (a), and data acquisition with MAE A3000TM resistivity meter along Line 9 (b).
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Figure 3. Sequence of horizontal slices at increasing depth of 1.5 m (a), 2.25 m (b), 3.0 m (c) and 3.75 m (d) beneath the ground level overlapped to a satellite image. A and B mark the two high-resistivity volumes.
Figure 3. Sequence of horizontal slices at increasing depth of 1.5 m (a), 2.25 m (b), 3.0 m (c) and 3.75 m (d) beneath the ground level overlapped to a satellite image. A and B mark the two high-resistivity volumes.
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Figure 4. 3D ERT model obtained by the assemblage of the E-PERTI sections (a, b) showing also some vertical (c, d) and horizontal slices (e, f).
Figure 4. 3D ERT model obtained by the assemblage of the E-PERTI sections (a, b) showing also some vertical (c, d) and horizontal slices (e, f).
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Figure 5. Overlapping of geophysical results on the archaeological map relative to the Early Iron Age (a) and on an aerial picture (b). The fortification is marked with magenta arrows and the gates with blue arrows, both those known and those hypothesized.
Figure 5. Overlapping of geophysical results on the archaeological map relative to the Early Iron Age (a) and on an aerial picture (b). The fortification is marked with magenta arrows and the gates with blue arrows, both those known and those hypothesized.
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