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processing of geophysicaL surveys in suburban and urban archaeoLogicaL sites empLoying different integrated approaches E. Papale, S. Piro, D. ZamunerIstituto per le Tecnologie Applicate ai Beni Culturali. ITABC-CNR, Roma, Italy

Introduction. The aim of archaeological prospections is to obtain information about the geometrical and physical characteristics of buried archaeological remains present at shallow depth in the ground.

Generally, the limited size and depth of the archaeological remains, the presence of structures built with the same material as the surrounding rocks, soil inhomogeneity and environmental and anthropogenic disturbances, can be considered as “source” of noise which can cover the anomalies and contribute to acquisition of data with low S/N. It is possible to overcome these problems by improving data acquisition techniques (modern instruments allow the application of high resolution two dimensional and three dimensional acquisition techniques), by improving data processing methods through application of signal to noise enhancement techniques and by anomaly modelling. Another approach, which is discussed in this paper, involves the integration of data obtained with multiple geophysical methods (Brizzolari et al., 1992; Piro et al., 2000, 2016; Kvamme, 2007; Kucukdemirci et al., 2015).

Qualitative and quantitative integration techniques have been applied to data acquired in urban and suburban areas using the Ground Penetrating Radar (GPR) and the Electrical Resistivity Tomography (ERT) method.

For the qualitative integration, graphical overlays and RGB colour composites have been applied to the datasets. Quantitative integration instead involves mathematical and statistical processes by which it is possible to merge the data acquired into one dataset. In this case we applied the mathematical approach of data sum and the statistical approach of Principal Component Analysis.

These methods were used to process geophysical data collected in two sites in Italy; the first is situated in a suburban area in the Aurunci Natural Regional Park (Latina). The second site is instead located in an urban context in the city of Rome, near Santa Balbina’s church. The purpose of this work is to verify the applicability of some integration techniques of the data acquired with different methods and eventually to demonstrate the advantages of combining the geophysical methods used for this work.

Investigated sites. Suburban Site (Appian Way, Fondi). The area is situated along an ancient segment of the Via Appia, near the Gorge of St. Andrew (Gola di S. Andrea). The area is characterized by the presence of various archaeological features such as the well-preserved old basalt paving from the mid-Imperial period and the Fort of St. Andrew, which is a mixture of Roman, medieval and modern fortification that closed the way to the gulf. Moreover, there is proof of the presence of an ancient temple dedicated to the God Apollo, which has been dismantled over the centuries in order to build other structures such as the Fort of St. Andrew. The subsurface is also characterized by the presence of some archaeological features, such as a series of cisterns for water storage dating back to the III century B.C.

Geologically, the sedimentary succession cropping out in the area belongs to the carbonate platform domain, and it consists of neritic carbonate deposits of upper Triassic to Upper Cretaceous age (Accordi et al., 1988; Chiocchini et al., 1977).

Urban Site (Santa Balbina, Rome). The second investigated site is located in the central part of the city of Rome, near the Santa Balbina all’Aventino’s Church. There is not much archaeological information regarding this area, however it is suggested that there may be the presence of structures associated with the Servian Wall (IV B.C.), and tuff quarries. In this area the stratigraphic succession is mainly characterized by the presence of the “Tufo Lionato” formation which consists of a lithified pyroclastic flow deposit from the Albani Volcanic Complex, overlaid by the alluvial sediments of the Aurelia Formation (Middle Pleistocene) (Funiciello et al., 2008).

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Geophysical surveys. The Appian Way – Fondi. The suburban area, near Fondi was investigated using the Ground Penetrating Radar (GPR) and ERT.

Part of the GPR surveys were conducted during 2013 in a 14 m x 24 m area, using the SIR 3000 (GSSI) system equipped with a 400 MHz bistatic antenna with constant offset. This portion of the investigated area is located where the presence of the cisterns was hypothesised by previous studies. A total of 29 profiles were collected with a horizontal spacing of 0.5 m.

An area of 5 m x 23.5 m overlapping the surveyed GPR area was investigated by 11 parallel ERT profiles, distanced by 0.5 m, each consisting of a 0.5 m spaced 48 electrodes, Dipole-Dipole array. The measurements were carried out employing an IRIS S�SCAL Junior Switch-72.

Santa Balbina’s Church – Rome. The second site was also investigated using the GPR and ERT methods. For GPR surveys the site was divided in two areas investigated in two separate times using the SIR 3000 (GSSI) system equipped with a 400 MHz bistatic antenna with constant offset. The first area of 50 m x 45 m was investigated during December 2013 by collecting 101 profiles with horizontal spacing of 0.5 m. The second area was investigated in May 2015 with an extent of 60 m x 35 m; a total of 121 profiles was collected with a horizontal spacing of 0.5 m.

The ERT survey was performed in an area overlapping the two GPR surveyed areas; in order to acquire 3D data a special array type was employed (“Snake” geometry with a Dipole – Dipole configuration), consisting of 72 electrodes laying in a regular rectangular grid of 18 by 4 electrodes with a spacing of 2 m; 11 of these ERT grids were used in order to cover a total area of 72 m x 40 m. The measurements were taken employing an IRIS S�SCAL Junior Switch-72.

Data processing and results. GPR Data. All processing operations of the acquired data were performed using the GPRSlice software (Goodman, 2015), with which it was possible to obtain time slices.

At the site of the ancient Appian way, strong reflections have been recorded, which are associated with the empty portions of the cisterns present in the area. These anomalies are clearly visible from a depth of about 1 m.

In Santa Balbina two different types of anomalies appear. At shallower depths the images show the presence of regular strong anomalies which could indicate the presence of possible structures. The deeper slices are characterized by diffused anomalies, that may be related to the presence of collapsed buildings.

ERT Data. ERT data was processed differently for the two areas. In the suburban site along the ancient Appian Way the 11 ERT profiles were inverted using the software RES2DINV (Geotomo); all the inverted electrical sections display approximately the same features and are characterized by high resistivity anomalies (over 10,000 Ωm) some of which are surely related to the presence of the empty sections of the cisterns. These inverted pseudosections were then interpolated using Voxler (Golden Software) in order to obtain a 2.5D model of the resistivity distribution of the subsurface, from which it was possible to extract depth slices.

The data acquired from the second site was instead processed with the RES3DINV (Geotomo) software which generates directly the depth – slices. The highest resistivity anomalies (ρ > 150 Ωm) may be related to the presence of structures such as buildings, while sections of the investigated area with lower resistivity (ρ < 50 Ωm) can indicate the presence of inhomogeneous material.

Fig. 1a shows the GPR and ERT depth slices at a depth of 1.4 m used for data integration for the Appian Way site. Fig. 2a shows the GPR and ERT depth slices at a depth of 0.5 m used for data integration for Santa Balbina’s site.

Qualitative data integration. Contour maps overlays. Contour line maps were generated for all the GPR and ERT depth slices and overlaid (Figs. 1b and 2b). This method is particularly helpful for rapidly visualizing together the different geophysical datasets in their spatial context.

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For the site in Fondi it could show to a good approximation how the cisterns were “seen” by the single methods; furthermore, the matching of the anomalies confirms the presence of structures. For the Santa Balbina site instead the overlays do not show good matching anomalies, however, it could be useful to discern the differences between the datasets, especially, in this case, in terms of resolution. One disadvantage of this method is that the images might become too confusing if many datasets are overlaid.

RGB Colour Composites. In this visualization method, to each of the dataset is assigned

Fig. 1 – Results for the Appian Way site (Depth: 1.4 m). a) Normalized GPR and ERT data for a depth of 1.4 m. b) Contour map overlays: GPR data is represented as black contour lines; ERT data is represented as red contour lines. c) RGB colour composite: green indicates the GPR slice and red indicates ERT slice. d) Results for Data Sum. e) Results for Principal Component Analysis (1st principal component).

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a primary colour and the images are then combined to create colour mixes that span the full visual spectrum (Kvamme, 2007). In this case the GPR depth slices were represented by a red band and the ERT depth slices through a green band (Figs. 1c and 2c). In this case, the final images relative to different depths will be represented through various degrees of red and green, depending on the location and intensity of the anomalies; the yellow colour in the maps, will indicate the areas where strong anomalies were observed by both methods. This is clearly visible in the images obtained by the combination of the slices for the site of Fondi, where the

Fig. 2 – Results for Santa Balbina’s site (Depth: 0.5 m). a) Normalized GPR and ERT data for a depth of 0.5 m. b) Contour map overlays: GPR data is represented as black contour lines; ERT data is represented as red contour lines. c) RGB colour composite: green indicates the GPR slice and red indicates ERT slice. d) Results for Data Sum. e) Results for Principal Component Analysis (1st principal component).

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yellow portions indicate the position of the cisterns. This method is more effective than the contour maps overlay method since it helps in better defining the position of the anomalies detected by the different methods in a more meaningful way.

Quantitative data integration. Data Sum. The data sum integration method consists in adding together the normalized cell values of each dataset, to produce a new set of data containing all the anomalies detected by the methods employed, including those of large and small magnitude (Piro et al., 2000). This process was carried out for each depth slice where the resulting datasets will contain the contribution of all the methods employed at different depths. More precisely this will give an indicator of the spatial distribution of the anomalous sources detected by at least one of the methods used. The results obtained show how both the GPR and ERT methods concur to give a complete image of the subsurface in the two sites (Figs. 1d and 2d). The maximum value of the integrated dataset corresponds to the areas where all methods recorded the maximum anomaly pattern, while the lowest values coincide with the points where no method recorded a variation in the measured parameter. As expected it can be seen from the results that the data sum enhances strong anomalies, yet also includes lower intensity anomalies that were not previously visible. Since this integration technique generates new datasets, it is also possible to generate a 3D model of the integrated data.

Principal Component Analysis. Principal components analysis (PCA) is a statistical procedure that transforms a number of correlated input datasets into output images that are uncorrelated. The first principal component usually accounts for most of the variance from all the output images and each successive component summarizes less and less of the total variation (Davis, 1986). The more the original variables are correlated, the more meaningful the new dataset will be and therefore the more information can be retrieved from the reclassification. The PCA was performed on the normalized depth slices for the two sites (Figs. 1e and 2e). In the first case (ancient Appian way) for most of the slices, this method gave good results; this is due to the fact that the GPR and ERT data for this site is highly correlated.ReferencesAccordi G., Carbone F., Civitelli G., Corda L., De Rita D., Esu D., Funiciello R., Kotsakis T., Mariotti G., Sposato

A.; 1988: Note Illustrative alla Carta delle litofacies del Lazio – Abruzzo ed aree limitrofe. C.N.R – Progetto Finalizzato Geodinamica: sottoprogetto 4. Quad. Ric. Scient., 114, vol, 5, 223 p.

Brizzolari E., Ermolli F., Orando L., Piro S., Versino L.; 1992: Integrated geophysical methods in archaeological surveys. Journal of Applied Geophysics 29: 47-55.

Campana S., Dabas M., Marasco L., Piro S., Zamuner D.; 2009: Integration of remote sensing, geophysical surveys and archaeological excavation for the study of a medieval mound (Tuscany-Italy). Archaeological Prospection, Vol. 16, n. 3, 167-176.

Chiocchini M., Mancinelli A.; 1977: Microbiostratigrafia del Mesozoico in facies di piattaforma carbonatica dei Monti Aurunci (Lazio Meridionale). Studi Geologici Camerti, 3, 109-152.

Davis J.C.; 1986: Statistics and Data Analysis in Geology. John Wiley & Sons.Funiciello R., Giordano G.; 2008: Note illustrative della carta geologica d’Italia alla scala 1:50000, Foglio 374

“Roma”. Servizio geologico d’Italia.Kucukdemirci M., Piro S., Ozer E., Baydemir N., Zamuner D.; 2015: An integrated geophysical survey at Aizanoi

archaeological site (Turkey). Proceedings of 11th International Conference on Archaeological Prospection ICAP2015. Archaeologia Polona, Vol. 53, 477-479. ISSN: 0066-5924.

Kvamme L. K.; 2007: Integrating multiple geophysical datasets. Remote Sensing in Archaeology (Ed.s) Wiseman J and El-Baz F. , pp 345-374. Springer ISBN 978-0-387-44453-6.

Piro S., Mauriello P., Cammarano F.; 2000: Quantitative integration of geophysical methods for archaeological prospection. Archaeological Prospection, 7, 203-213.

Piro S., Gabrielli R.; 2009: Multimethodological approach to investigate chamber tombs in the Sabine Necropolis at Colle del Forno (CNR, Rome, Italy). Archaeological Prospection, Vol. 16, n.2, pp. 111-124.

Piro S., Papale E., Zamuner D.; 2016: Different integrated geophysical approaches to investigate archaeological sites in urban and suburban area. Geophysical Research Abstracts, Vol. 18, EGU General Assembly 2016.