GNGTS 2016 - Atti del 35° Convegno Nazionale

GNGTS 2016 S essione 3.2 565 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 SYSCAL 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 SYSCAL 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 processedwith 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.