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We performed magnetic and GPR measurements to image the buried ruins of the Middle Age abbey San Pietro in Crapolla, on the Sorrento‐Amalfi Coast (Massa Lubrense, Southern Italy). The site represents an important religious location, which is nowadays partially buried along the cliff. An integrated study was necessary to map the buried structures and address the archaeological excavation. For this reason, we carried out the surveys on two main grids in order to reconstruct the structures of the abbey and of its related church. The magnetic data were filtered through the discrete wavelet transform (DWT) and then transformed to total gradient maps. The obtained maps were interpreted with depth from extreme points (DEXP) imaging method to assess the horizontal and depth positions of the top. The GPR data were processed and time‐depth converted. Results from the integrated interpretation of these data suggest the possible presence of different vaulted rooms and an elongated structure at 0.3‐m depth from ground surface. This latter is interpretable in terms of perimetral and internal walls of the abbey and its church. These outcomes were crucial to successfully address archaeological excavations, which targeted one of the modelled areas and unearthed a wall at the predicted depths. [ABSTRACT FROM AUTHOR]

In the inversion of geophysical data, an attempt is made to obtain a model with the best fit on the observed data. Unfortunately, the results are usually accompanied by non-uniqueness and ambiguity. These inversion problems can be reduced by inverting different geophysical datasets. Sequential inversion is one of the most common ways to integrate two or more geophysical datasets, to obtain a model that is compatible with all geophysical data, thus reducing the amount of ambiguity. This paper presents separate inversions of DC resistivity and magnetic data and sequential inversion of DC resistivity constrained by magnetic data. Here, the inverse model of magnetic data is considered the initial model for the sequential inversion of DC resistivity data. At first, the algorithm is applied to a synthetic model composed of four conductive and magnetized bodies, and the results show notable improvement for the resistivity model after sequential inversion, compared with the separate resistivity inversion model. Finally, encouraged by the results obtained in the synthetic case, the algorithm was applied to DC resistivity and magnetic datasets that were collected in the archeological area of old Pompeii city nearby Naples, Italy. The result of the sequential resistivity inversion model was notably superior to the corresponding resistivity model obtained from standard separate inversion. [ABSTRACT FROM AUTHOR]

In this paper we perform a 2-D joint inversion of DC resistivity and magnetic data, constrained by cross-gradients. Inspired by methods developed for potential fields, we introduce into both the separate and joint inversion algorithms also compactness and depth weighting functions, under the form of a model weighting-function. These constraints, usually not considered for DC resistivity inversion, reveal to be decisive for its joint inversion with magnetic data. A linear approximated forward problem of the resistivity is used for the joint inversion so that both the resistivity and magnetic problems are expressed as a linear integral equation under the form of a Fredholm integral of 1st kind. To examine the feasibility of the joint inversion algorithm, we first test the method with two synthetic cases: a thick dyke in a two-layered medium and a cavity located above a conductor. A third synthetic case involves a multisource model. The results are encouraging, revealing that the cross-gradient constraint is an effective tool to improve the separate inversions of DC resistivity and magnetic data. The joint inversion algorithm is also applied to data in the archeological area of the old Pompeii city, nearby Naples. Comparing the results of joint and separate inversions, we obtain a significant improvement in the interpretation of both kind of data in terms of buried walls of an ancient roman villa. In all the studied cases, the cross-gradient constraint appears to be a key-diagnostic tool to assess whether actual coherence is gained among DC resistivity and magnetic susceptibility models. [ABSTRACT FROM AUTHOR]