Semi-Automatic Identification and Pre-Screening of Geological–Geotechnical Deformational Processes Using Persistent Scatterer Interferometry Datasets

Abstract

This work describes a new procedure aimed to semi-automatically identify clusters of active persistent scatterers and preliminarily associate them with different potential types of deformational processes over wide areas. This procedure consists of three main modules: (i) ADAfinder, aimed at the detection of Active Deformation Areas (ADA) using Persistent Scatterer Interferometry (PSI) data; (ii) LOS2HV, focused on the decomposition of Line Of Sight (LOS) displacements from ascending and descending PSI datasets into vertical and east-west components; iii) ADAclassifier, that semi-automatically categorizes each ADA into potential deformational processes using the outputs derived from (i) and (ii), as well as ancillary external information. The proposed procedure enables infrastructures management authorities to identify, classify, monitor and categorize the most critical deformations measured by PSI techniques in order to provide the capacity for implementing prevention and mitigation actions over wide areas against geological threats. Zeri, Campiglia Marittima–Suvereto and Abbadia San Salvatore (Tuscany, central Italy) are used as case studies for illustrating the developed methodology. Three PSI datasets derived from the Sentinel-1 constellation have been used, jointly with the geological map of Italy (scale 1:50,000), the updated Italian landslide and land subsidence maps (scale 1:25,000), a 25 m grid Digital Elevation Model, and a cadastral vector map (scale 1:5,000). The application to these cases of the proposed workflow demonstrates its capability to quickly process wide areas in very short times and a high compatibility with Geographical Information System (GIS) environments for data visualization and representation. The derived products are of key interest for infrastructures and land management as well as decision-making at a regional scale.

ADAtools: Automatic Detection and Classification of Active Deformation Areas from PSI Displacement Maps

“…In the case of ADAfinder, the methodology to perform the identification and assessment of ADA was presented in [26,27] back in 2017 and 2019, respectively. In these works, the authors explain in detail the procedure to identify the active deformation areas and to assess their quality.…”

Automatic Subsidence Troughs Detection in SAR Interferograms Using Circlet Transform

“…Many studies have shown the use of the DInSAR methodology to assess the ground deformation [ 6 , 7 , 8 , 9 ]. Over the past few years, a lot of effort has been put in the automation of DInSAR [ 10 , 11 , 12 ] or PSInsar procedures [ 13 ]. The development of an effective method of automatic detection of deformation patterns in the SAR interferograms is difficult due to the presence of noise and irregularities.…”

Vulnerability Assessment of Buildings due to Land Subsidence Using InSAR Data in the Ancient Historical City of Pistoia (Italy)

“…Since seismic, volcanic and flood vulnerability has been widely studied, geological risks associated to local or slow processes are still underdeveloped. Recent studies focused on landslides and rockfalls, developing methodologies that generate useful products for local authorities derived from remote sensing data [ 12 , 27 , 28 , 29 , 30 , 31 ]. Land subsidence is characterized by slow displacements that usually cover large areas and involve agricultural and economic activities as well as buildings, cultural heritages and linear infrastructures, generating important economic losses.…”