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

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Title: Semi-Automatic Identification and Pre-Screening of Geological–Geotechnical Deformational Processes Using Persistent Scatterer Interferometry Datasets
Authors: Tomás, Roberto | Pagán, José Ignacio | Navarro, José A. | Cano, Miguel | Pastor Navarro, José Luis | Riquelme, Adrián | Cuevas-González, María | Crosetto, Michele | Barra, Anna | Monserrat, Oriol | Lopez-Sanchez, Juan M. | Ramón, Alfredo | Ivorra, Salvador | Del Soldato, Matteo | Solari, Lorenzo | Bianchini, Silvia | Raspini, Federico | Novali, Fabrizio | Ferretti, Alessandro | Costantini, Mario | Trillo, Francesco | Herrera García, Gerardo | Casagli, Nicola
Research Group/s: Ingeniería del Terreno y sus Estructuras (InTerEs) | Señales, Sistemas y Telecomunicación | Medio, Sociedad y Paisaje (MedSPai) | Planificación y Gestión Sostenible del Turismo | Grupo de Ensayo, Simulación y Modelización de Estructuras (GRESMES)
Center, Department or Service: Universidad de Alicante. Departamento de Ingeniería Civil | Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal | Universidad de Alicante. Departamento de Análisis Geográfico Regional y Geografía Física | Universidad de Alicante. Instituto Universitario de Investigación Informática
Keywords: Deformational processes | PSI | Pre-screening | Active Deformation Areas
Knowledge Area: Ingeniería del Terreno | Teoría de la Señal y Comunicaciones | Análisis Geográfico Regional | Mecánica de Medios Continuos y Teoría de Estructuras
Issue Date: 14-Jul-2019
Publisher: MDPI
Citation: Tomás R, Pagán JI, Navarro JA, Cano M, Pastor JL, Riquelme A, Cuevas-González M, Crosetto M, Barra A, Monserrat O, Lopez-Sanchez JM, Ramón A, Ivorra S, Del Soldato M, Solari L, Bianchini S, Raspini F, Novali F, Ferretti A, Costantini M, Trillo F, Herrera G, Casagli N. Semi-Automatic Identification and Pre-Screening of Geological–Geotechnical Deformational Processes Using Persistent Scatterer Interferometry Datasets. Remote Sensing. 2019; 11(14):1675. doi:10.3390/rs11141675
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 1:5000). 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.
Sponsor: This research was funded by the Shift2Rail Joint Undertaking under the European Union’s Horizon 2020 research and innovation program, with grant agreement No 777630, project MOMIT, “Multiscale Observation and Monitoring of railway Infrastructure Threats” and the Spanish Ministry of Economy, Industry and Competitiveness (MINECO), the State Agency of Research (AEI), and the European Funds for Regional Development (FEDER) under project TEC2017-85244-C2-1-P.
ISSN: 2072-4292
DOI: 10.3390/rs11141675
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
Peer Review: si
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Appears in Collections:INV - SST - Artículos de Revistas
INV - GRESMES - Artículos de Revistas
INV - MedSPai - Artículos de Revistas
INV - PGST - Artículos de Revistas
INV - INTERES - Artículos de Revistas
Research funded by the EU

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