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Article

A Methodology to Detect and Update Active Deformation Areas Based on Sentinel-1 SAR Images

1
Centre Tecnològic de Telecomunicacions de Catalunya (CTTC/CERCA), Geomatics Division, 08860 Castelldefels, Spain
2
Earth Sciences Department, University of Firenze, Via La Pira, 4, I-50121 Firenze, Italy
3
Geohazards InSAR Laboratory and Modeling Group (InSARlab), Geoscience Research Department, Geological Survey of Spain (IGME), Alenza 1, 28003 Madrid, Spain
4
Centro Nacional de Información Geográfica, Instituto Geográfico Nacional, C/General Ibáñez de Ibero, 3, 28003 Madrid, Spain
5
Geological Survey of Spain (IGME), Urb. Alcázar del Genil, 4-Edif. Bajo, 18006 Granada, Spain
*
Author to whom correspondence should be addressed.
Remote Sens. 2017, 9(10), 1002; https://doi.org/10.3390/rs9101002
Received: 4 August 2017 / Revised: 12 September 2017 / Accepted: 21 September 2017 / Published: 28 September 2017
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
This work is focused on deformation activity mapping and monitoring using Sentinel-1 (S-1) data and the DInSAR (Differential Interferometric Synthetic Aperture Radar) technique. The main goal is to present a procedure to periodically update and assess the geohazard activity (volcanic activity, landslides and ground-subsidence) of a given area by exploiting the wide area coverage and the high coherence and temporal sampling (revisit time up to six days) provided by the S-1 satellites. The main products of the procedure are two updatable maps: the deformation activity map and the active deformation areas map. These maps present two different levels of information aimed at different levels of geohazard risk management, from a very simplified level of information to the classical deformation map based on SAR interferometry. The methodology has been successfully applied to La Gomera, Tenerife and Gran Canaria Islands (Canary Island archipelago). The main obtained results are discussed. View Full-Text
Keywords: SAR; DInSAR; deformation; measurement; landslide; subsidence; risk management SAR; DInSAR; deformation; measurement; landslide; subsidence; risk management
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MDPI and ACS Style

Barra, A.; Solari, L.; Béjar-Pizarro, M.; Monserrat, O.; Bianchini, S.; Herrera, G.; Crosetto, M.; Sarro, R.; González-Alonso, E.; Mateos, R.M.; Ligüerzana, S.; López, C.; Moretti, S. A Methodology to Detect and Update Active Deformation Areas Based on Sentinel-1 SAR Images. Remote Sens. 2017, 9, 1002. https://doi.org/10.3390/rs9101002

AMA Style

Barra A, Solari L, Béjar-Pizarro M, Monserrat O, Bianchini S, Herrera G, Crosetto M, Sarro R, González-Alonso E, Mateos RM, Ligüerzana S, López C, Moretti S. A Methodology to Detect and Update Active Deformation Areas Based on Sentinel-1 SAR Images. Remote Sensing. 2017; 9(10):1002. https://doi.org/10.3390/rs9101002

Chicago/Turabian Style

Barra, Anna, Lorenzo Solari, Marta Béjar-Pizarro, Oriol Monserrat, Silvia Bianchini, Gerardo Herrera, Michele Crosetto, Roberto Sarro, Elena González-Alonso, Rosa M. Mateos, Sergio Ligüerzana, Carmen López, and Sandro Moretti. 2017. "A Methodology to Detect and Update Active Deformation Areas Based on Sentinel-1 SAR Images" Remote Sensing 9, no. 10: 1002. https://doi.org/10.3390/rs9101002

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