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Open AccessArticle

New Perspectives in Landslide Displacement Detection Using Sentinel-1 Datasets

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Italian National Research Council (CNR), Research Institute for Geo-Hydrological Protection (IRPI), Corso Stati Uniti 4, 35127 Padova, Italy
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Department of Civil, Chemical, Environmental and Materials Engineering DICAM, Alma Mater Studiorum Università di Bologna, Viale Risorgimento 2, 40136 Bologna, Italy
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(18), 2135; https://doi.org/10.3390/rs11182135
Received: 26 June 2019 / Revised: 9 September 2019 / Accepted: 11 September 2019 / Published: 13 September 2019
(This article belongs to the Section Remote Sensing in Geology, Geomorphology and Hydrology)
Space-borne radar interferometry is a fundamental tool to detect and measure a variety of ground surface deformations, either human induced or originated by natural processes. Latest development of radar remote sensing imaging techniques and the increasing number of space missions, specifically designed for interferometry analyses, led to the development of new and more effective approaches, commonly referred to as Advanced DInSAR (A-DInSAR) or Time Series Radar Interferometry (TS-InSAR). Nevertheless, even if these methods were proved to be suitable for the study of a large majority of ground surface dynamic phenomena, their application to landslides detection is still problematic. One of the main limiting factors is related to the rate of displacement of the unstable slopes: landslides evolving too fast decorrelate the radar signal making the interferometric phase useless. This is the reason why A-DInSAR techniques have been successfully applied exclusively to measure very slow landslides (few centimetres per year). This study demonstrates how the C-band data collected since 2014 by the Sentinel-1 (S1) mission and properly designed interferometric approaches can pull down this restriction allowing to measure rate of displacements ten times higher than previously done, thus providing new perspectives in landslides detection. The analysis was carried out on a test site located in the Cortina d’Ampezzo valley (Eastern Italian Alps), which is affected by several earth flows characterized by different size and kinematics. View Full-Text
Keywords: landslide; monitoring; A-DInSAR; Sentinel-1; Cortina d’Ampezzo landslide; monitoring; A-DInSAR; Sentinel-1; Cortina d’Ampezzo
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Mantovani, M.; Bossi, G.; Marcato, G.; Schenato, L.; Tedesco, G.; Titti, G.; Pasuto, A. New Perspectives in Landslide Displacement Detection Using Sentinel-1 Datasets. Remote Sens. 2019, 11, 2135.

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