Next Article in Journal
New ECOSTRESS and MODIS Land Surface Temperature Data Reveal Fine-Scale Heat Vulnerability in Cities: A Case Study for Los Angeles County, California
Previous Article in Journal
Estimating 3D Chlorophyll Content Distribution of Trees Using an Image Fusion Method Between 2D Camera and 3D Portable Scanning Lidar
Open AccessArticle

New Perspectives in Landslide Displacement Detection Using Sentinel-1 Datasets

Italian National Research Council (CNR), Research Institute for Geo-Hydrological Protection (IRPI), Corso Stati Uniti 4, 35127 Padova, Italy
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;
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
Show Figures

Graphical abstract

MDPI and ACS Style

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.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Search more from Scilit
Back to TopTop