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A spaceborne SAR-based procedure to support the detection of landslides / Giuseppe Esposito in Natural Hazards and Earth System Sciences, vol 20 n° 9 (September 2020)  

Public [article]  inNatural Hazards and Earth System Sciences > vol 20 n° 9 (September 2020) . - pp 2379 - 2395 Titre : A spaceborne SAR-based procedure to support the detection of landslides Type de document : Article/Communication Auteurs : Giuseppe Esposito, Auteur ; Ivan Marchesini, Auteur ; Alessandro Cesare Mondini, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 2379 - 2395 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] algorithme de décalage moyen [Termes IGN] cartographie des risques [Termes IGN] correction d'image [Termes IGN] détection de changement [Termes IGN] effondrement de terrain [Termes IGN] gestion des risques [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] ligne de rupture de pente [Termes IGN] modèle de simulation [Termes IGN] Papouasie-Nouvelle-Guinée [Termes IGN] risque naturel [Termes IGN] segmentation d'image [Termes IGN] traitement automatique de données Résumé : (auteur) The increasing availability of free-access satellite data represents a relevant opportunity for the analysis and assessment of natural hazards. The systematic acquisition of spaceborne imagery allows for monitoring areas prone to geohydrological disasters, providing relevant information for risk evaluation and management. In cases of major landslide events, for example, spaceborne radar data can provide an effective solution for the detection of slope failures, even in cases with persistent cloud cover. The information about the extension and location of the landslide-affected areas may support decision-making processes during emergency responses. In this paper, we present an automatic procedure based on Sentinel-1 Synthetic Aperture Radar (SAR) images, aimed at facilitating the detection of landslides over wide areas. Specifically, the procedure evaluates changes of radar backscattered signals associated with land cover modifications that may be also caused by mass movements. After a one-time calibration of some parameters, the processing chain is able to automatically execute the download and preprocessing of images, the detection of SAR amplitude changes, and the identification of areas potentially affected by landslides, which are then displayed in a georeferenced map. This map should help decision makers and emergency managers to organize field investigations. The process of automatization is implemented with specific scripts running on a GNU/Linux operating system and exploiting modules of open-source software. We tested the processing chain, in back analysis, on an area of about 3000 km2 in central Papua New Guinea that was struck by a severe seismic sequence in February–March 2018. In the area, we simulated a periodic survey of about 7 months, from 12 November 2017 to 6 June 2018, downloading 36 Sentinel-1 images and performing 17 change detection analyses automatically. The procedure resulted in statistical and graphical evidence of widespread land cover changes that occurred just after the most severe seismic events. Most of the detected changes can be interpreted as mass movements triggered by the seismic shaking. Numéro de notice : A2020-611 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5194/nhess-20-2379-2020 Date de publication en ligne : 10/09/2020 En ligne : https://doi.org/10.5194/nhess-20-2379-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95976 [article]