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  • 标题:A spaceborne SAR-based procedure to support the detection of landslides
  • 本地全文:下载
  • 作者:Esposito, Giuseppe ; Marchesini, Ivan ; Mondini, Alessandro Cesare
  • 期刊名称:Natural Hazards and Earth System Sciences
  • 电子版ISSN:2195-9269
  • 出版年度:2020
  • 卷号:20
  • 期号:9
  • 页码:2379-2395
  • DOI:10.5194/nhess-20-2379-2020
  • 语种:English
  • 出版社:Copernicus Publications
  • 摘要: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 thedetection of slope failures, even in cases with persistent cloud cover. Theinformation 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-1Synthetic Aperture Radar (SAR) images, aimed at facilitating the detection oflandslides 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 someparameters, the processing chain is able to automatically execute thedownload and preprocessing of images, the detection of SAR amplitudechanges, 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.
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