Remote Sensing of Landslides—A Review
Triggered by earthquakes, rainfall, or anthropogenic activities, landslides represent widespread and problematic geohazards worldwide. In recent years, multiple remote sensing techniques, including synthetic aperture radar, optical, and light detection and ranging measurements from spaceborne, airbo...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-02-01
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| Series: | Remote Sensing |
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| Online Access: | http://www.mdpi.com/2072-4292/10/2/279 |
| _version_ | 1819289126467272704 |
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| author | Chaoying Zhao Zhong Lu |
| author_facet | Chaoying Zhao Zhong Lu |
| author_sort | Chaoying Zhao |
| collection | DOAJ |
| description | Triggered by earthquakes, rainfall, or anthropogenic activities, landslides represent widespread and problematic geohazards worldwide. In recent years, multiple remote sensing techniques, including synthetic aperture radar, optical, and light detection and ranging measurements from spaceborne, airborne, and ground-based platforms, have been widely applied for the analysis of landslide processes. Current techniques include landslide detection, inventory mapping, surface deformation monitoring, trigger factor analysis and mechanism inversion. In addition, landslide susceptibility modelling, hazard assessment, and risk evaluation can be further analyzed using a synergic fusion of multiple remote sensing data and other factors affecting landslides. We summarize the 19 articles collected in this special issue of Remote Sensing of Landslide, in the terms of data, methods and applications used in the papers. |
| first_indexed | 2024-12-24T03:01:54Z |
| format | Article |
| id | doaj.art-674786d3223f4e3e95c2295bd94b9b40 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-24T03:01:54Z |
| publishDate | 2018-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-674786d3223f4e3e95c2295bd94b9b402022-12-21T17:18:10ZengMDPI AGRemote Sensing2072-42922018-02-0110227910.3390/rs10020279rs10020279Remote Sensing of Landslides—A ReviewChaoying Zhao0Zhong Lu1School of Geology Engineering and Geomatics, Chang’an University, No. 126, Yanta Road, Xi’an 710054, ChinaHuffington Department of Earth Sciences, Southern Methodist University, P.O. Box 750395, Dallas, TX 75275, USATriggered by earthquakes, rainfall, or anthropogenic activities, landslides represent widespread and problematic geohazards worldwide. In recent years, multiple remote sensing techniques, including synthetic aperture radar, optical, and light detection and ranging measurements from spaceborne, airborne, and ground-based platforms, have been widely applied for the analysis of landslide processes. Current techniques include landslide detection, inventory mapping, surface deformation monitoring, trigger factor analysis and mechanism inversion. In addition, landslide susceptibility modelling, hazard assessment, and risk evaluation can be further analyzed using a synergic fusion of multiple remote sensing data and other factors affecting landslides. We summarize the 19 articles collected in this special issue of Remote Sensing of Landslide, in the terms of data, methods and applications used in the papers.http://www.mdpi.com/2072-4292/10/2/279landslideremote sensingdeformationdetectionsusceptibility modelling |
| spellingShingle | Chaoying Zhao Zhong Lu Remote Sensing of Landslides—A Review Remote Sensing landslide remote sensing deformation detection susceptibility modelling |
| title | Remote Sensing of Landslides—A Review |
| title_full | Remote Sensing of Landslides—A Review |
| title_fullStr | Remote Sensing of Landslides—A Review |
| title_full_unstemmed | Remote Sensing of Landslides—A Review |
| title_short | Remote Sensing of Landslides—A Review |
| title_sort | remote sensing of landslides a review |
| topic | landslide remote sensing deformation detection susceptibility modelling |
| url | http://www.mdpi.com/2072-4292/10/2/279 |
| work_keys_str_mv | AT chaoyingzhao remotesensingoflandslidesareview AT zhonglu remotesensingoflandslidesareview |