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Landslide detection, monitoring and prediction with remote-sensing techniques

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NATURE REVIEWS EARTH & ENVIRONMENT
卷 4, 期 1, 页码 51-64

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SPRINGERNATURE
DOI: 10.1038/s43017-022-00373-x

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This article discusses the use of remote sensing technology in detecting, monitoring, and predicting landslides. It highlights the importance of these activities in managing landslide risks, especially when they occur near human settlements and infrastructure. Various remote sensing techniques, such as satellite observation and ground-based sensors, provide valuable information for landslide analysis and management.
Detection, monitoring and prediction are essential to managing landslide risks. This Technical Review examines the use of remote-sensing technology in tracking landslides and mitigating disaster. Landslides are widespread occurrences that can become catastrophic when they occur near settlements and infrastructure. Detection, monitoring and prediction are fundamental to managing landslide risks and often rely on remote-sensing techniques (RSTs) that include the observation of Earth from space, laser scanning and ground-based interferometry. In this Technical Review, we describe the use of RSTs in landslide analysis and management. Satellite RSTs are used to detect and measure landslide displacement, providing a synoptic view over various spatiotemporal scales. Ground-based sensors (including ground-based interferometric radar, Doppler radar and lidar) monitor smaller areas, but combine accuracy, high acquisition frequency and configuration flexibility, and are therefore increasingly used in real-time monitoring and early warning of landslides. Each RST has advantages and limitations that depend on the application (detection, monitoring or prediction), the size of the area of concern, the type of landslide, deformation pattern and risks posed by landslide. The integration of various technologies is, therefore, often best. More effective landslide risk management requires greater leveraging of big data, more strategic use of monitoring resources and better communication with residents of landslide-prone areas.

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