An Automatic Identification Method of Geohazard Risk Area Based On Improved Hot Spot Analysis Within Insar Results

2023 SAR in Big Data Era (BIGSARDATA)(2023)

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摘要
Geohazard risk areas are difficult to identify automatically without prior information. In general, the greater the deformation rate, the higher the risk of geological hazards. But the absolute value of the deformation rate to judge whether risk will occur varies from place to place. Therefore, a relative risk identification method based on improved hot spot analysis (IHSA) is applied to identify the risk areas from InSAR deformation results. The key to IHSA is to combine hotspot analysis with density-based spatial clustering. So, the areas with high deformation rates InSAR points clustered together are identified as risk areas. InSAR results in this paper were generated using 38 Sentinel-1 SAR images from Jan 2019 to Apr 2020 in the North China region. 484,082 InSAR measurement points (MPs) were extracted over the area of interest (AOI). With IHSA, 4469 MPs were identified as high-risk points.
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关键词
InSAR,geohazard risk identification,hotspot analysis
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