Fusion Analysis of Optical Satellite Images and Digital Elevation Model for Quantifying Volume in Debris Flow Disaster
Fusion Analysis of Optical Satellite Images and Digital Elevation Model for Quantifying Volume in Debris Flow Disaster
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DOI：
10.3390/rs11091096
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发表时间：
2019-05
期刊：
影响因子：
--
通讯作者：
H. Miura
中科院分区：
文献类型：
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作者：
H. Miura
快速识别大规模泥石流灾害的受影响区域和体积对于早期恢复和泥石流管理规划非常重要。本研究介绍了一种光学卫星图像和数字高程模型 (DEM) 融合分析的方法，用于简化泥石流事件中体积的量化。本研究对 2018 年 7 月日本广岛泥石流灾害影响的 LiDAR 数据、Sentinel-2 事件前后图像以及事件前 DEM 进行了分析。泥石流侵蚀深度是根据事件前和事件后 LiDAR 衍生的 DEM 进行经验建模的。通过提供预定义的源，通过卫星图像的变化检测和基于 DEM 的泥石流传播分析来检测侵蚀区域。通过乘以经验侵蚀深度，根据检测到的侵蚀区域来估计体积及其模式。体积估计的结果与 LiDAR 得出的体积非常吻合。
Rapid identification of affected areas and volumes in a large-scale debris flow disaster is important for early-stage recovery and debris management planning. This study introduces a methodology for fusion analysis of optical satellite images and digital elevation model (DEM) for simplified quantification of volumes in a debris flow event. The LiDAR data, the pre- and post-event Sentinel-2 images and the pre-event DEM in Hiroshima, Japan affected by the debris flow disaster on July 2018 are analyzed in this study. Erosion depth by the debris flows is empirically modeled from the pre- and post-event LiDAR-derived DEMs. Erosion areas are detected from the change detection of the satellite images and the DEM-based debris flow propagation analysis by providing predefined sources. The volumes and their pattern are estimated from the detected erosion areas by multiplying the empirical erosion depth. The result of the volume estimations show good agreement with the LiDAR-derived volumes.