Sentinel-1 SAR数据在四川茂县山体滑坡灾害监测中的应用研究

星载合成孔径雷达具有全天候、全天时、实时性和宽覆盖的观测特征,在滑坡灾害快速监测中具有独特优势。为此,本文针对2017年6月24日四川茂县遭遇的严重滑坡灾害,开展基于灾中Sentinel-1 SAR数据的滑坡体范围提取的应用研究。首先,通过分析森林区和滑坡区的雷达微波后向散射机理,提出基于VV极化和VH极化的雷达比值指数法;然后,结合灾前灾中两时相Sentinel-1 SAR影像,分析非滑坡区与滑坡区后向散射强度变化特征和基于雷达比值指数法提取滑坡体的合理性;最后,针对灾中Sentinel-1 SAR数据,运用雷达比值指数法进行滑坡范围的快速提取,实现滑坡灾害的监测。结果显示,基于Sentinel-1 SAR数据快速提取的茂县滑坡体面积达1.3 km2,斜向滑动距离约为2378 m;山体滑坡导致新磨村受灾严重,房屋完全被毁。研究表明,雷达比值指数能够显著的突出滑坡体的图像特征,该方法在针对Sentinel-1 SAR的滑坡提取与监测上具有较大的应用潜力和优势。

Research on the application of Sentinel-1 SAR data in monitoring of landslide disaster in Maoxian County Sichuan

Synthetic Aperture Radar is with observation characteristics of full time, all day, real time and wide coverage, which has unique advantage in fast monitoring of landslide disaster. Therefore, based on the serious landslide disaster in Maoxian County, Sichuan Province on June 24, 2017, this paper conducts the application research of landslide range extraction based on the Sentinel-1 SAR data in the disaster. First,by analyzing the radar backscattering mechanism of forest area and landslide area,the radar ratio index method is proposed based on VV polarization and VH polarization. Then,combining the two-phase Sentinel-1 SAR images before and during the disaster,the features of backscattering intensity change are investigated,and the rationality of extracting landslide mass by the radar ratio index method is verified. Finally, for the Sentinel-1 SAR data in the disaster, the radar ratio index method is adopted for the rapid extraction of landslide range and the monitoring of landslide disaster. The results show that the Maoxian landslide area is 1.3 km² and the inclined sliding distance is about 2378m by performing the rapid extraction of Sentinel-1 SAR data. The landslide caused the serious damage to Xinmo village and the houses were completely destructed. The research shows that the radar ratio index can significantly characterize the image features of the landslide mass. This method presents great potential and advantages in landslide extraction and monitoring by Sentinel-1 SAR.