Monitoring the Jianshanying landslide in a karst mountainous area of Guizhou by optical remote sensing
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摘要: 文章选取贵州省发耳镇尖山营采矿型滑坡为研究对象,利用多期光学遥感数据,基于亚像元相关性匹配技术,实现该滑坡长时序定量化二维形变监测。利用多期存档Google earth影像及无人机影像,探测出该地区1#滑坡在2013年已开始发生明显的地表形变,且随着时间的推移,地表形变愈发严重;再基于Sentinel-2遥感数据求解出1#滑坡自2016年7月31日至2020年3月22日期间的二维形变时间序列,结果表明:该滑坡最大水平形变方向与斜坡方向一致,且在东西向和南北向上均表现为持续增大的趋势,最大累积形变量分别达到了44 m和-58 m。Abstract: Landslides in karst mountainous areas of southwest China induced by underground mining can cause huge economic losses and casualties. Such hazard is characterized by large deformation gradients and serious collapse of the surface. This work takes the Jianshanying mining-induced landslide as an example to realizes the quantitative 2D time-series deformation monitoring of the landslide by optical sub-pixel correlation methods based on multiple optical images. First, multiple historical archives of Google earth images and UAV images are used to detect the damage of the surface, showing that the 1# landslide area has undergone significant surface deformation in 2013, becoming increasingly serious over time. Then, the 2D deformation time series of the 1# landslide area from July 31, 2016 to March 22, 2020 is inverted based on the Sentinel-2 data. Results indicate that the horizontal deformation in this area tended to be larger in the slope direction as well as in the east-west and north-south directions over time. The deformation continued to increase over time, and the maximum cumulative deformation reached 44 m and -58 m, respectively. Therefore, the large-gradient deformation monitoring of the landslide disaster in Guizhou karst mountainous areas can be realized by using optical remote sensing technology, which is important to the monitoring and early warning of landslides in similar areas.
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Key words:
- landslide /
- optical remote sensing /
- correlation /
- 2D deformation /
- time-series monitoring
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