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Landslide Susceptibility Mapping using Remotely Sensed Soil Moisture

机译:使用远程感测土壤湿度的滑坡易感性测绘

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Slope stability analysis using remotely sensed data is routinely conducted throughout the world. This study focuses on rainfall induced landslides and the use of AMSR-E and TRMM satellite data to develop susceptibility maps that can be used to forecast landslides. This research established the first relationships among soil moisture derived from AMSR-E, precipitation from TRMM and major landslide events, respectively, in California, U.S., Leyte, Philippines and, Dhading, Nepal. Each of the three study regions had slope movements when soil moisture was high and rainfall occurred and clearly indicates a strong relationship among landslide events, remotely sensed soil moisture and rainfall. A slope stability model is used to develop susceptibility maps for a California site under a range of conditions. Results suggest that the AMSR-E and TRMM satellite data, coupled with land-surface model estimates, are viable for enhancing rainfall induced slope stability analysis at regional or global scales.
机译:使用远程感测数据的斜率稳定性分析是常规的全世界进行的。本研究重点介绍降雨诱导山体滑坡和AMSR-E和TRMM卫星数据的使用,以开发可用于预测山体滑坡的易感性图。本研究在加州,美国,莱特,菲律宾和尼泊尔Dhading,尼泊尔,尼泊尔分别建立了来自AMSR-E的土壤水分,降水和重大滑坡事件的第一个关系。当土壤水分高降雨并发生降雨并清楚地表明滑坡事件中的巨大关系,遥感土壤水分和降雨时,这三个研究区域都有斜坡运动。坡度稳定性模型用于在一系列条件下开发加利福尼亚植物的易感性图。结果表明,与土地面模型估算相结合的AMSR-E和TRMM卫星数据可用于增强区域或全球尺度的降雨诱导的坡稳定性分析。

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