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Landslide susceptibility mapping using downscaled AMSR-E soil moisture: a case study from Cleveland Corral, California, US
- Ray, Ram L., Jacobs, Jennifer M., Cosh, Michael H.
- Remote sensing of environment 2010 v.114 no.11 pp. 2624
- landslides, soil water content, prediction, slope, soil stabilization, remote sensing, radiometry, satellites, mathematical models, equations, California
- As soil moisture increases, slope stability decreases. Remotely sensed soil moisture data can provide routine updates of slope conditions necessary for landslide predictions. For regional scale landslide investigations, only remote-sensing methods have the spatial and temporal resolution required to map hazard increases. Here, a dynamic physically-based slope stability model that requires soil moisture is applied using remote-sensing products from multiple Earth observing platforms. The resulting landslide susceptibility maps using the advanced microwave scanning radiometer (AMSR-E) surface soil moisture are compared to those created using variable infiltration capacity (VIC-3L) modeled soil moisture at Cleveland Corral landslide area in California, US. Despite snow cover influences on AMSR-E surface soil moisture estimates, a good relationship between the downscaled AMSR-E's surface soil moisture and the VIC-3L modeled soil moisture is evident. The AMSR-E soil moisture mean (0.17 cm3/cm3) and standard deviation (0.02 cm3/cm3) are very close to the mean (0.21 cm3/cm3) and standard deviation (0.09 cm3/cm3) estimated by VIC-3L model. Qualitative results show that the location and extent of landslide prone regions are quite similar. Under the maximum saturation scenario, 0.42% and 0.49% of the study area were highly susceptible using AMSR-E and VIC-3L model soil moisture, respectively.