USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES
Title: Landslide susceptibility mapping using downscaled AMSR-E soil moisture: A case study from Cleveland Corral, California, US
Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: August 1, 2010
Publication Date: September 8, 2010
Citation: Ray, R., Jacobs, J., Cosh, M.H. 2010. Landslide susceptibility mapping using downscaled AMSR-E soil moisture: A case study from Cleveland Corral, California, US. Remote Sensing of Environment. 114:2624-2636.
Interpretive Summary: Land slides are a costly natural disaster which is often sudden and unpredictiable because of the lack of available data. Slope stability modeling is the key to quantifying potential landslide locations, which is critical for areas prone to landslides, such as Nepal, or California. However a key component to stability modeling, soil moisture, is lacking in situ data to support large scale monitoring. An alternate method of soil moisture estimation, remote sensing, has been developed via the AMSR-E satellite instrument. Using estimates from this sensor, slope stability maps can be generated which closely match maps generated from intensive modeling schemes, namely the VIC-3L model. At a study site at Cleveland Corral landslide Area in California, the utility of the AMSR-E approach to landslide estimation proved that satellite remote sensing can be used to quickly assess the susceptibility of a region for landslides.
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 AMSRE 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 was highly susceptible using AMSR-E and VIC-3L model soil moisture, respectively.