Landslide Forecasting Using Microwave Remote Sensing

Landslides, a natural disaster, are becoming more common in mountainous region of many countries. A dynamic physically-based slope stability model that requires soil moisture or wetness index can be driven by remote sensing products from multiple Earth observing platforms. While satellite remote sensing (e.g., AMSR-E and TRMM satellite data) can measure surface soil moisture, land surface model can estimate the soil moisture profile. This research compares AMSR-E surface soil moisture with the variable infiltration capacity (VIC-3L) model's soil moisture at Cleveland Corral landslide area in California, USA from 2003 to 2006. Snow cover influences on AMSR-E surface soil moisture estimate are also examined. The results show a strong relationship among AMSR-E's surface soil moisture, modeled soil moisture and in situ pore water pressure measurements. Preliminary results show that the AMSR-E satellite data, coupled with VIC model estimates, are viable for rainfall induced slope stability analysis at regional or global scales. Keywords: Landslide, AMSR-E, TRMM, Remote Sensing, VIC, Soil Moisture