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Estimated soil moisture in vegetated area using multitemporal multipolarization data

Alpine ecosystem is the most sensitive terrestrial ecosystem to global climate change. Recently, a dwarf bamboo species, Sasa kurilensis, (Poaceae), has invaded into alpine snow-meadows in the wilderness area of the Taisetsu Mountains, northern Japan. The spatial distribution and seasonal changes in soil moistures are key parameter in numerous environmental studies at both regional and global scales including hydrological, ecological, climatic and agricultural fields. However, the natural variability and complexity of vegetation canopy and surface roughness significantly affect the sensitivity of backscatter from soil. This study indicates a new method to estimate surface soil moisture in high density vegetated area in the Taisetsu Mountains with an L-band dual-polarization (HH and HV) radiometer measurements. For dense vegetated surfaces, we used the multitemporal and multipolarization backscatter coefficient data and the subtraction methods to provide the estimation of vegetation effects. After the soil moisture corrected based on vegetation phenology, the surface soil moisture can be inferred by the estimated surface backscatter signals.