Evaluate usage of decomposition technique in estimation of soil moisture with vegetated surface by multi-temporal measurements

Active microwave remote sensing as an important tool for soil physical properties. Despite the promise, its application to hydrological and agricultural sciences has been hampered by natural variability and the complexity of the vegetation canopy and surface roughness that significantly affect the sensitivity of radar backscattering to soil moisture. An operational algorithm for mapping soil moisture distribution has not been developed because of the effects of surface roughness and vegetation cover. The inversion of soil moisture information from radar backscatter became more rigorous after the availability of multi-polarization radar data. Several algorithms have been developed for measuring bare surface soil moisture quantitatively using either dual-polarization L-band SAR image data or three-polarization SAR measurements. The algorithms had been applied to a series of L-band SIR-C and JPL/AIRSAR image data successfully by using VV and HH polarization. However, all those algorithms were under the surface scattering consideration. They used the weighted combinations of the different polarization signatures to minimize the effect of surface roughness so that soil moisture can be directly inferred from SAR image data. The effect of vegetation cover has not been included in current available algorithms. It is clear that vegetation cover will cause an under-estimation of soil moisture and an overestimation of surface roughness when the authors apply the algorithm for bare surface soil moisture estimation to vegetation covered regions.