Development of a new vegetation modulated soil moisture index for the spatial disaggregation of SMAP soil moisture data product

Microwave remote sensing serves as a complementary tool for soil moisture mapping and monitoring in comparison to the optical and the infrared remote sensing. The key advantage of microwave remote sensing lies in its ability to estimate soil moisture irrespective of weather or atmospheric conditions. However, existing microwave passive soil moisture products are currently available only at a coarse spatial resolution, limiting their utility for various regional hydrological applications. Various studies have introduced different approaches to downscale these satellite soil moisture data products but the modulation of vegetation present on the soil surface is still a challenging task in the field of downscaling satellite soil moisture data products. Therefore, this study presents a novel vegetation-modulated soil moisture index developed by incorporating the MODIS (MODerate resolution Imaging Spectroradiometer) NDVI (Normalized Difference Vegetation Index), and LST (Land Surface Temperature). This newly derived index is then used to downscale the coarse resolution SMAP (Soil Moisture Active Passive) soil moisture data product. The proposed downscaling method has been validated using ground - measured soil moisture and compared with conventional downscaling approaches. It is found that the newly developed method, which has a bias error of −0.004 m3/m3 an Unbiased Root Mean Square Error (ubRMSE) of 0.068 m3/m3 of the downscaled soil moisture and demonstrates more intricate spatial variations.