Downscaling Passive Microwave Soil Moisture Estimates Using Stand-Alone Optical Remote Sensing Data

Downscaling of passive microwave derived soil moisture (SM) using thermal-infrared remote sensing data is a common method to obtain higher resolution SM information. However, these thermal-based downscaling methods are limited by their requirement of daily reparameterization because thermal-infrared data are influenced by both the SM content and weather conditions. To overcome these limitations, this study developed a new method called downscaling method based on optical trapezoid model (DespiTe), which improves the spatial resolution of passive microwave derived SM products by using only optical remote sensing data. This method relies on the linear relationship between SM and the shortwave-infrared transformed (STR) reflectance, which is less affected by weather conditions. Thus, the DespiTe method needs to be parameterized only once for each area. By establishing statistical relationships between optical parameters (normalized difference vegetation index (NDVI) and STR) and passive microwave derived SM observations, the DespiTe method enables a higher spatial resolution SM estimation to be derived. The downscaling results from DespiTe were evaluated with aircraft and in situ observed SM data acquired during the SMAPEx-4 and SMAPVEX16 field experiments. Moreover, these results were compared with those from disaggregation based on physical and theoretical scale change (DisPATCh), a commonly used thermal-based downscaling method. A comparison against aircraft SM data showed that the DespiTe method achieved an unbiased root-mean-square error (ubRMSE) of 0.026 m(3)/m(3), which outperformed the DisPATCh method that achieved a ubRMSE of 0.059 m(3)/m(3).