A global 400-m high-resolution soil moisture dataset derived from multi-sensor remote sensing observations

Soil Moisture (SM) has been monitored by satellite remote sensing for the past five decades. Among recent missions, the Soil Moisture Active Passive (SMAP) mission, launched by the National Aeronautics and Space Administration's (NASA), has been providing high-quality global SM observations from an L-band passive microwave radiometer with a revisit time of 1-2 days, although its spatial resolution remains on the order of tens of kilometers. To address this limitation, an algorithm was developed and applied to downscale the SMAP enhanced Level-2 radiometer half-orbit SM product from 9 km to 400 m resolution by incorporating land surface temperature (LST) and leaf area index (LAI) products from the Visible Infrared Imaging Radiometer Suite (VIIRS). The 400 m downscaled SM product was validated against in situ observations acquired from the International Soil Moisture Network (ISMN) and compared with both 1 km downscaled and original 9 km SMAP products. Overall, the 400 m product outperformed the other two in terms of Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). It also revealed finer-scale spatial patterns of SM supporting local and regional hydrological applications.