A Method for Spatial Downscaling of Satellite Soil Moisture Products Using ATI-LAI Space

Soil moisture is of great importance for regional hydrological studies such as agricultural management and drought prediction, but those applications usually require a high spatial resolution of 1-10 kilometers. To improve the spatial resolution of satellite soil moisture products, this paper constructs a soil moisture downscaling method in Apparent Thermal Inertia- Leaf Area Index (ATI-LAI) space using an improved automatic edge determination algorithm. The effectiveness and robustness of the method are validated by the Australian Soil Moisture Monitoring Network and ESA Climate Change Initiative (ESA CCI) soil moisture data. By comparing with in situ SM measurements and the spatial patterns of the CCI SM, the R of the downscaled 1km SM reaches 0.694 with a bias of 0.027. The results show that the downscaled 1km SM significantly improves the spatial details of the CCI SM while replicating the accuracy of the CCI SM, and demonstrating fine-scale spatial variability.