The project started in April 2023/04 and was completed at the end of April 2024/04 as a result of 1 year of work. As one of the outputs of the rapid support project, the article "A novel land surface temperature reconstruction method and its application for downscaling surface soil moisture with machine learning" was published in the Journal of Hydrology.
At the current stage, using the link given below, you can use the raw data of the study area; You can download GIS maps, SoilGrid soil properties (Sand, Clay, Silt), precipitation data sets obtained from different sources (MSWEP, IMERG etc.), ESRI 2022 LULC, Surface Soil Temperature (LST) and original SMAP surface soil moisture data.
You can access the daily 1 km LST maps and downscaled SMAP L3 and SMAP L4 maps, which are the output of the project, from the link below. The data was stored in netcdf format and shared for the years 2019-2022.