Multi-source Remote Sensing and Ground-based Soil Moisture Data for Agricultural Applications across Three Watersheds: Mississippi River Basin, Shandian River Basin, and Douro River Basin (2016-2019)

This dataset contains processed remote sensing features and ground-based soil moisture measurements used for agricultural soil moisture retrieval across three environmentally diverse watersheds. The dataset includes:

Study Areas:
- Mississippi River Basin, USA (humid subtropical climate)
- Shandian River Basin, China (temperate continental climate)
- Douro River Basin, Portugal (Mediterranean climate)

Data Components:
1. Ground-based soil moisture measurements (0-5 cm depth) from SCAN, SMN-SDR, and REMEDHUS networks
2. Sentinel-1 SAR backscatter coefficients (VV/VH polarizations)
3. Sentinel-2 derived vegetation indices (NDVI, NDWI)
4. Topographic features from SRTM DEM (DEM, RMSH,meanDEM)
5. Soil texture data (clay and sand content)

Time Period: 2016-2019
Spatial Resolution: 10-30 meters
Applications: Precision agriculture, soil moisture monitoring, machine learning model development

The dataset supports research on environment-algorithm relationships for agricultural soil moisture retrieval and precision irrigation applications.