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)
Description
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.
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Institutions
- Henan Polytechnic University