SWATI-Based Global Monthly Dryness-Wetness Dataset (Part 1: 03/2000–12/2006)

Overview: Accurate drought assessment is crucial for optimizing water distribution and irrigation planning, particularly in the context of climate change. However, existing remote sensing datasets often lack the necessary spatial resolution to analyze dryness-wetness (DW) conditions. This collection is part 1 of the global 1km monthly DW dataset based on the Surface Water Availability-Temperature Index (SWATI) during 2000–2006. It contains global DW monitoring data derived from the SWATI, which integrates three variables (i.e., Normalized Difference Latent Heat Index (NDLI), Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST)) using the Euclidean distance method. The SWATI values typically range from 0 to 1, with lower values indicating wetter states and higher values reflecting drier conditions.

Key Features
- Superior DW monitoring capabilities compared to existing indices
- Extensively validated against multiple datasets including: Site-based soil moisture (SM) and latent heat flux (LE), Global Land Surface Satellite (GLASS) SM, FEWS NET Land Data Assimilation System (FLDAS) SM, Moderate Resolution Imaging Spectroradiometer (MODIS) evapotranspiration (ET)

Data Specifications
- Spatial and Temporal Resolution: 1 km/Monthly
- Spatial Coverage: Global
- File Format: GeoTIFF

For data covering other time periods, please refer to the related datasets:
- Part 2: https://doi.org/10.5281/zenodo.15354026 (2007–2013)
- Part 3: https://doi.org/10.5281/zenodo.15354273 (2014–2020)
- Part 4: https://doi.org/10.5281/zenodo.15355139 (2021–2024)