The project will provide a collection of EO, climate and epidemiological datasets designed to support research, policy analysis, and decision-making in the climate–health domain. All datasets, algorithms, and documentation will be made available through our two-official open-science communities:
These two platforms ensure full transparency, traceability, and long-term preservation of the project’s outputs. Each dataset published in Zenodo will follow a consistent metadata structure, enabling users to understand the spatial and temporal coverage, methodology, variables, and limitations of each product.
Each dataset will include a title in the format:
Title: Dataset name – Location, Date
(e.g., EO-based flooding maps – South Sudan, 2012–2024)
Followed by a structured description using the table below:
| Field Name | Example Description |
|---|---|
| Use Case Name | Name and focus area of the use case (e.g., Flooding and health care service disruption in South Sudan). |
| Dataset Name | Descriptive title (e.g., EO-based flooding maps). |
| Dataset Description | Detailed description of dataset content, purpose, and methodology (e.g., Dataset covering 2012–2024 providing flood maps derived from VIIRS 375 m/pixel water fraction products. Flood extent is downscaled to 90 m using a hydrologically conditioned DEM and HAND algorithm. Each layer represents a 5-day composite.) |
| Temporal Domain | Time range covered (e.g., 2012–2024). |
| Spatial Domain | Geographic area, resolution, and coordinate system (e.g., South Sudan, 90 m, WGS84). |
| Key Variables / Indicators | Main variables represented (e.g., surface water extent, flood frequency). |
| Data Format | Dataset file type (e.g., GeoTIFF, netCDF, CSV, Shapefile). |
| Source Data | Input datasets used (e.g., VIIRS, Sentinel-1, HydroDEM, ERA5). |
| Limitations / Assumptions | Important caveats (e.g., VIIRS resolution limits detection of small inundated areas; cloud cover may reduce accuracy; mixed pixels introduce uncertainty along flood boundaries.) |