Sub-canopy Inundation in the Amazon and Congo Rainforests

This dataset accompanies a yet unpublished work on the extent and frequency of flooding under the dense canopies of the Amazon and Congo rainforests (link to pre-print). CONTENT For each rainforest (Amazon and Congo), the following files are provided: regions_boundaries.geojson Partitioning of our area of interest into 20 hydrologically-consistent regions. Column "cluster" indicates the identifier of the region (0 to 19). seasonal_curves_regions.csv Values represent mean-centered seasonal water level dynamics, in meters. Derived from an aggregation of satellite altimetry virtual stations. Column "date" corresponds to the day of the year from 0 (January 1st) to 364 (December 31st) Other columns correspond to the different regions (0 to 19). flooded_forest_probability.tif 0-100 : probability to correspond to a flooded forest from 0% : not flooded at high water (high confidence) to 100% : flooded at high water (high confidence) -1 : masked out for one of the following reasons unforested tree cover < 50% according to Copernicus Land Cover (DOI) average HV backscatter on 2025 (PALSAR-2) lower than 2,800 steep slopes slope (rise over run) higher than 15%, after gaussian smoothing (Copernicus GLO-30) -2 : outside AOI boundaries subcanopy_flood_frequency.tif 0-4 : number of river-stages for which the deviation is consistent with the radar signature of flooded forests. from 0 (out of 4), the pixel does present a radar signature consistent with flooding, even at high water to 4 (out of 4), the pixel does present a radar signature consistent with flooding for all four river-stages -1 : masked out (unforested or steep slopes), or outside of AOI boundaries. CITATION If you use this dataset, please cite the Zenodo DOI associated with this repository. CONTACT Users are advised to consult the associated publication for methodological details.For questions regarding the dataset or its use, please contact the corresponding author: Paul Senty, e-mail: [e-mail] ACKNOWLEDGMENTS This work was supported by the Novo Nordisk Foundation (Global Wetland Center, grant NNF23OC0081089). The authors thank the Japan Aerospace Exploration Agency (JAXA) for providing free access to ALOS-2 PALSAR-2 ScanSAR data, Google Earth Engine for hosting these datasets and providing computational resources for research, and the DGFI-TUM for their Database for Hydrological Time Series of Inland Waters (DAHITI).