Pinel S. auteur aut IRD Bonnet Marie-Paule auteur aut IRD Da Silva J. S. auteur aut IRD Moreira D. auteur aut IRD Calmant Stéphane auteur aut IRD Satgé Frédéric auteur aut IRD Seyler Frédérique auteur aut IRD text journalArticle eng text/pdf reformatted digital access In the Amazon basin, the recently released SRTM Global 1 arc-second (SRTMGL1) remains the best topographic information for hydrological and hydrodynamic modeling purposes. However, its accuracy is hindered by errors, partly due to vegetation, leading to erroneous simulations. Previous efforts to remove the vegetation signal either did not account for its spatial variability or relied on a single assumed percentage of penetration of the SRTM signal. Here, we propose a systematic approach over an Amazonian floodplain to remove the vegetation signal, addressing its heterogeneity by combining estimates of vegetation height and a land cover map. We improve this approach by interpolating the first results with drainage network, field and altimetry data to obtain a hydrological conditioned DEM. The averaged interferometric and vegetation biases over the forest zone were found to be -2.0 m and 7.4 m, respectively. Comparing the original and corrected DEM, vertical validation against Ground Control Points shows a RMSE reduction of 64%. Flood extent accuracy, controlled against Landsat and JERS-1 images, stresses improvements in low and high water periods (+24% and +18%, respectively). This study also highlights that a ground truth drainage network, as a unique input during the interpolation, achieves reasonable results in terms of flood extent and hydrological characteristics. specialized DEM SRTMGL1 Amazon vegetation altimetry floodplain remote sensing lake bathymetry BRESIL AMAZONIE 126 062 082 7 12 16108-16130 2015 2072-4292 https://www.documentation.ird.fr/hor/fdi:010066088 10.3390/rs71215822 2072-4292 [F B010066088] https://www.documentation.ird.fr/hor/fdi:010066088 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers16-04/010066088.pdf IRD - Base Horizon / Pleins textes 2016-02-26 2023-12-06 fdi:010066088 fre