Iovan Corina auteur aut IRD Kulbicki M. auteur aut IRD Mermet E. auteur aut IRD text bookSection eng text/pdf born digital access Updated information on the spatial distribution of mangrove forests is of high importance for management plans. Yet, access to mangrove distribution maps is limited, even-though remote sensing data is currently freely available and deep learning algorithms score high performances in automatic classification tasks. The methodologies developed in this paper are based on a deep convolutional neural network and have been tested on WorldView 2 and Sentinel-2 images. The obtained results are highly satisfactory and open perspectives for automatically mapping mangrove distribution over large areas. specialized PACIFIQUE FIDJI 126 128 082 1969-1972 Piscataway IEEE 2020 IGARSS.International Geoscience and Remote Sensing Symposium, Waikoloa (USA), 2020/09/26-2020/10/02 https://www.documentation.ird.fr/hor/fdi:010084424 10.1109/IGARSS39084.2020.9323802 978-1-7281-6375-8 [F B010084424] https://www.documentation.ird.fr/hor/fdi:010084424 https://www.documentation.ird.fr/intranet/publi/2023-01/010084424.pdf Accès réservé (Intranet de l'IRD) IRD - Base Horizon / Pleins textes 2022-02-16 2025-02-24 fdi:010084424 fre