Deep convolutional neural network for mangrove mapping IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium /Iovan, Corina Kulbicki, M. Mermet, E. 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. IEEE 2020 text https://www.documentation.ird.fr/hor/fdi:010084424 fdi:010084424 Iovan Corina, Kulbicki M., Mermet E.. Deep convolutional neural network for mangrove mapping. In : . IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium IEEE, 2020, 1969-1972 IGARSS.International Geoscience and Remote Sensing Symposium, Waikoloa (USA), 2020/09/26-2020/10/02 EN PACIFIQUE FIDJI