Iovan Corina, Kulbicki M., Mermet E. (2020). Deep convolutional neural network for mangrove mapping. In :
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium. Piscataway : IEEE, 1969-1972. IGARSS.International Geoscience and Remote Sensing Symposium, Waikoloa (USA), 2020/09/26-2020/10/02. ISBN 978-1-7281-6375-8.
Titre du document
Deep convolutional neural network for mangrove mapping
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium
Source
Piscataway : IEEE, 2020,
1969-1972 ISBN 978-1-7281-6375-8
Colloque
IGARSS.International Geoscience and Remote Sensing Symposium, Waikoloa (USA), 2020/09/26-2020/10/02
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.
Plan de classement
Etudes, transformation, conservation du milieu naturel [082]
;
Télédétection [126]
;
Cartographie / Méthodes graphiques [128]
