Deep Recurrent Neural Network for Agricultural Classification using multitemporal SAR Sentinel-1 for Camargue, France

Deep Recurrent Neural Network for Agricultural Classification using multitemporal SAR Sentinel-1 for Camargue, France

The development and improvement of methods to map agricultural land cover are currently major challenges, especially for radar images. This is due to the speckle noise nature of radar, leading to a less intensive use of radar rather than optical images. The European Space Agency Sentinel-1 constella...

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Bibliographic Details
Main Authors: Emile Ndikumana, Dinh Ho Tong Minh, Nicolas Baghdadi, Dominique Courault, Laure Hossard
Format: Article
Language:English
Published: MDPI AG 2018-08-01
Series:Remote Sensing
Subjects:
SAR
Sentinel-1
agricultural land cover map
recurrent neural network
long-short term memory
gated recurrent unit
K nearest neighbors
random forest
vector support machines
Camargue
France
Online Access:http://www.mdpi.com/2072-4292/10/8/1217

Internet

http://www.mdpi.com/2072-4292/10/8/1217

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