CerealNet: A Hybrid Deep Learning Architecture for Cereal Crop Mapping Using Sentinel-2 Time-Series

CerealNet: A Hybrid Deep Learning Architecture for Cereal Crop Mapping Using Sentinel-2 Time-Series

Remote sensing-based crop mapping has continued to grow in economic importance over the last two decades. Given the ever-increasing rate of population growth and the implications of multiplying global food production, the necessity for timely, accurate, and reliable agricultural data is of the utmos...

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Bibliographic Details
Main Authors: Mouad Alami Machichi, Loubna El Mansouri, Yasmina Imani, Omar Bourja, Rachid Hadria, Ouiam Lahlou, Samir Benmansour, Yahya Zennayi, François Bourzeix
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Informatics
Subjects:
crop mapping
CerealNet
spectral similarity
deep learning
LSTM
CNN
Online Access:https://www.mdpi.com/2227-9709/9/4/96

Internet

https://www.mdpi.com/2227-9709/9/4/96

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