A Scalable Machine Learning Pipeline for Paddy Rice Classification Using Multi-Temporal Sentinel Data

A Scalable Machine Learning Pipeline for Paddy Rice Classification Using Multi-Temporal Sentinel Data

The demand for rice production in Asia is expected to increase by 70% in the next 30 years, which makes evident the need for a balanced productivity and effective food security management at a national and continental level. Consequently, the timely and accurate mapping of paddy rice extent and its...

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Bibliographic Details
Main Authors: Vasileios Sitokonstantinou, Alkiviadis Koukos, Thanassis Drivas, Charalampos Kontoes, Ioannis Papoutsis, Vassilia Karathanassi
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Remote Sensing
Subjects:
pseudo-labeling
paddy rice mapping
distributed learning
semi-supervised learning
food security
high performance computing
Online Access:https://www.mdpi.com/2072-4292/13/9/1769

Internet

https://www.mdpi.com/2072-4292/13/9/1769

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