Winter Wheat Yield Estimation by Fusing CNN–MALSTM Deep Learning with Remote Sensing Indices

Winter Wheat Yield Estimation by Fusing CNN–MALSTM Deep Learning with Remote Sensing Indices

A rapid and accurate determination of large-scale winter wheat yield is significant for food security and policy formulation. In this study, meteorological data and enhanced vegetation index (EVI) were used to estimate the winter wheat yield in Henan Province, China, by constructing a deep learning...

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Bibliographic Details
Main Authors: Changchun Li, Lei Zhang, Xifang Wu, Huabin Chai, Hengmao Xiang, Yinghua Jiao
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Agriculture
Subjects:
enhanced vegetation index (EVI)
meteorological data
long short-term memory networks with multiple attention mechanism (MALSTM)
yield estimation
winter wheat
Online Access:https://www.mdpi.com/2077-0472/14/11/1961
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