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The Accuracy of Winter Wheat Identification at Different Growth Stages Using Remote Sensing

The aim of this study was to explore the differences in the accuracy of winter wheat identification using remote sensing data at different growth stages using the same methods. Part of northern Henan Province, China was taken as the study area, and the winter wheat growth cycle was divided into five...

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Hoofdauteurs: Shengwei Liu, Dailiang Peng, Bing Zhang, Zhengchao Chen, Le Yu, Junjie Chen, Yuhao Pan, Shijun Zheng, Jinkang Hu, Zihang Lou, Yue Chen, Songlin Yang
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: MDPI AG 2022-02-01
Reeks:Remote Sensing
Onderwerpen:
winter wheat identification
remote sensing
random forest
deep learning
semantic segmentation
jointing-heading period
Online toegang:https://www.mdpi.com/2072-4292/14/4/893
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