Improved Winter Wheat Spatial Distribution Extraction from High-Resolution Remote Sensing Imagery Using Semantic Features and Statistical Analysis

Improved Winter Wheat Spatial Distribution Extraction from High-Resolution Remote Sensing Imagery Using Semantic Features and Statistical Analysis

Improving the accuracy of edge pixel classification is an important aspect of using convolutional neural networks (CNNs) to extract winter wheat spatial distribution information from remote sensing imagery. In this study, we established a method using prior knowledge obtained from statistical analys...

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Bibliographic Details
Main Authors: Feng Li, Chengming Zhang, Wenwen Zhang, Zhigang Xu, Shouyi Wang, Genyun Sun, Zhenjie Wang
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Remote Sensing
Subjects:
convolutional neural network
semantic features
statistical features
gaofen-2 imagery
winter wheat
post-processing
spatial distribution
feicheng
china
Online Access:https://www.mdpi.com/2072-4292/12/3/538

Internet

https://www.mdpi.com/2072-4292/12/3/538

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