Improving the Accuracy of Land Cover Mapping by Distributing Training Samples

High-quality training samples are essential for accurate land cover classification. Due to the difficulties in collecting a large number of training samples, it is of great significance to collect a high-quality sample dataset with a limited sample size but effective sample distribution. In this pap...

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Auteurs principaux:	Chenxi Li, Zaiying Ma, Liuyue Wang, Weijian Yu, Donglin Tan, Bingbo Gao, Quanlong Feng, Hao Guo, Yuanyuan Zhao
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2021-11-01
Collection:	Remote Sensing
Sujets:	training samples spatial distribution land cover supervised classification
Accès en ligne:	https://www.mdpi.com/2072-4292/13/22/4594
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