Comparing Three Methods of Selecting Training Samples in Supervised Classification of Multispectral Remote Sensing Images
Selecting training samples is crucial in remote sensing image classification. In this paper, we selected three images—Sentinel-2, GF-1, and Landsat 8—and employed three methods for selecting training samples: grouping selection, entropy-based selection, and direct selection. We then used the selecte...
主要な著者: | , , , , , |
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フォーマット: | 論文 |
言語: | English |
出版事項: |
MDPI AG
2023-10-01
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シリーズ: | Sensors |
主題: | |
オンライン・アクセス: | https://www.mdpi.com/1424-8220/23/20/8530 |