{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T08:54:03Z","timestamp":1776329643315,"version":"3.50.1"},"reference-count":22,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T00:00:00Z","timestamp":1697500800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key Research and Development Program of China","award":["2020YFA0714103"],"award-info":[{"award-number":["2020YFA0714103"]}]},{"name":"the National Key Research and Development Program of China","award":["2022-JCXK-31"],"award-info":[{"award-number":["2022-JCXK-31"]}]},{"name":"the Young Teachers and Students\u2019 Cutting-Edge Funding of Jilin University, China","award":["2020YFA0714103"],"award-info":[{"award-number":["2020YFA0714103"]}]},{"name":"the Young Teachers and Students\u2019 Cutting-Edge Funding of Jilin University, China","award":["2022-JCXK-31"],"award-info":[{"award-number":["2022-JCXK-31"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Selecting training samples is crucial in remote sensing image classification. In this paper, we selected three images\u2014Sentinel-2, GF-1, and Landsat 8\u2014and employed three methods for selecting training samples: grouping selection, entropy-based selection, and direct selection. We then used the selected training samples to train three supervised classification models\u2014random forest (RF), support-vector machine (SVM), and k-nearest neighbor (KNN)\u2014and evaluated the classification results of the three images. According to the experimental results, the three classification models performed similarly. Compared with the entropy-based method, the grouping selection method achieved higher classification accuracy using fewer samples. In addition, the grouping selection method outperformed the direct selection method with the same number of samples. Therefore, the grouping selection method performed the best. When using the grouping selection method, the image classification accuracy increased with the increase in the number of samples within a certain sample size range.<\/jats:p>","DOI":"10.3390\/s23208530","type":"journal-article","created":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T10:43:10Z","timestamp":1697539390000},"page":"8530","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Comparing Three Methods of Selecting Training Samples in Supervised Classification of Multispectral Remote Sensing Images"],"prefix":"10.3390","volume":"23","author":[{"given":"Hongying","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Earth Sciences, Jilin University, Changchun 130061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinxin","family":"He","sequence":"additional","affiliation":[{"name":"College of Earth Sciences, Jilin University, Changchun 130061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shengbo","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Geoexploration Science and Technology, Jilin University, Changchun 130061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ye","family":"Zhan","sequence":"additional","affiliation":[{"name":"Aviation Operations Service College, Aviation University Air Force, Changchun 130021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanyan","family":"Bai","sequence":"additional","affiliation":[{"name":"College of Earth Sciences, Jilin University, Changchun 130061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yujia","family":"Qin","sequence":"additional","affiliation":[{"name":"College of Earth Sciences, Jilin University, Changchun 130061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Xi, J., Ersoy Okan, K., Cong, M., Zhao, C., Qu, W., and Wu, T. 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