{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T09:01:34Z","timestamp":1769072494139,"version":"3.49.0"},"reference-count":46,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,6,6]],"date-time":"2023-06-06T00:00:00Z","timestamp":1686009600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Open Fund of Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resource","award":["202302002"],"award-info":[{"award-number":["202302002"]}]},{"name":"Open Fund of Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resource","award":["41601373"],"award-info":[{"award-number":["41601373"]}]},{"name":"Open Fund of Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resource","award":["2022GZ52"],"award-info":[{"award-number":["2022GZ52"]}]},{"name":"Open Fund of Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resource","award":["U03210022"],"award-info":[{"award-number":["U03210022"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["202302002"],"award-info":[{"award-number":["202302002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41601373"],"award-info":[{"award-number":["41601373"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2022GZ52"],"award-info":[{"award-number":["2022GZ52"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U03210022"],"award-info":[{"award-number":["U03210022"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Huzhou Public Welfare Applied Research Project","award":["202302002"],"award-info":[{"award-number":["202302002"]}]},{"name":"Huzhou Public Welfare Applied Research Project","award":["41601373"],"award-info":[{"award-number":["41601373"]}]},{"name":"Huzhou Public Welfare Applied Research Project","award":["2022GZ52"],"award-info":[{"award-number":["2022GZ52"]}]},{"name":"Huzhou Public Welfare Applied Research Project","award":["U03210022"],"award-info":[{"award-number":["U03210022"]}]},{"name":"Scientific Research Starting Foundation from Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China","award":["202302002"],"award-info":[{"award-number":["202302002"]}]},{"name":"Scientific Research Starting Foundation from Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China","award":["41601373"],"award-info":[{"award-number":["41601373"]}]},{"name":"Scientific Research Starting Foundation from Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China","award":["2022GZ52"],"award-info":[{"award-number":["2022GZ52"]}]},{"name":"Scientific Research Starting Foundation from Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China","award":["U03210022"],"award-info":[{"award-number":["U03210022"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Rice false smut (RFS) is a late-onset fungal disease that primarily affects rice panicle in recent years. Severe RFS can decrease the yield by 20\u201330% and severely affect rice quality. This research used hyperspectral remote sensing data from unmanned aerial vehicles (UAV). On the basis of genetic algorithm combined with partial least squares to select the feature bands, this paper creates a new method to use the Pearson correlation coefficient method and Instability Index between Classes (ISIC) method to further select characteristic bands, which further eliminated 27.78% of the feature bands when the model monitoring accuracy was improved overall. The prediction accuracy of the Gradient Boosting Decision Tree model and Random Forest model was the best, which were 85.62% and 84.10%, respectively, and the monitoring accuracy was improved by 2.22% and 2.4% compared with that before optimization. Then, based on the UAV hyperspectral data and the combination of characteristic bands selected by the three band optimization methods, the sensitive band ranges of rice false smut monitoring were determined, which were 698\u2013800 nm and 974\u2013997 nm. This paper provides an effective method of selecting characteristic bands of hyperspectral data and a method of monitoring crop diseases\u2019 using unmanned aerial vehicles.<\/jats:p>","DOI":"10.3390\/rs15122961","type":"journal-article","created":{"date-parts":[[2023,6,7]],"date-time":"2023-06-07T01:38:41Z","timestamp":1686101921000},"page":"2961","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Rice False Smut Monitoring Based on Band Selection of UAV Hyperspectral Data"],"prefix":"10.3390","volume":"15","author":[{"given":"Yanxiang","family":"Wang","sequence":"first","affiliation":[{"name":"School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China"},{"name":"Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resources, Beijing 100081, China"},{"name":"Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China, Huzhou 313001, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5369-4638","authenticated-orcid":false,"given":"Minfeng","family":"Xing","sequence":"additional","affiliation":[{"name":"School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China"},{"name":"Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resources, Beijing 100081, China"},{"name":"Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China, Huzhou 313001, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3530-5333","authenticated-orcid":false,"given":"Hongguo","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China"}]},{"given":"Binbin","family":"He","sequence":"additional","affiliation":[{"name":"School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China"}]},{"given":"Yi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resources, Beijing 100081, China"},{"name":"Deep Ocean Environment Remote Sensing Monitoring Department, National Satellite Ocean Application Service, Beijing 100081, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.biosystemseng.2022.04.005","article-title":"Rapid image detection and recognition of rice false smut based on mobile smart devices with anti-light features from cloud database","volume":"218","author":"Yang","year":"2022","journal-title":"Biosyst. 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