{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T09:32:18Z","timestamp":1769074338666,"version":"3.49.0"},"reference-count":44,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T00:00:00Z","timestamp":1628640000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key R&amp;D Program of China","award":["2018YFD0200301"],"award-info":[{"award-number":["2018YFD0200301"]}]},{"name":"Sichuan Science and Technology Program","award":["2020YFG0048"],"award-info":[{"award-number":["2020YFG0048"]}]},{"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"}]},{"name":"the Open Fund of State Key Laboratory of Remote Sensing Science","award":["OFSLRSS201712"],"award-info":[{"award-number":["OFSLRSS201712"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["ZYGX2019J070"],"award-info":[{"award-number":["ZYGX2019J070"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Rice false smut (RFS), caused by Ustilaginoidea virens, is a significant grain disease in rice that can lead to reduced yield and quality. In order to obtain spatiotemporal change information, multitemporal hyperspectral UAV data were used in this study to determine the sensitive wavebands for RFS identification, 665\u2013685 and 705\u2013880 nm. Then, two methods were used for the extraction of rice false smut-infected areas, one based on spectral similarity analysis and one based on spectral and temporal characteristics. The final overall accuracy of the two methods was 74.23 and 85.19%, respectively, showing that the second method had better prediction accuracy. In addition, the classification results of the two methods show that the areas of rice false smut infection had an expanding trend over time, which is consistent with the natural development law of rice false smut, and also shows the scientific nature of the two methods.<\/jats:p>","DOI":"10.3390\/rs13163185","type":"journal-article","created":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T21:48:12Z","timestamp":1628718492000},"page":"3185","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Extraction of Areas of Rice False Smut Infection Using UAV Hyperspectral Data"],"prefix":"10.3390","volume":"13","author":[{"given":"Gangqiang","family":"An","sequence":"first","affiliation":[{"name":"School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China"},{"name":"The Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China, Huzhou 313001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"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":"The Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China, Huzhou 313001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Binbin","family":"He","sequence":"additional","affiliation":[{"name":"School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China"},{"name":"The Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China, Huzhou 313001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haiqi","family":"Kang","sequence":"additional","affiliation":[{"name":"Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu 610066, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiali","family":"Shang","sequence":"additional","affiliation":[{"name":"Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, 960 Carling Avenue, Ottawa, ON K1A 0C6, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunhua","family":"Liao","sequence":"additional","affiliation":[{"name":"School of Geospatial Engineering and Science, Sun Yat-Sen University, Zhuhai 519082, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3573-718X","authenticated-orcid":false,"given":"Xiaodong","family":"Huang","sequence":"additional","affiliation":[{"name":"Applied Geosolutions, 15 Newmarket Road, Durham, NH 03824, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"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"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.compag.2018.10.017","article-title":"Wheat Yellow Rust Monitoring by Learning from Multispectral UAV Aerial Imagery","volume":"155","author":"Su","year":"2018","journal-title":"Comput. 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