{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T15:10:16Z","timestamp":1778253016566,"version":"3.51.4"},"reference-count":77,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,11]],"date-time":"2023-01-11T00:00:00Z","timestamp":1673395200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2021YFD1400900"],"award-info":[{"award-number":["2021YFD1400900"]}]},{"name":"National Key R&amp;D Program of China","award":["ZD202001"],"award-info":[{"award-number":["ZD202001"]}]},{"name":"Major emergency science and Technology Project of National Forestry and Grassland Administration","award":["2021YFD1400900"],"award-info":[{"award-number":["2021YFD1400900"]}]},{"name":"Major emergency science and Technology Project of National Forestry and Grassland Administration","award":["ZD202001"],"award-info":[{"award-number":["ZD202001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Pine wilt disease (PWD) has caused huge economic and environmental losses since it invaded China. Although early monitoring is an effective way to control this hazard, the monitoring window for the early stage is hard to identify, and varies in different hosts and environments. We used UAV-based multispectral images of Pinus thunbergii forest in East China to identify the change in the number of infected trees in each month of the growing season. We built classification models to detect different PWD infection stages by testing three machine learning algorithms\u2014random forest, support vector machine, and linear discriminant analysis\u2014and identified the best monitoring period for each infection stage (namely, green attack, early, middle, and late). From the obtained results, the early monitoring window period was determined to be in late July, whereas the monitoring window for middle and late PWD stages ranged from mid-August to early September. We also identified four important vegetation indices to monitor each infection stage. In conclusion, this study demonstrated the effectiveness of using machine learning algorithms to analyze multitemporal multispectral data to establish a window for early monitoring of pine wilt disease infestation. The results could provide a reference for future research and guidance for the control of pine wilt disease.<\/jats:p>","DOI":"10.3390\/rs15020444","type":"journal-article","created":{"date-parts":[[2023,1,12]],"date-time":"2023-01-12T03:11:02Z","timestamp":1673493062000},"page":"444","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["Detection of the Monitoring Window for Pine Wilt Disease Using Multi-Temporal UAV-Based Multispectral Imagery and Machine Learning Algorithms"],"prefix":"10.3390","volume":"15","author":[{"given":"Dewei","family":"Wu","sequence":"first","affiliation":[{"name":"Beijing Key Laboratory for Forest Pest Control, Beijing Forestry University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Linfeng","family":"Yu","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory for Forest Pest Control, Beijing Forestry University, Beijing 100083, China"},{"name":"School of Ecology and Nature Conservation, Beijing Forestry University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Run","family":"Yu","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory for Forest Pest Control, Beijing Forestry University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Quan","family":"Zhou","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory for Forest Pest Control, Beijing Forestry University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiaxing","family":"Li","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory for Forest Pest Control, Beijing Forestry University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xudong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory for Forest Pest Control, Beijing Forestry University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0333-0681","authenticated-orcid":false,"given":"Lili","family":"Ren","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory for Forest Pest Control, Beijing Forestry University, Beijing 100083, China"},{"name":"Sino-French Joint Laboratory for Invasive Forest Pests in Eurasia, Beijing Forestry University\u2014French National Research Institute for Agriculture, Food and Environment (INRAE), Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Youqing","family":"Luo","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory for Forest Pest Control, Beijing Forestry University, Beijing 100083, China"},{"name":"Sino-French Joint Laboratory for Invasive Forest Pests in Eurasia, Beijing Forestry University\u2014French National Research Institute for Agriculture, Food and Environment (INRAE), Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1111\/ppa.12960","article-title":"Induction of resistance against pine wilt disease caused by Bursaphelenchus xylophilus using selected pine endophytic bacteria","volume":"68","author":"Kim","year":"2019","journal-title":"Plant Pathol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1163\/156854109X404553","article-title":"Pine wilt disease: A worldwide threat to forest ecosystems","volume":"11","author":"Hunt","year":"2009","journal-title":"Nematology"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"776","DOI":"10.1094\/PDIS-12-10-0902","article-title":"Detection of Bursaphelenchus Xylophilus, Causal Agent of Pine Wilt Disease on Pinus pinaster in Northwestern Spain","volume":"95","author":"Abelleira","year":"2011","journal-title":"Plant Dis."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1146\/annurev-phyto-081211-172910","article-title":"Pine Wood Nematode, Bursaphelenchus xylophilus","volume":"51","author":"Futai","year":"2013","journal-title":"Annu. 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