{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T04:28:56Z","timestamp":1786595336300,"version":"build-2736575974"},"reference-count":43,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T00:00:00Z","timestamp":1786492800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T00:00:00Z","timestamp":1786492800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32301586"],"award-info":[{"award-number":["32301586"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["scijournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Pest Management Science"],"abstract":"Abstract<\/jats:title>\n \n BACKGROUND<\/jats:title>\n Pine wilt disease (PWD), caused by the pine wood nematode, threatens forest ecosystems in China. Early detection of infected trees is essential for timely disease management but remains challenging in conifer\u2013broadleaf mixed forests because of crown overlap and complex canopy structures. This study aimed to comprehensively evaluate the potential of unmanned aerial vehicle (UAV)\u2010based hyperspectral, LiDAR (light detection and ranging), and thermal data for multi\u2010stage PWD detection at individual tree scale.<\/jats:p>\n <\/jats:sec>\n \n RESULTS<\/jats:title>\n \n An object\u2010based classification and point cloud segmentation (OBPCS) method was developed to delineate individual pine trees by integrating LiDAR point clouds and UAV multi\u2010spectral imagery. Compared with the canopy height model (CHM)\u2010based watershed approach, OBPCS significantly improved segmentation accuracy (\n F<\/jats:italic>\n \u2010score\u2009=\u20090.88\n versus<\/jats:italic>\n 0.72). Random forest models were then constructed using crown biochemical, structural, and temperature features to classify five PWD infection stages. Among single\u2010sensor datasets, hyperspectral data achieved the highest accuracy (overall accuracy (OA)\u2009=\u200978%,\n \u03ba<\/jats:italic>\n \u2009=\u20090.72), outperforming LiDAR (OA\u2009=\u200946%,\n \u03ba<\/jats:italic>\n \u2009=\u20090.32) and thermal data (OA\u2009=\u200928%,\n \u03ba<\/jats:italic>\n \u2009=\u20090.10). Multi\u2010sensor fusion further increased classification accuracy to 82% (\n \u03ba<\/jats:italic>\n \u2009=\u20090.77) and improved early\u2010stage detection accuracy by 7%. Variable importance analysis revealed that pigment\u2010related indices were the most influential features, followed by LiDAR return intensity and point distribution metrics.\n <\/jats:p>\n <\/jats:sec>\n \n CONCLUSION<\/jats:title>\n UAV\u2010based multi\u2010sensor fusion provides an effective approach for early detection of PWD in structurally complex mixed forests. The proposed framework improves individual\u2010tree delineation and early\u2010stage diagnosis, offering practical support for early warning and fine\u2010scale monitoring of disease progression in forest ecosystems. \u00a9 2026 Society of Chemical Industry.<\/jats:p>\n <\/jats:sec>","DOI":"10.1002\/ps.71207","type":"journal-article","created":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T04:03:31Z","timestamp":1786593811000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Early detection of pine wilt disease infection in conifer\u2013broadleaf mixed forests using\n UAV<\/scp>\n \u2010based multi\u2010sensor data fusion"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4925-942X","authenticated-orcid":false,"given":"Qinan","family":"Lin","sequence":"first","affiliation":[{"name":"Zhejiang Key Laboratory of Carbon Sequestration and Emission Reduction in Agriculture and Forestry Zhejiang A&F University Hangzhou China"},{"name":"College of Environment and Resources, College of Carbon Neutrality Zhejiang A&F University Hangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Li","sequence":"additional","affiliation":[{"name":"Zhejiang Key Laboratory of Carbon Sequestration and Emission Reduction in Agriculture and Forestry Zhejiang A&F University Hangzhou China"},{"name":"College of Environment and Resources, College of Carbon Neutrality Zhejiang A&F University Hangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingxu","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Remote Sensing and Geographic Information System of Henan Province Institute of Geography, Henan Academy of Sciences Zhengzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huaguo","family":"Huang","sequence":"additional","affiliation":[{"name":"Research Center of Forest Management Engineering of State Forestry and Grassland Administration Beijing Forestry University Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peilun","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Forest Sciences University of Helsinki Helsinki Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shenghao","family":"Li","sequence":"additional","affiliation":[{"name":"Zhejiang Key Laboratory of Carbon Sequestration and Emission Reduction in Agriculture and Forestry Zhejiang A&F University Hangzhou China"},{"name":"College of Environment and Resources, College of Carbon Neutrality Zhejiang A&F University Hangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huaqiang","family":"Du","sequence":"additional","affiliation":[{"name":"Zhejiang Key Laboratory of Carbon Sequestration and Emission Reduction in Agriculture and Forestry Zhejiang A&F University Hangzhou China"},{"name":"College of Environment and Resources, College of Carbon Neutrality Zhejiang A&F University Hangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guomo","family":"Zhou","sequence":"additional","affiliation":[{"name":"Zhejiang Key Laboratory of Carbon Sequestration and Emission Reduction in Agriculture and Forestry Zhejiang A&F University Hangzhou China"},{"name":"College of Environment and Resources, College of Carbon Neutrality Zhejiang A&F University Hangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,12]]},"reference":[{"key":"e_1_2_9_2_1","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 K","year":"2013","journal-title":"Annu Rev 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