{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T15:18:00Z","timestamp":1771514280892,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2022,5,18]],"date-time":"2022-05-18T00:00:00Z","timestamp":1652832000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Beijing\u2019s Science and Technology Planning Project","award":["Z201100008020001"],"award-info":[{"award-number":["Z201100008020001"]}]},{"name":"Beijing\u2019s Science and Technology Planning Project","award":["ZD202001"],"award-info":[{"award-number":["ZD202001"]}]},{"name":"Major Emergency Science and Technology Project of National Forestry and Grassland Administration","award":["Z201100008020001"],"award-info":[{"award-number":["Z201100008020001"]}]},{"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>Beijing\u2019s One Million Mu Plain Afforestation Project involves planting large areas with the exotic North American tree species Fraxinus pennsylvanica Marsh (ash). As an exotic tree species, ash is very vulnerable to infestations by the emerald ash borer (EAB), a native Chinese wood borer pest. In the early stage of an EAB infestation, attacked trees show no obvious sign. Once the stand has reached the late damage stage, death occurs rapidly. Therefore, there is a need for efficient early detection methods of EAB stress over large areas. The combination of unmanned aerial vehicle (UAV)-based hyperspectral imaging (HI) with light detection and ranging (LiDAR) is a promising practical approach for monitoring insect disturbance. In this study, we identified the most useful narrow-band spectral HI data and 3D LiDAR data for the early detection of EAB stress in ash. UAV-HI data of different infested stages (healthy, light, moderate and severe) of EAB in the 400\u20131000 nm range were collected from ash canopies and were processed by Partial Least Squares\u2013Variable Importance in Projection (PLS-VIP) to identify the maximally sensitive bands. Band R678 nm had the highest PLS-VIP scores and the most robust classification ability. We combined this band with band R776 nm to develop an innovative normalized difference vegetation index (NDVI(776,678)) to estimate EAB stress. LiDAR data were used to segment individual trees and supplement the HI data. The new NDVI(776,678) identified different stages of EAB stress, with a producer\u2019s accuracy of 90% for healthy trees, 76.25% for light infestation, 58.33% for moderate infestation, and 100% for severe infestation, with an overall accuracy of 82.90% when combined with UAV-HI and LiDAR.<\/jats:p>","DOI":"10.3390\/rs14102428","type":"journal-article","created":{"date-parts":[[2022,5,18]],"date-time":"2022-05-18T23:14:26Z","timestamp":1652915666000},"page":"2428","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Fusion of UAV Hyperspectral Imaging and LiDAR for the Early Detection of EAB Stress in Ash and a New EAB Detection Index\u2014NDVI(776,678)"],"prefix":"10.3390","volume":"14","author":[{"given":"Quan","family":"Zhou","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"}],"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"}]},{"given":"Yujie","family":"Liu","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory for Forest Pest Control, Beijing Forestry University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongyi","family":"Zhan","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-French 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-French National Research Institute for Agriculture, Food and Environment (INRAE), Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,18]]},"reference":[{"key":"ref_1","unstructured":"Maloney, K., Boughton, J., and Schneeberger, N. 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