{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T09:02:29Z","timestamp":1770973349550,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2020,12,17]],"date-time":"2020-12-17T00:00:00Z","timestamp":1608163200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Citrus greening is a severe disease significantly affecting citrus production in the United States because the disease is not curable with currently available technologies. For this reason, monitoring citrus disease in orchards is critical to eradicate and replace infected trees before the spread of the disease. In this study, the canopy shape and vegetation indices of infected and healthy orange trees were compared to better understand their significant characteristics using unmanned aerial vehicle (UAV)-based multispectral images. Individual citrus trees were identified using thresholding and morphological filtering. The UAV-based phenotypes of each tree, such as tree height, crown diameter, and canopy volume, were calculated and evaluated with the corresponding ground measurements. The vegetation indices of infected and healthy trees were also compared to investigate their spectral differences. The results showed that correlation coefficients of tree height and crown diameter between the UAV-based and ground measurements were 0.7 and 0.8, respectively. The UAV-based canopy volume was also highly correlated with the ground measurements (R2 &gt; 0.9). Four vegetation indices\u2014normalized difference vegetation index (NDVI), normalized difference RedEdge index (NDRE), modified soil adjusted vegetation index (MSAVI), and chlorophyll index (CI)\u2014were significantly higher in healthy trees than diseased trees. The RedEdge-related vegetation indices showed more capability for citrus disease monitoring. Additionally, the experimental results showed that the UAV-based flush ratio and canopy volume can be valuable indicators to differentiate trees with citrus greening disease.<\/jats:p>","DOI":"10.3390\/rs12244122","type":"journal-article","created":{"date-parts":[[2020,12,17]],"date-time":"2020-12-17T10:42:47Z","timestamp":1608201767000},"page":"4122","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["Comparison of Canopy Shape and Vegetation Indices of Citrus Trees Derived from UAV Multispectral Images for Characterization of Citrus Greening Disease"],"prefix":"10.3390","volume":"12","author":[{"given":"Anjin","family":"Chang","sequence":"first","affiliation":[{"name":"School of Engineering and Computing Sciences, Texas A&amp;M University-Corpus Christi, Corpus Christi, TX 78412, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7571-1155","authenticated-orcid":false,"given":"Junho","family":"Yeom","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, Gyeongsang National University, Jinju 52828, Gyeongsangnam-do, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1176-3540","authenticated-orcid":false,"given":"Jinha","family":"Jung","sequence":"additional","affiliation":[{"name":"Lyles School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA"}]},{"given":"Juan","family":"Landivar","sequence":"additional","affiliation":[{"name":"Texas A&amp;M AgriLife Research and Extension at Corpus Christi, Corpus Christi, TX 78406, USA"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,17]]},"reference":[{"key":"ref_1","unstructured":"USDA (2020). 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