{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T15:24:51Z","timestamp":1771514691240,"version":"3.50.1"},"reference-count":107,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2024,10,18]],"date-time":"2024-10-18T00:00:00Z","timestamp":1729209600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003032","name":"Association Nationale de la Recherche et de la Technologie","doi-asserted-by":"publisher","award":["2021\/0301"],"award-info":[{"award-number":["2021\/0301"]}],"id":[{"id":"10.13039\/501100003032","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Rennes M\u00e9tropole","award":["2021\/0301"],"award-info":[{"award-number":["2021\/0301"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Urban trees play an important role in mitigating effects of climate change and provide essential ecosystem services. However, the urban environment can stress trees, requiring the use of effective monitoring methods to assess their health and functionality. The objective of this study, which focused on four deciduous tree species in Rennes, France, was to evaluate the ability of hybrid inversion models to estimate leaf chlorophyll content (LCC), leaf area index (LAI), and canopy chlorophyll content (CCC) of urban trees using eight Sentinel-2 (S2) images acquired in 2021. Simulations were performed using the 3D radiative transfer model DART, and the hybrid inversion models were developed using machine-learning regression algorithms (random forest (RF) and gaussian process regression). Model performance was assessed using in situ measurements, and relations between satellite data and in situ measurements were investigated using spatial allocation (SA) methods at the pixel and tree scales. The influence of including environment features (EFs) as model inputs was also assessed. The results indicated that random forest models that included EFs and used the pixel-scale SA method were the most accurate with R2 values of 0.33, 0.29, and 0.46 for LCC, LAI, and CCC, respectively, with notable variability among species.<\/jats:p>","DOI":"10.3390\/rs16203867","type":"journal-article","created":{"date-parts":[[2024,10,18]],"date-time":"2024-10-18T05:03:49Z","timestamp":1729227829000},"page":"3867","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Estimation of Urban Tree Chlorophyll Content and Leaf Area Index Using Sentinel-2 Images and 3D Radiative Transfer Model Inversion"],"prefix":"10.3390","volume":"16","author":[{"given":"Th\u00e9o","family":"Le Saint","sequence":"first","affiliation":[{"name":"UMR 6554 CNRS, LETG, University of Rennes, Place du Recteur Henri Le Moal, 35000 Rennes, France"},{"name":"DOTA, ONERA, Universit\u00e9 de Toulouse, 31055 Toulouse, France"}]},{"given":"Jean","family":"Nabucet","sequence":"additional","affiliation":[{"name":"UMR 6554 CNRS, LETG, University of Rennes, Place du Recteur Henri Le Moal, 35000 Rennes, France"}]},{"given":"Laurence","family":"Hubert-Moy","sequence":"additional","affiliation":[{"name":"UMR 6554 CNRS, LETG, University of Rennes, Place du Recteur Henri Le Moal, 35000 Rennes, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6514-3561","authenticated-orcid":false,"given":"Karine","family":"Adeline","sequence":"additional","affiliation":[{"name":"DOTA, ONERA, Universit\u00e9 de Toulouse, 31055 Toulouse, France"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"104477","DOI":"10.1016\/j.landurbplan.2022.104477","article-title":"Pan-European Urban Green Space Dynamics: A View from Space between 1990 and 2015","volume":"226","author":"Xu","year":"2022","journal-title":"Landsc. 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