{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,18]],"date-time":"2026-10-18T05:26:42Z","timestamp":1792301202614,"version":"4.4.0"},"reference-count":71,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2020,4,18]],"date-time":"2020-04-18T00:00:00Z","timestamp":1587168000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001807","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","doi-asserted-by":"publisher","award":["2018\/06072-7"],"award-info":[{"award-number":["2018\/06072-7"]}],"id":[{"id":"10.13039\/501100001807","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Tropical forests concentrate the largest diversity of species on the planet and play a key role in maintaining environmental processes. Due to the importance of those forests, there is growing interest in mapping their components and getting information at an individual tree level to conduct reliable satellite-based forest inventory for biomass and species distribution qualification. Individual tree crown information could be manually gathered from high resolution satellite images; however, to achieve this task at large-scale, an algorithm to identify and delineate each tree crown individually, with high accuracy, is a prerequisite. In this study, we propose the application of a convolutional neural network\u2014Mask R-CNN algorithm\u2014to perform the tree crown detection and delineation. The algorithm uses very high-resolution satellite images from tropical forests. The results obtained are promising\u2014the     R e c a l l    ,     P r e c i s i o n    , and     F 1     score values obtained were were     0.81    ,     0.91    , and     0.86    , respectively. In the study site, the total of tree crowns delineated was     59,062    . These results suggest that this algorithm can be used to assist the planning and conduction of forest inventories. As the algorithm is based on a Deep Learning approach, it can be systematically trained and used for other regions.<\/jats:p>","DOI":"10.3390\/rs12081288","type":"journal-article","created":{"date-parts":[[2020,4,21]],"date-time":"2020-04-21T04:49:38Z","timestamp":1587444578000},"page":"1288","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":136,"title":["Tree Crown Delineation Algorithm Based on a Convolutional Neural Network"],"prefix":"10.3390","volume":"12","author":[{"given":"Jos\u00e9 R.","family":"G. Braga","sequence":"first","affiliation":[{"name":"Remote Sensing Division, National Institute for Space Research\u2014INPE, Av. dos Astronautas 1758, S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3137-211X","authenticated-orcid":false,"given":"Vin\u00edcius","family":"Peripato","sequence":"additional","affiliation":[{"name":"Remote Sensing Division, National Institute for Space Research\u2014INPE, Av. dos Astronautas 1758, S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7151-8697","authenticated-orcid":false,"given":"Ricardo","family":"Dalagnol","sequence":"additional","affiliation":[{"name":"Remote Sensing Division, National Institute for Space Research\u2014INPE, Av. dos Astronautas 1758, S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0687-4422","authenticated-orcid":false,"given":"Matheus","family":"P. Ferreira","sequence":"additional","affiliation":[{"name":"Cartographic Engineering Section, Military Institute of Engineering\u2014IME, Pra\u00e7a Gen.Tib\u00farcio 80, Rio de Janeiro 22290-270, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuliya","family":"Tarabalka","sequence":"additional","affiliation":[{"name":"Inria Sophia Antipolis, Cedex Sophia Antipolis, 06902 Valbonne, France"},{"name":"Luxcarta Technology, Parc d\u2019Activit\u00e9 l\u2019Argile, Lot 119b, 06370 Mouans Sartoux, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4134-6708","authenticated-orcid":false,"given":"Luiz E.","family":"O. C. Arag\u00e3o","sequence":"additional","affiliation":[{"name":"Remote Sensing Division, National Institute for Space Research\u2014INPE, Av. dos Astronautas 1758, S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"},{"name":"College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4RJ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haroldo","family":"F. de Campos Velho","sequence":"additional","affiliation":[{"name":"Associated Laboratory for Computing and Applied Mathematics, National Institute for Space Research\u2014INPE, Av. dos Astronautas 1758, S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5226-0435","authenticated-orcid":false,"given":"Elcio H.","family":"Shiguemori","sequence":"additional","affiliation":[{"name":"Department of Aerospace Science and Technology, Institute for Advanced Studies\u2014IEAv, Trevo Coronel Aviador Jos\u00e9 Alberto Albano do Amarante 01, S\u00e3o Jos\u00e9 dos Campos 12228-001, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9623-1182","authenticated-orcid":false,"given":"Fabien H.","family":"Wagner","sequence":"additional","affiliation":[{"name":"Remote Sensing Division, National Institute for Space Research\u2014INPE, Av. dos Astronautas 1758, S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"},{"name":"GeoProcessing Division, Foundation for Science, Technology and Space Applications\u2014FUNCATE, S\u00e3o Jos\u00e9 dos Campos 12210-131, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,18]]},"reference":[{"key":"ref_1","unstructured":"FAO (2010). 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