{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T07:02:21Z","timestamp":1774422141333,"version":"3.50.1"},"reference-count":59,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T00:00:00Z","timestamp":1628035200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","doi-asserted-by":"publisher","award":["88881.211850\/2018-01"],"award-info":[{"award-number":["88881.211850\/2018-01"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"publisher","award":["(310517\/2020-6, 303559\/2019-5, 313887\/2018- 401 7, 433783\/2018-4 and 304173\/2016-9"],"award-info":[{"award-number":["(310517\/2020-6, 303559\/2019-5, 313887\/2018- 401 7, 433783\/2018-4 and 304173\/2016-9"]}],"id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005672","name":"Funda\u00e7\u00e3o de Apoio ao Desenvolvimento do Ensino, Ci\u00eancia e Tecnologia do Estado de Mato Grosso do Sul","doi-asserted-by":"publisher","award":["59\/300.066\/2015 and 59\/300.095\/2015"],"award-info":[{"award-number":["59\/300.066\/2015 and 59\/300.095\/2015"]}],"id":[{"id":"10.13039\/501100005672","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Urban forests are an important part of any city, given that they provide several environmental benefits, such as improving urban drainage, climate regulation, public health, biodiversity, and others. However, tree detection in cities is challenging, given the irregular shape, size, occlusion, and complexity of urban areas. With the advance of environmental technologies, deep learning segmentation mapping methods can map urban forests accurately. We applied a region-based CNN object instance segmentation algorithm for the semantic segmentation of tree canopies in urban environments based on aerial RGB imagery. To the best of our knowledge, no study investigated the performance of deep learning-based methods for segmentation tasks inside the Cerrado biome, specifically for urban tree segmentation. Five state-of-the-art architectures were evaluated, namely: Fully Convolutional Network; U-Net; SegNet; Dynamic Dilated Convolution Network and DeepLabV3+. The experimental analysis showed the effectiveness of these methods reporting results such as pixel accuracy of 96,35%, an average accuracy of 91.25%, F1-score of 91.40%, Kappa of 82.80% and IoU of 73.89%. We also determined the inference time needed per area, and the deep learning methods investigated after the training proved to be suitable to solve this task, providing fast and effective solutions with inference time varying from 0.042 to 0.153 minutes per hectare. We conclude that the semantic segmentation of trees inside urban environments is highly achievable with deep neural networks. This information could be of high importance to decision-making and may contribute to the management of urban systems. It should be also important to mention that the dataset used in this work is available on our website.<\/jats:p>","DOI":"10.3390\/rs13163054","type":"journal-article","created":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T21:44:24Z","timestamp":1628113464000},"page":"3054","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":63,"title":["Semantic Segmentation of Tree-Canopy in Urban Environment with Pixel-Wise Deep Learning"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0668-8224","authenticated-orcid":false,"given":"Jos\u00e9 Augusto Correa","family":"Martins","sequence":"first","affiliation":[{"name":"Faculty of Engineering, Architecture and Urbanism and Geography, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3308-6384","authenticated-orcid":false,"given":"Keiller","family":"Nogueira","sequence":"additional","affiliation":[{"name":"Computing Science and Mathematics Division, University of Stirling, Stirling FK9 4LA, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0258-536X","authenticated-orcid":false,"given":"Lucas Prado","family":"Osco","sequence":"additional","affiliation":[{"name":"Faculty of Engineering and Architecture and Urbanism, University of Western S\u00e3o Paulo, Rodovia Raposo Tavares, km 572, Bairro Limoeiro 19067-175, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0843-560X","authenticated-orcid":false,"given":"Felipe David Georges","family":"Gomes","sequence":"additional","affiliation":[{"name":"Environment and Regional Development Program, University of Western S\u00e3o Paulo, Rodovia Raposo Tavares, km 572, Bairro Limoeiro 19067-175, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9106-1620","authenticated-orcid":false,"given":"Danielle Elis Garcia","family":"Furuya","sequence":"additional","affiliation":[{"name":"Environment and Regional Development Program, University of Western S\u00e3o Paulo, Rodovia Raposo Tavares, km 572, Bairro Limoeiro 19067-175, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8815-6653","authenticated-orcid":false,"given":"Wesley Nunes","family":"Gon\u00e7alves","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Architecture and Urbanism and Geography, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9209-9129","authenticated-orcid":false,"given":"Diego Andr\u00e9","family":"Sant\u2019Ana","sequence":"additional","affiliation":[{"name":"Environmental Science and Sustainability, INOVIS\u00c3O Universidade Cat\u00f3lica Dom Bosco, Av. Tamandar\u00e9, 6000, Campo Grande 79117-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6633-2903","authenticated-orcid":false,"given":"Ana Paula Marques","family":"Ramos","sequence":"additional","affiliation":[{"name":"Environment and Regional Development Program, University of Western S\u00e3o Paulo, Rodovia Raposo Tavares, km 572, Bairro Limoeiro 19067-175, Brazil"},{"name":"Agronomy Program, University of Western S\u00e3o Paulo, Rodovia Raposo Tavares, km 572, Bairro Limoeiro 19067-175, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0564-7818","authenticated-orcid":false,"given":"Veraldo","family":"Liesenberg","sequence":"additional","affiliation":[{"name":"Forest Engineering Department, Santa Catarina State University, Avenida Luiz de Cam\u00f5es 2090, Lages 88520-000, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8889-1586","authenticated-orcid":false,"given":"Jefersson Alex","family":"dos Santos","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2806-0083","authenticated-orcid":false,"given":"Paulo Tarso Sanches","family":"de Oliveira","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Architecture and Urbanism and Geography, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9096-6866","authenticated-orcid":false,"given":"Jos\u00e9 Marcato","family":"Junior","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Architecture and Urbanism and Geography, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,4]]},"reference":[{"key":"ref_1","unstructured":"(2021, July 16). 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