AUTOMATIC TREE DETECTION/LOCALIZATION IN URBAN FOREST USING TERRESTRIAL LIDAR DATA

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatordos Santos, Renato César-
Autor(es): dc.creatorda Silva, Matheus Ferreira-
Autor(es): dc.creatorTommaselli, Antônio Maria G.-
Autor(es): dc.creatorGalo, Mauricio-
Data de aceite: dc.date.accessioned2025-08-21T17:29:10Z-
Data de disponibilização: dc.date.available2025-08-21T17:29:10Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2023-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/IGARSS53475.2024.10642701-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/308955-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/308955-
Descrição: dc.descriptionIndividual tree detection is essential task to access relevant parameters at the tree scale, such as: diameter at breast height (DBH), first branch height, and tree height. In this context, we propose an automatic tree detection/localization approach based on trunk geometry, i.e., on vertical continuity, not requiring preprocessing stages (ground filtering, point cloud normalization, classification) or training samples, as in some classes of methods. The performance of the proposed approach was evaluated using LiDAR data acquired by a terrestrial laser scanning (TLS) system in an urban forest. Obtained results indicated the potential of the proposed approach, resulting in an Fscore of 98% and a RMSEXY of 15 cm.-
Descrição: dc.descriptionDepartment of Cartography-
Descrição: dc.descriptionGraduate Program in Cartographic Sciences São Paulo State University, SP-
Descrição: dc.descriptionGraduate Program in Cartographic Sciences São Paulo State University, SP-
Formato: dc.format4522-4525-
Idioma: dc.languageen-
Relação: dc.relationInternational Geoscience and Remote Sensing Symposium (IGARSS)-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectForest Inventory-
Palavras-chave: dc.subjectMapping-
Palavras-chave: dc.subjectPhotogrammetry-
Palavras-chave: dc.subjectPoint Cloud-
Palavras-chave: dc.subjectTerrestrial Laser Scanning-
Título: dc.titleAUTOMATIC TREE DETECTION/LOCALIZATION IN URBAN FOREST USING TERRESTRIAL LIDAR DATA-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

Não existem arquivos associados a este item.