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Publicação:
Mapping Areas Invaded by Pinus sp. from Geographic Object-Based Image Analysis (GEOBIA) Applied on RPAS (Drone) Color Images

dc.contributor.authorGonçalves, Vinicius Paiva
dc.contributor.authorRibeiro, Eduardo Augusto Werneck
dc.contributor.authorImai, Nilton Nobuhiro [UNESP]
dc.contributor.institutionFederal Institute of Santa Catarina—IFSC
dc.contributor.institutionFederal Catarinense Institute—IFC
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2023-03-01T20:50:49Z
dc.date.available2023-03-01T20:50:49Z
dc.date.issued2022-06-01
dc.description.abstractInvasive alien species reduce biodiversity. In southern Brazil, the genus Pinus is considered invasive, and its dispersal by humans has resulted in this species reaching ecosystems that are more sensitive and less suitable for cultivation, as is the case for the restingas on the island of Santa Catarina. Invasion control requires persistent efforts to identify and treat each new invasion case as a priority. In this study, areas invaded by Pinus sp. in restingas were mapped using images taken by a remotely piloted aircraft system (RPAS, or drone) to identify the invasion areas in great detail, enabling management to be planned for the most recently invaded areas, where management is simpler, more effective, and less costly. Geographic object-based image analysis (GEOBIA) was applied on images taken from a conventional RGB camera embedded in an RPAS, which resulted in a global accuracy of 89.56%, a mean kappa index of 0.86, and an F-score of 0.90 for Pinus sp. Processing was conducted with open-source software to reduce operational costs.en
dc.description.affiliationDepartment of Health and Services Federal Institute of Santa Catarina—IFSC, Av. Mauro Ramos, 950, SC
dc.description.affiliationSão Francisco do Sul Campus Federal Catarinense Institute—IFC, Duque de Caxias Highway, 6750, Iperoba, SC
dc.description.affiliationDepartment of Cartography São Paulo State University—UNESP, Roberto Simonsen St., 305, SP
dc.description.affiliationUnespDepartment of Cartography São Paulo State University—UNESP, Roberto Simonsen St., 305, SP
dc.identifierhttp://dx.doi.org/10.3390/rs14122805
dc.identifier.citationRemote Sensing, v. 14, n. 12, 2022.
dc.identifier.doi10.3390/rs14122805
dc.identifier.issn2072-4292
dc.identifier.scopus2-s2.0-85132300583
dc.identifier.urihttp://hdl.handle.net/11449/241186
dc.language.isoeng
dc.relation.ispartofRemote Sensing
dc.sourceScopus
dc.subjectdrone
dc.subjectGEOBIA
dc.subjectmachine learning
dc.subjectPinus
dc.subjectRPAS
dc.titleMapping Areas Invaded by Pinus sp. from Geographic Object-Based Image Analysis (GEOBIA) Applied on RPAS (Drone) Color Imagesen
dc.typeArtigo
dspace.entity.typePublication
unesp.departmentCartografia - FCTpt

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