{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T11:09:18Z","timestamp":1772017758028,"version":"3.50.1"},"reference-count":62,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,6,11]],"date-time":"2022-06-11T00:00:00Z","timestamp":1654905600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Invasive 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 Santa Catarina Island. 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.<\/jats:p>","DOI":"10.3390\/rs14122805","type":"journal-article","created":{"date-parts":[[2022,6,12]],"date-time":"2022-06-12T23:55:24Z","timestamp":1655078124000},"page":"2805","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Mapping Areas Invaded by Pinus sp. from Geographic Object-Based Image Analysis (GEOBIA) Applied on RPAS (Drone) Color Images"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1038-4709","authenticated-orcid":false,"given":"Vinicius","family":"Gon\u00e7alves","sequence":"first","affiliation":[{"name":"Professional Master\u2019s Program in Climate and Environment, Department of Health and Services, Federal Institute of Santa Catarina\u2014IFSC, Av. Mauro Ramos, 950, Florian\u00f3polis 88020-300, SC, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3313-6783","authenticated-orcid":false,"given":"Eduardo","family":"Ribeiro","sequence":"additional","affiliation":[{"name":"Professional Master\u2019s Program in Climate and Environment, S\u00e3o Francisco do Sul Campus, Federal Catarinense Institute\u2014IFC, Duque de Caxias Highway, 6750, Iperoba, S\u00e3o Francisco do Sul 89240-000, SC, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0516-0567","authenticated-orcid":false,"given":"Nilton","family":"Imai","sequence":"additional","affiliation":[{"name":"Department of Cartography, S\u00e3o Paulo State University\u2014UNESP, Roberto Simonsen St., 305, Presidente Prudente 19060-900, SP, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,11]]},"reference":[{"key":"ref_1","unstructured":"(2021, July 20). Secretariat of the Convention on Biological Diversity. Global Biodiversity Outlook 5; Montreal. 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