Comparison of vegetation indices and image classification methods for mangrove mapping at semi-detailed scale in southwest of Rio de Janeiro, Brazil

Página do item simplificado
dc.contributor.authorRodrigues, Flávio Henrique [UNESP]
dc.contributor.authorCerri, Rodrigo Irineu [UNESP]
dc.contributor.authorde Andrade Kolya, André [UNESP]
dc.contributor.authorVeiga, Vinícius Mendes [UNESP]
dc.contributor.authorGomes Vieira Reis, Fábio Augusto [UNESP]
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2023-07-29T13:07:31Z
dc.date.available2023-07-29T13:07:31Z
dc.date.issued2023-04-01
dc.description.abstractThis paper presents the mangrove mapping carried out in the Rio de Janeiro City, Brazil, using two remote sensing data processing approaches in order to evaluate their potentialities as a complementary tool for oil spill sensitivity mapping. Ten vegetation indices were computed using the Landsat 8 imagery available in Google Earth Engine, and subsequently their spectral patterns were classified through three supervised and five unsupervised methods. Additionally, one pre-processed Landsat 8 OLI bands composition were classified by these eight classification algorithms. To role as a ground-truth for the comparison of 88 automatically produced maps, a mangrove map was prepared based on the methodological guidelines of Oceanic Atmospheric Administration of United States of America for Environmental Sensitivity Index. The best results were presented by Cobweb unsupervised classification of Mangrove Vegetation Index, properly identifying a great mangrove habitats diversity, such as inland brackish, riverine fringe and seaward forests.en
dc.description.affiliationDepartment of Geology and Natural Resources Geosciences Institute University of Campinas, PO Box 6152, SP
dc.description.affiliationDepartment of Geology Institute of Geosciences and Exact Sciences São Paulo State University, SP
dc.description.affiliationUnespDepartment of Geology Institute of Geosciences and Exact Sciences São Paulo State University, SP
dc.identifierhttp://dx.doi.org/10.1016/j.rsase.2023.100965
dc.identifier.citationRemote Sensing Applications: Society and Environment, v. 30.
dc.identifier.doi10.1016/j.rsase.2023.100965
dc.identifier.issn2352-9385
dc.identifier.scopus2-s2.0-85152145149
dc.identifier.urihttp://hdl.handle.net/11449/247144
dc.language.isoeng
dc.relation.ispartofRemote Sensing Applications: Society and Environment
dc.sourceScopus
dc.subjectGoogle earth engine
dc.subjectImage classification
dc.subjectMangrove
dc.subjectVegetation index
dc.titleComparison of vegetation indices and image classification methods for mangrove mapping at semi-detailed scale in southwest of Rio de Janeiro, Brazilen
dc.typeArtigo
unesp.author.orcid0000-0002-2016-5334 0000-0002-2016-5334[1]
unesp.author.orcid0000-0001-8507-2457[4]

Arquivos

Coleções

Artigos