The Accuracy of Land Use and Cover Mapping across Time in Environmental Disaster Zones: The Case of the B1 Tailings Dam Rupture in Brumadinho, Brazil

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dc.contributor.authorFilho, Carlos Roberto Mangussi
dc.contributor.authordo Valle Junior, Renato Farias
dc.contributor.authorde Melo Silva, Maytê Maria Abreu Pires
dc.contributor.authorMendes, Rafaella Gouveia
dc.contributor.authorde Souza Rolim, Glauco [UNESP]
dc.contributor.authorPissarra, Teresa Cristina Tarlé [UNESP]
dc.contributor.authorde Melo, Marília Carvalho
dc.contributor.authorValera, Carlos Alberto
dc.contributor.authorPacheco, Fernando António Leal [UNESP]
dc.contributor.authorFernandes, Luís Filipe Sanches
dc.contributor.institutionFederal Institute of Triângulo Mineiro (IFTM)
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionCidade Administrativa do Estado de Minas Gerais
dc.contributor.institutionCoordenadoria Regional das Promotorias de Justiça do Meio Ambiente das Bacias dos Rios Paranaíba e Baixo Rio Grande
dc.contributor.institutionUniversity of Trás-os-Montes e Alto Douro
dc.date.accessioned2023-07-29T16:12:52Z
dc.date.available2023-07-29T16:12:52Z
dc.date.issued2023-04-01
dc.description.abstractThe rupture of a tailings dam causes several social, economic, and environmental impacts because people can die, the devastation caused by the debris and mud waves is expressive and the released substances may be toxic to the ecosystem and humans. There were two major dam failures in the Minas Gerais state, Brazil, in the last decade. The first was in 2015 in the city of Mariana and the second was in 2019 in the municipality of Brumadinho. The extent of land use and cover changes derived from those collapses were an expression of their impacts. Thus, knowing the changes to land use and cover after these disasters is essential to help repair or mitigate environmental degradation. This study aimed to diagnose the changes to land cover that occurred after the failure of dam B1 in Brumadinho that affected the Ferro-Carvão stream watershed. In addition to the environmental objective, there was the intention of investigating the impact of image preparation, as well as the spatial and spectral resolution on the classification’s accuracy. To accomplish the goals, visible and near-infrared bands from Landsat (30 m), Sentinel-2 (10 m), and PlanetScope Dove (4.77 m) images collected between 2018 and 2021 were processed on the Google Earth Engine platform. The Pixel Reduction to Median tool was used to prepare the record of images, and then the random forest algorithm was used to detect the changes in land cover caused by the tailings dam failure under the different spatial and spectral resolutions and to provide the corresponding measures of accuracy. The results showed that the spatial resolution of the images affects the accuracy, but also that the selected algorithm and images were all capable of accurately classifying land use and cover in the Ferro-Carvão watershed and their changes over time. After the failure, mining/tailings areas increased in the impacted zone of the Ferro-Carvão stream, while native forest, pasture, and agricultural lands declined, exposing the environmental deterioration. The environment recovered in subsequent years (2020–2021) due to tailings removal and mobilization.en
dc.description.affiliationGeoprocessing Laboratory Federal Institute of Triângulo Mineiro (IFTM), Uberaba Campus, MG
dc.description.affiliationFaculdade de Ciências Agrárias e Veterinárias Universidade Estadual Paulista (UNESP), Via de Acesso Prof. Paulo Donato Castellane, s/n, SP
dc.description.affiliationSecretaria de Estado de Meio Ambiente e Desenvolvimento Sustentável Cidade Administrativa do Estado de Minas Gerais, Rodovia João Paulo II, 4143, Bairro Serra Verde, MG
dc.description.affiliationCoordenadoria Regional das Promotorias de Justiça do Meio Ambiente das Bacias dos Rios Paranaíba e Baixo Rio Grande, Rua Coronel Antônio Rios, 951, MG
dc.description.affiliationCenter of Chemistry of Vila Real (CQVR) University of Trás-os-Montes e Alto Douro, Ap. 1013
dc.description.affiliationCenter for Research and Agro-Environmental and Biological Technologies (CITAB) University of Trás-os-Montes e Alto Douro, Ap. 1013
dc.description.affiliationUnespFaculdade de Ciências Agrárias e Veterinárias Universidade Estadual Paulista (UNESP), Via de Acesso Prof. Paulo Donato Castellane, s/n, SP
dc.description.sponsorshipConselleria de Agricultura, Medio Ambiente, Cambio Climático y Desarrollo Rural, Generalitat Valenciana
dc.description.sponsorshipIdConselleria de Agricultura, Medio Ambiente, Cambio Climático y Desarrollo Rural, Generalitat Valenciana: 5500074952/5500074950/5500074953
dc.identifierhttp://dx.doi.org/10.3390/su15086949
dc.identifier.citationSustainability (Switzerland), v. 15, n. 8, 2023.
dc.identifier.doi10.3390/su15086949
dc.identifier.issn2071-1050
dc.identifier.scopus2-s2.0-85156183477
dc.identifier.urihttp://hdl.handle.net/11449/249923
dc.language.isoeng
dc.relation.ispartofSustainability (Switzerland)
dc.sourceScopus
dc.subjectenvironmental degradation
dc.subjectGoogle Earth Engine
dc.subjectrandom forest classifier
dc.subjectremote sensing
dc.subjectsocio-environmental impacts
dc.subjectsoil cover change
dc.titleThe Accuracy of Land Use and Cover Mapping across Time in Environmental Disaster Zones: The Case of the B1 Tailings Dam Rupture in Brumadinho, Brazilen
dc.typeArtigo
unesp.author.orcid0000-0003-0774-5788[2]
unesp.author.orcid0000-0001-8261-2470[6]
unesp.author.orcid0000-0001-5096-0550[8]
unesp.author.orcid0000-0002-2399-5261[9]
unesp.author.orcid0000-0002-9486-7160[10]
unesp.departmentEngenharia Rural - FCAVpt

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Jaboticabal - FCAV - Faculdade de Ciências Agrárias e Veterinárias