Identifica??o de ?reas mineradas a partir de Sensoriamento Remoto: um olhar com o Mapbiomas

Detalhes bibliográficos
Autor(a) principal: Souza, Camila Reis de
Data de Publicação: 2021
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações da UEFS
Texto Completo: http://tede2.uefs.br:8080/handle/tede/1381
Resumo: Mining activity, often installed in hard-to-reach regions, is responsible for causing distant changes in land use and land cover. To monitor and identify changes the application of appropriate remote sensing tools is a viable alternative. There are different software and platforms if remote sensing that enable the digital processing of satellite images, Google Earth Engine (GEE) is a fast tool that brings the possibility of historical series analysis that help in sizing the scope of the impacts caused by mining activity. This work brings the comparison between some remote sensing methods that can be used to identify areas: SIGMINE, MAPBIOMAS, GLOBALFOREST WATCH ANDDELIMITATION BYREGIONOF INTEREST, presenting the most appropriate among them. Although MAPBIOMAS was considered the platform that presented better results among the others analyzed, the tool MAPBIOMAS, in the first months of the release of the new collection, presented several inconsistencies in some features. Mapbiomas was applied to design mines that extract gold, copper, iron, magnesite and talc in the state of Bahia in Brazil, analyzing the expansion of its areas of operation over the 36-year interval, between 1985 and 2020. The expansion of metals, gold, copper and iron mining is influenced by the commercialization value of these materials in the market; however, internal factors can also impact on an enterprise. Some inconsistencies found during identification, or not, of areas mined by Mapbiomas, is due to the methodology of filtering and image stabilization applied by the platform.
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spelling Castro, Paulo de Tarso Amorim24695203634http://lattes.cnpq.br/7247198559551536Nolasco, Marjorie Cseko19758960504http://lattes.cnpq.br/314055642487130903509054520http://lattes.cnpq.br/6188116123911587Souza, Camila Reis de2022-07-12T17:51:58Z2021-12-21SOUZA, Camila Reis. Identifica??o de ?reas mineradas a partir de Sensoriamento Remoto: um olhar com o Mapbiomas. 2021. 193 f. Disserta??o (Mestrado em Modelagem em Ci?ncia da Terra e do Ambiente) - Departamento de Ci?ncias Exatas, Universidade Estadual de Feira de Santana, Feira de Santana, 2021.http://tede2.uefs.br:8080/handle/tede/1381Mining activity, often installed in hard-to-reach regions, is responsible for causing distant changes in land use and land cover. To monitor and identify changes the application of appropriate remote sensing tools is a viable alternative. There are different software and platforms if remote sensing that enable the digital processing of satellite images, Google Earth Engine (GEE) is a fast tool that brings the possibility of historical series analysis that help in sizing the scope of the impacts caused by mining activity. This work brings the comparison between some remote sensing methods that can be used to identify areas: SIGMINE, MAPBIOMAS, GLOBALFOREST WATCH ANDDELIMITATION BYREGIONOF INTEREST, presenting the most appropriate among them. Although MAPBIOMAS was considered the platform that presented better results among the others analyzed, the tool MAPBIOMAS, in the first months of the release of the new collection, presented several inconsistencies in some features. Mapbiomas was applied to design mines that extract gold, copper, iron, magnesite and talc in the state of Bahia in Brazil, analyzing the expansion of its areas of operation over the 36-year interval, between 1985 and 2020. The expansion of metals, gold, copper and iron mining is influenced by the commercialization value of these materials in the market; however, internal factors can also impact on an enterprise. Some inconsistencies found during identification, or not, of areas mined by Mapbiomas, is due to the methodology of filtering and image stabilization applied by the platform.A atividade de minera??o, muitas vezes instaladas em regi?es de dif?cil acesso, ? respons?vel por causar long?nquas mudan?as no uso e cobertura da terra. Para acompanhar e identificar ?s altera??es a aplica??o de ferramentas de sensoriamento remoto adequadas s?o uma alternativa vi?vel. Existem diferentes softwares e plataformas se sensoriamento remoto que possibilita mo processamento digital de imagens de sat?lite, o Google Earth Engine (GEE) ? uma ferramenta r?pida e que traz a possibilidade de an?lises de s?ries hist?ricas que auxiliam no dimensionamento do alcance dos impactos causados pela atividade. Este trabalho traz a compara??o entre alguns m?todos de sensoriamento remoto que podem ser usados para identifica??o de ?reas: SIGMINE, MAPBIOMAS, GLOBAL FOREST WATCH e DELIMITA??O PORREGI?O DE INTERESSE, apresentando o mais adequado entre eles. Apesar do MAPBIOMAS ter sido considerado a plataforma que apresentou resultados melhores entre aquelas analisadas, a ferramenta,nos primeiros meses de lan?amento da nova cole??o, apresentou diversas inconsist?ncias em algumas funcionalidades. O Mapbiomas foi aplicado para realizar o dimensionamento de minas que extra em ouro, cobre, ferro, Magnesita e talco no estado da Bahia, fazendo uma an?lise da expans?o de suas ?reas de opera??o ao longo do intervalo de 36 anos, entre 1985 a 2020. A expans?o da minera??o de metais, ouro, cobre e ferro ? influencia da pelo valor de comercializa??o desses materiais no mercado, por?m, fatores internos tamb?m podem impactar em um empreendimento. Algumas inconsist?ncias encontradas durante a identifica??o, ou n?o, de ?reas mineradas pelo Mapbiomas, se deve a metodologia de filtra geme estabiliza??o de imagem aplicada pela plataforma.Submitted by Renata Aline Souza Silva (rassilva@uefs.br) on 2022-07-12T17:51:58Z No. of bitstreams: 1 Dissertacao_Camila Reis de Souza_2021.pdf: 27166524 bytes, checksum: b2c251ca4f818632fa9a380a728a6f4e (MD5)Made available in DSpace on 2022-07-12T17:51:58Z (GMT). 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dc.title.por.fl_str_mv Identifica??o de ?reas mineradas a partir de Sensoriamento Remoto: um olhar com o Mapbiomas
title Identifica??o de ?reas mineradas a partir de Sensoriamento Remoto: um olhar com o Mapbiomas
spellingShingle Identifica??o de ?reas mineradas a partir de Sensoriamento Remoto: um olhar com o Mapbiomas
Souza, Camila Reis de
Identifica??o de minera??o
Google Earth Engine
Mapbiomas
Mining Identification
Google Earth Engine
Mapbiomas
CIENCIAS EXATAS E DA TERRA
title_short Identifica??o de ?reas mineradas a partir de Sensoriamento Remoto: um olhar com o Mapbiomas
title_full Identifica??o de ?reas mineradas a partir de Sensoriamento Remoto: um olhar com o Mapbiomas
title_fullStr Identifica??o de ?reas mineradas a partir de Sensoriamento Remoto: um olhar com o Mapbiomas
title_full_unstemmed Identifica??o de ?reas mineradas a partir de Sensoriamento Remoto: um olhar com o Mapbiomas
title_sort Identifica??o de ?reas mineradas a partir de Sensoriamento Remoto: um olhar com o Mapbiomas
author Souza, Camila Reis de
author_facet Souza, Camila Reis de
author_role author
dc.contributor.advisor1.fl_str_mv Castro, Paulo de Tarso Amorim
dc.contributor.advisor1ID.fl_str_mv 24695203634
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/7247198559551536
dc.contributor.advisor-co1.fl_str_mv Nolasco, Marjorie Cseko
dc.contributor.advisor-co1ID.fl_str_mv 19758960504
dc.contributor.advisor-co1Lattes.fl_str_mv http://lattes.cnpq.br/3140556424871309
dc.contributor.authorID.fl_str_mv 03509054520
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/6188116123911587
dc.contributor.author.fl_str_mv Souza, Camila Reis de
contributor_str_mv Castro, Paulo de Tarso Amorim
Nolasco, Marjorie Cseko
dc.subject.por.fl_str_mv Identifica??o de minera??o
Google Earth Engine
Mapbiomas
topic Identifica??o de minera??o
Google Earth Engine
Mapbiomas
Mining Identification
Google Earth Engine
Mapbiomas
CIENCIAS EXATAS E DA TERRA
dc.subject.eng.fl_str_mv Mining Identification
Google Earth Engine
Mapbiomas
dc.subject.cnpq.fl_str_mv CIENCIAS EXATAS E DA TERRA
description Mining activity, often installed in hard-to-reach regions, is responsible for causing distant changes in land use and land cover. To monitor and identify changes the application of appropriate remote sensing tools is a viable alternative. There are different software and platforms if remote sensing that enable the digital processing of satellite images, Google Earth Engine (GEE) is a fast tool that brings the possibility of historical series analysis that help in sizing the scope of the impacts caused by mining activity. This work brings the comparison between some remote sensing methods that can be used to identify areas: SIGMINE, MAPBIOMAS, GLOBALFOREST WATCH ANDDELIMITATION BYREGIONOF INTEREST, presenting the most appropriate among them. Although MAPBIOMAS was considered the platform that presented better results among the others analyzed, the tool MAPBIOMAS, in the first months of the release of the new collection, presented several inconsistencies in some features. Mapbiomas was applied to design mines that extract gold, copper, iron, magnesite and talc in the state of Bahia in Brazil, analyzing the expansion of its areas of operation over the 36-year interval, between 1985 and 2020. The expansion of metals, gold, copper and iron mining is influenced by the commercialization value of these materials in the market; however, internal factors can also impact on an enterprise. Some inconsistencies found during identification, or not, of areas mined by Mapbiomas, is due to the methodology of filtering and image stabilization applied by the platform.
publishDate 2021
dc.date.issued.fl_str_mv 2021-12-21
dc.date.accessioned.fl_str_mv 2022-07-12T17:51:58Z
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dc.identifier.citation.fl_str_mv SOUZA, Camila Reis. Identifica??o de ?reas mineradas a partir de Sensoriamento Remoto: um olhar com o Mapbiomas. 2021. 193 f. Disserta??o (Mestrado em Modelagem em Ci?ncia da Terra e do Ambiente) - Departamento de Ci?ncias Exatas, Universidade Estadual de Feira de Santana, Feira de Santana, 2021.
dc.identifier.uri.fl_str_mv http://tede2.uefs.br:8080/handle/tede/1381
identifier_str_mv SOUZA, Camila Reis. Identifica??o de ?reas mineradas a partir de Sensoriamento Remoto: um olhar com o Mapbiomas. 2021. 193 f. Disserta??o (Mestrado em Modelagem em Ci?ncia da Terra e do Ambiente) - Departamento de Ci?ncias Exatas, Universidade Estadual de Feira de Santana, Feira de Santana, 2021.
url http://tede2.uefs.br:8080/handle/tede/1381
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