Identifica??o de ?reas mineradas a partir de Sensoriamento Remoto: um olhar com o Mapbiomas
| Autor(a) principal: | |
|---|---|
| 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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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). No. of bitstreams: 1 Dissertacao_Camila Reis de Souza_2021.pdf: 27166524 bytes, checksum: b2c251ca4f818632fa9a380a728a6f4e (MD5) Previous issue date: 2021-12-21Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPESConselho Nacional de Pesquisa e Desenvolvimento Cient?fico e Tecnol?gico - CNPqapplication/pdfhttp://tede2.uefs.br:8080/retrieve/6715/Dissertacao_Camila%20%20Reis%20de%20Souza_2021.pdf.jpgporUniversidade Estadual de Feira de SantanaMestrado em Modelagem em Ci?ncia da Terra e do AmbienteUEFSBrasilDEPARTAMENTO DE CI?NCIAS EXATASIdentifica??o de minera??oGoogle Earth EngineMapbiomasMining IdentificationGoogle Earth EngineMapbiomasCIENCIAS EXATAS E DA TERRAIdentifica??o de ?reas mineradas a partir de Sensoriamento Remoto: um olhar com o Mapbiomasinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis-885176421937510469600600600600600-5486832816611506211-453732605960478401635904625501369753661802873727776104890info:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UEFSinstname:Universidade Estadual de Feira de Santana (UEFS)instacron:UEFSTHUMBNAILDissertacao_Camila Reis de Souza_2021.pdf.jpgDissertacao_Camila Reis de Souza_2021.pdf.jpgimage/jpeg2244http://tede2.uefs.br:8080/bitstream/tede/1381/4/Dissertacao_Camila++Reis+de+Souza_2021.pdf.jpg6bfca2e62ae33df4827fe0ec76cbf6faMD54TEXTDissertacao_Camila Reis de Souza_2021.pdf.txtDissertacao_Camila Reis de Souza_2021.pdf.txttext/plain271523http://tede2.uefs.br:8080/bitstream/tede/1381/3/Dissertacao_Camila++Reis+de+Souza_2021.pdf.txte64c4a082aa7bd2b3e1ed4a73719e059MD53ORIGINALDissertacao_Camila Reis de Souza_2021.pdfDissertacao_Camila Reis de Souza_2021.pdfapplication/pdf27166524http://tede2.uefs.br:8080/bitstream/tede/1381/2/Dissertacao_Camila++Reis+de+Souza_2021.pdfb2c251ca4f818632fa9a380a728a6f4eMD52LICENSElicense.txtlicense.txttext/plain; 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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. |
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2021 |
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2021-12-21 |
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2022-07-12T17:51:58Z |
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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. |
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http://tede2.uefs.br:8080/handle/tede/1381 |
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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. |
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