{"id":5623,"date":"2018-08-01T15:46:01","date_gmt":"2018-08-01T18:46:01","guid":{"rendered":"https:\/\/www.amazoniasocioambiental.org\/radar\/mapping-mining-areas-in-the-brazilian-amazon-using-msi-sentinel-2-imagery-2017\/"},"modified":"2018-08-01T16:14:32","modified_gmt":"2018-08-01T19:14:32","slug":"mapping-mining-areas-in-the-brazilian-amazon-using-msi-sentinel-2-imagery-2017","status":"publish","type":"post","link":"https:\/\/www.raisg.org\/es\/radar\/mapping-mining-areas-in-the-brazilian-amazon-using-msi-sentinel-2-imagery-2017\/","title":{"rendered":"Mapping Mining Areas in the Brazilian Amazon Using MSI\/Sentinel-2 Imagery (2017)"},"content":{"rendered":"

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Felipe de Lucia Lobo\u00a01,2<\/sup>,\u00a0<\/span>Pedro Walfir M. Souza-Filho\u00a01,3<\/sup><\/span>,\u00a0<\/span>Evlyn M\u00e1rcia Le\u00e3o de Moraes Novo\u00a02<\/sup><\/span>,\u00a0<\/span>Felipe Menino Carlos4\u00a0<\/sup><\/span>and\u00a0<\/span>Claudio Clemente Faria Barbosa\u00a04<\/sup><\/span><\/strong><\/p>\n

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1\u00a0<\/sup>Instituto Tecnol\u00f3gico Vale, Rua Boaventura da Silva, 955, Bel\u00e9m, PA 66055-090, Brazil<\/h5>\n
2\u00a0<\/sup>Remote Sensing Division, National Institute for Space Research (INPE), Av. dos Astronautas 1758, S\u00e3o Jos\u00e9 dos Campos, SP 12227-010, Brazil<\/h5>\n
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3\u00a0<\/sup>Geosciences Institute, Universidade Federal do Par\u00e1, Rua Augusto Correa 1, Bel\u00e9m, PA 66075-110, Brazil<\/h5>\n
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4\u00a0<\/sup>Image Processing Division, National Institute for Space Research (INPE), Av. dos Astronautas 1758, S\u00e3o Jos\u00e9 dos Campos, SP 12227-010, Brazil<\/h5>\n<\/div>\n<\/div>\n<\/div>\n

[\/vc_column_text][vc_column_text]Abstract<\/strong><\/p>\n

Although mining plays an important role for the economy of the Amazon, little is known about its attributes such as area, type, scale, and current status as well as socio\/environmental impacts. Therefore, we first propose a low time-consuming and high detection accuracy method for mapping the current mining areas within 13 regions of the Brazilian Amazon using Sentinel-2 images. Then, integrating the maps in a GIS (Geography Information System) environment, mining attributes for each region were further assessed with the aid of the DNPM (National Department for Mineral Production) database. Detection of the mining area was conducted in five main steps. (a) MSI (MultiSpectral Instrument)\/Sentinel-2A (S2A) image selection; (b) definition of land-use classes and training samples; (c) supervised classification; (d) vector editing for quality control; and (e) validation with high-resolution RapidEye images (Kappa = 0.70). Mining areas derived from validated S2A classification totals 1084.7 km2<\/sup>\u00a0in the regions analyzed. Small-scale mining comprises up to 64% of total mining area detected comprises mostly gold (617.8 km2<\/sup>), followed by tin mining (73.0 km2<\/sup>). The remaining 36% is comprised by industrial mining such as iron (47.8), copper (55.5) and manganese (8.9 km2<\/sup>) in Caraj\u00e1s, bauxite in Trombetas (78.4) and Rio Capim (48.5 km2<\/sup>). Given recent events of mining impacts, the large extension of mining areas detected raises a concern regarding its socio-environmental impacts for the Amazonian ecosystems and for local communities.<\/p>\n

Keywords:\u00a0<\/em>small-scale mining<\/a>;\u00a0industrial mining<\/a>;\u00a0google engine<\/a>;\u00a0image classification<\/a>;\u00a0land-use cover change<\/a><\/p>\n

VIEW FULL-TEXT (PDF)<\/strong><\/a><\/p>\n

Lobo, F.L.; Souza-Filho, P.W.M.; Novo, E.M.L.M.; Carlos, F.M.; Barbosa, C.C.F. Mapping Mining Areas in the Brazilian Amazon Using MSI\/Sentinel-2 Imagery (2017).\u00a0Remote Sens.<\/em>\u00a02018<\/b>,\u00a010<\/em>, 1178.[\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][\/vc_column][\/vc_row][vc_row][vc_column][\/vc_column][\/vc_row]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"

[vc_row][vc_column][vc_column_text] Felipe de Lucia Lobo\u00a01,2,\u00a0Pedro Walfir M. Souza-Filho\u00a01,3,\u00a0Evlyn M\u00e1rcia Le\u00e3o de Moraes Novo\u00a02,\u00a0Felipe Menino Carlos4\u00a0and\u00a0Claudio Clemente Faria Barbosa\u00a04 1\u00a0Instituto Tecnol\u00f3gico Vale, Rua Boaventura da Silva, 955, Bel\u00e9m, PA 66055-090, Brazil 2\u00a0Remote Sensing Division, National Institute for Space Research (INPE), Av. dos Astronautas 1758, S\u00e3o Jos\u00e9 dos Campos, SP 12227-010, Brazil 3\u00a0Geosciences Institute, Universidade Federal do…<\/p>\n","protected":false},"author":11,"featured_media":5613,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[2],"tags":[],"class_list":["post-5623","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-radar","category-2","description-off"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.raisg.org\/es\/wp-json\/wp\/v2\/posts\/5623","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.raisg.org\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.raisg.org\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.raisg.org\/es\/wp-json\/wp\/v2\/users\/11"}],"replies":[{"embeddable":true,"href":"https:\/\/www.raisg.org\/es\/wp-json\/wp\/v2\/comments?post=5623"}],"version-history":[{"count":4,"href":"https:\/\/www.raisg.org\/es\/wp-json\/wp\/v2\/posts\/5623\/revisions"}],"predecessor-version":[{"id":5637,"href":"https:\/\/www.raisg.org\/es\/wp-json\/wp\/v2\/posts\/5623\/revisions\/5637"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.raisg.org\/es\/wp-json\/wp\/v2\/media\/5613"}],"wp:attachment":[{"href":"https:\/\/www.raisg.org\/es\/wp-json\/wp\/v2\/media?parent=5623"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.raisg.org\/es\/wp-json\/wp\/v2\/categories?post=5623"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.raisg.org\/es\/wp-json\/wp\/v2\/tags?post=5623"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}