Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/324928
Type: Artigo
Title: Mapping Iron Oxides With Landsat-8/oli And Eo-1/hyperion Imagery From The Serra Norte Iron Deposits In The Carajás Mineral Province, Brazil
Title Alternative: Mapeamento De óxidos De Ferro Usando Imagens Landsat-8/oli E Eo-1/hyperion Nos Depósitos Ferríferos Da Serra Norte, Província Mineral De Carajás, Brasil
Author: Ducart
Diego Fernando; Silva
Adalene Moreira; Toledo
Catarina Labouré Bemfica; Assis
Luciano Mozer de
Abstract: Mapping methods for iron oxides and clay minerals, using Landsat-8/Operational Land Imager (OLI) and Earth Observing 1 (EO-1)/Hyperion imagery integrated with airborne geophysical data, were applied in the N4, N5, and N4WS iron deposits, Serra Norte, Carajás, Brazil. Band ratios were achieved on Landsat-8/OLI imagery, allowing the recognition of the main minerals from iron deposits. The Landsat-8/OLI imagery showed a robust performance for iron oxide exploration, even in vegetated shrub areas. Feature extraction and Spectral Angle Mapper hyperspectral classification methods were carried out on EO-1/Hyperion imagery with good results for mapping high-grade iron ore, the hematite-goethite ratio, and clay minerals from regolith. The EO-1/Hyperion imagery proved an excellent tool for fast remote mineral mapping in open-pit areas, as well as mapping waste and tailing disposal facilities. An unsupervised classification was carried out on a data set consisting of EO-1/Hyperion visible near-infrared 74 bands, Landsat-8/OLI-derived Normalized Difference Vegetation Index, Laser Imaging Detection and Ranging-derived Digital Terrain Model, and high-resolution airborne geophysical data (gamma ray spectrometry, Tzz component of gradiometric gravimetry data). This multisource classification proved to be an adequate alternative for mapping iron oxides in vegetated shrub areas and to enhance the geology of the regolith and mineralized areas.
Subject: Remote Sensing
Multispectral And Hyperspectral Imagery
Iron Ore
Sensoriamento Remoto
Imagens Multiespectrais E Hiperespectrais
Minério De Ferro
Editor: Sociedade Brasileira de Geologia
Rights: aberto
Address: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2317-48892016000300331&lng=en&tlng=en
Date Issue: 2016
Appears in Collections:Unicamp - Artigos e Outros Documentos

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