Mapping iron oxides with Landsat-8/OLI and EO-1/Hyperion imagery from the Serra Norte iron deposits in the Carajas Mineral Province, Brazil

被引:91
作者
Ducart, Diego Fernando [1 ,2 ]
Silva, Adalene Moreira [2 ]
Bemfica Toledo, Catarina Laboure [2 ]
de Assis, Luciano Mozer [3 ]
机构
[1] Univ Estadual Campinas UNICAMP, Inst Geociencias, Campinas, SP, Brazil
[2] Univ Brasilia UnB, Inst Geociencias, Campus Darcy Ribeiro, Brasilia, DF, Brazil
[3] Vale SA, Ctr Tecnol Ferrosos, Exploracao Mineral Ferrosos, Nova Lima, MG, Brazil
关键词
Remote sensing; Multispectral and hyperspectral imagery; Iron ore; GRAO-PARA GROUP; HYPERSPECTRAL DATA; EO-1; HYPERION; U-PB; REFLECTANCE; AIRBORNE; SPECTROMETRY; INTEGRATION; MIXTURES; OLIVINE;
D O I
10.1590/2317-4889201620160023
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
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, Carajas, 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, T-zz 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.
引用
收藏
页码:331 / 349
页数:19
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