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

Abstract

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 openpit 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/OLIderived 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. KEYWORDS:Remote sensing; Multispectral and hyperspectral imagery; Iron ore. RESUMO: Métodos de mapeamento para óxidos de ferro e argilas, aplicados em imagens Landsat-8/Operational Land Imager (OLI) e Earth Observing 1 (EO-1)/Hyperion e integrados com dados aerogeofísicos, foram testados nos depósitos de ferro de N4, N5 e N4WS, Serra

Survey of Hyperspectral Earth Observation Applications from Space in the Sentinel-2 Context

“…Geological applications are therefore suitable applications for hyperspectral sensors enabling an identical or better discrimination of the potential geological components than multispectral sensors of similar GSD [107,108,120]. However, the SNR value is identified as the hyperspectral critical factor for geological applications, and a higher spatial resolution is required only, but for finer detection (such as mineral dykes detection).…”

Remote sensing techniques for onshore oil and gas exploration

“…al, 2013). This has proven useful for rapid mapping in remote areas (Ducart et al, 2016) and to be an extremely cost-effective approach (Lisica, 2015) for high-grading study areas. With seismic data and field crews yielding financial burdens and health and safety risks, remote sensing is becoming a go-to tool for exploration.…”

Aeromagnetic and spectral expressions of rare earth element deposits in Gallinas Mountains area, Central New Mexico, USA

“…By applying the theoretical method of the spectral features of iron oxides, which typically present reflectance in OLI band 4, 6 and absorptions in band 2 and band 5 (Ducart et al, 2016), OLI bands 4/2 and 6/5 were selected as band ratios for highlighting iron minerals in the study area.…”

“…Area of ferric iron mineral occuring as coatings or disseminated on surfaces of hydrothermally altered rocks, sedimentary rocks and mafic related regolith at low grade can be identified with this ratio (Rockwell, 2013;Dehnavi et al, 2010). As a result, high pixel values in the study area Another band ratio applied in this study is OLI band 6/5, an index proposed to detect crystal-field absorption features from possible ferrous (Fe 2+ ) mineral and ferric-ferrous iron oxide magnetite (Kaufmann, 1988;Wilford and Creasey, 2002;Rajendran et al, 2007;Dogan, 2008;Elsayed Zeinelabdein and Albiely, 2008;Ducart et al, 2016) since OLI band 5 coincides with the absorption feature of ferrous and ferric iron minerals whereas band 6 covers the high reflection peak for ferrous iron oxides, ferruginous saprolite, clays and hydrothermally altered rocks (Podwysocki, et al, 1985;Wilford and Creasey, 2002). This index highlights ferrous iron related rocks as shown in figure 4.…”

“…Based on the consideration of those two band ratio results above, a false color composite image using a combination of the OLI band ratios of 6/4, 4/2 and 6/7 in red, green and blue, respectively, has been obtained to detect alteration zones featured by iron oxides, hydroxyl-bearing minerals, and hydrothermal clays (Sabins, 1999;Elsayed Zeinelabdein and Albielyb, 2008;Knepper, 2010;Knepper, 2010;Ducart et al, 2016). A high ratio value of one color will display on the pixel as a primary color of red, green or blue; high ratio values of two colors will be presented in the pixel as a combination of two colors proportional to their values.…”