Multispectral Imagery Applied to Nickel Laterite Exploration: The Conceição do Araguaia Discovery
Published:January 01, 2009
J. Carlos Sícoli Seoane, Neivaldo A. Castro, Liliana S. Osako, Franciscus J. Baars, 2009. "Multispectral Imagery Applied to Nickel Laterite Exploration: The Conceição do Araguaia Discovery", Remote Sensing and Spectral Geology, Richard Bedell, Alvaro P. Crósta, Eric Grunsky
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Recent advances in geometallurgy have made nickel laterites a premier target for mining and exploration companies. Parallel to this, a series of advances in remote sensing have become available at very low cost. Two of these advances, namely better topographical data, through NASA’s Shuttle Radar Topographic Mission (SRTM), and multispectral imagery from the ASTER sensor, have been combined to aid nickel laterite exploration in central Brazil.
The Conceição do Araguaia region, located in Pará and extending into Tocantins state, is part of the Neoproterozoic Araguaia fold belt. The target area covers the Quatipuru mafic-ultramafic association, which includes serpentinites (metaperidotites and metadunites), talc schists, tremolite-actinolite schists and small volumes of pillow basalts, phyllites, BIFs, gabbroic and jasperoid rocks. These are enclosed regionally by slate to phyllitic rocks. Several other occurrences of mafic-ultramafic rocks, along with Quatipuru mafic-ultramafic association are interpreted as part of an ophiolitic complex. Low-grade (greenschist) regional metamorphism is dominant. Laterization has been active since the early Tertiary, resulting in an extensive regolith cover over the older rock units.
In the present work, the Quatipuru mafic-ultramafic association was examined for nickel laterite mineralization by data compilation and remotely sensed image processing and interpretation. ASTER’s multispectral visible-shortwave infrared (SWIR) remote sensing capabilities were used to map areas of prospective mineral alteration and key mineral groups. Using spectral libraries for selected nickel-bearing minerals as standards, SWIR and visible-NIR bands of georeferenced mosaiced ASTER scenes were processed by feature-oriented principal component analysis (PCA), and the results converted in mineral-abundance images, based on statistical classification and pseudocoloring. The mineral abundance maps highlight areas most likely to contain minerals of interest.
Processing was performed for the whole region of interest, and for its part in the central scene alone, which covers about 85 percent of the concession areas. In both cases, statistics for PCA were conducted on a subset of the data, minimizing extraneous factors such as large drainages and urban sprawl, and then applied to the whole region.
Mineral abundance maps for the area have been built into a geographic information system (GIS), along with other remotely sensed data, public-domain regional geophysics, geologic, and infrastructure data, scouted geochemistry samples, and a leveled and continuous SRTM digital elevation model. Mapping for the occurrence of mafic-ultramafic rocks was achieved by a combination of PCs 1, 4 and 2 of ASTER bands 2, 4, 5, and 8. Clusters of anomalous contents of selected minerals are draped over the digital elevation model and indicate that the northeast-dipping rock units are covered by a laterized sequence constituting the main exploration targets. This targeting exercise revealed a number of favorable sites that are currently under exploration by mining companies.
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Remote Sensing and Spectral Geology
Two recent papers, “Utility of high-altitude infrared spectral data in mineral exploration: Application to northern Patagonia Mountains, Arizona,” by Berger et al. (2003), and “Mapping hydrothermally altered rocks at Cuprite, Nevada, using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), a new satellite-imaging system,” by Rowan et al. (2003), make a distinctive mark on the use of airborne and satellite hyperspectral imaging as an exploration tool.
These two papers deal with imaging of the Earth’s surface using the visible (0.4 μm) to near infrared (2.5 μm) part of the electromagnetic spectrum to map various mineral species. Depending on their structure and molecular bonding, minerals reflect and absorb the electromagnetic spectrum in unique ways. A large group of minerals have distinct electromagnetic signatures that make it possible to identify them from imaging systems that map the range of the electromagnetic spectrum between 0.5 and 2.5 μm.
These papers represent two distinct approaches. The first paper, by Berger et al., discusses the use of the AVIRIS (Airborne Visible Infrared Imaging Spectrometer) scanner, which provides high-resolution reflectance measurements in the spectral domain (224 channels between 0.4 and 2.45 μm) and variable spatial resolution (20 m), dependent on aircraft altitude. The second paper, by Rowan et al., discusses the use of the ASTER satellite scanner, which offers a limited range of spectra at three spatial resolutions (15, 30, and 90 m). ASTER measures reflectance radiation in 3 bands within the 0.52- to 0.86-μm range (visible-near-infrared) at 15-m spatial resolution, and 6 bands between 1.00 and 2.43 μm (short wave infrared) at 30-m spatial resolution. Emitted radiation is measured in 5 bands between 8.125 and 11.650 μm (thermal infrared) with a 90-m spatial resolution.
The main advantage of the AVIRIS sensor is the level of spectral detail, which provides accurate measurements of reflectance and absorption features of minerals that enables detailed mineral mapping. Its main disadvantages, however, are the extensive processing required to make the reflectance spectra useful, and its limited spatial coverage and acquisition cost based on programmed flights. In contrast, the main advantage of the ASTER sensor is that it measures key portions of the visible, near-infrared, and thermal infrared spectra of minerals for large-scale mapping projects, whereas its main disadvantage is that the data represent only portions of the electromagnetic spectrum and some minerals cannot be distinctively mapped. In addition, the lower spatial resolution in the near-and thermal infrared portions of the spectrum makes it more difficult to map at detailed scales.