Exploitation
M. Lotfi; H. Arefi; A. Bahroudi
Abstract
Hyperspectral remote sensing records reflectance or emittance data in a large sum of contiguous and narrow spectral bands, and thus has many information in detecting and mapping the mineral zones. On the other hand, the geological and geophysical data gives us some other fruitful information about the ...
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Hyperspectral remote sensing records reflectance or emittance data in a large sum of contiguous and narrow spectral bands, and thus has many information in detecting and mapping the mineral zones. On the other hand, the geological and geophysical data gives us some other fruitful information about the physical characteristics of soil and minerals that have been recorded from the surface. The Sarcheshmeh mining area located in the NW-trending Uromieh-Dokhtar magmatic belt within Central Iran is mainly of porphyry type, and is associated with extensive hydrothermal alterations. Due to the semi-arid type of climate with abundant rock exposure, this area is suitable for application of remote sensing techniques. In this work, we focus on generating the alteration maps around Cu porphyry copper deposits using the spectral angle mapper algorithm on Hyperion data by applying two filters named reduction to pole and analytical signal on a total magnetic intensity map and generating the Kd map from radiometry data. What is clear is the high importance of applying the adequate pre-processing on Hyperion data because of low signal-to-noise ratio. By comparing the known deposits in the region with the results obtained by applying the mentioned methods, it is revealed that not all the higher K radiometric values are entirely associated with the hydrothermal alteration zones, and in contrast, the potassic alteration map extracted from Hyperion imagery successfully corresponds to the alteration zones around the Sarcheshmeh mining area. Finally, the results particularly obtained from processing the Hyperion data are confirmed by indices of Cu porphyry deposits in the region.
M. Mohammady Oskouei; S. Babakan
Abstract
This work aims to extract the mineralogical constituents of the Lahroud Hyperion scene situated in the NW of Iran. Like the other push-broom sensors, Hyperion images suffer from spectral distortions, namely the smile effect. The corresponding spectral curvature is defined as an across-track wavelength ...
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This work aims to extract the mineralogical constituents of the Lahroud Hyperion scene situated in the NW of Iran. Like the other push-broom sensors, Hyperion images suffer from spectral distortions, namely the smile effect. The corresponding spectral curvature is defined as an across-track wavelength shift from the nominal central wavelength, and alters the pixel spectra. The common “column mean adjusted in MNF space” method was employed in this work to improve the processing accuracy by minimizing the smile effect before carrying out the atmospheric and topographical corrections. The mineral distributions were mapped by applying the standardized hyperspectral processing methodology developed by analytical imaging and geophysics (AIG). The spectral unmixing of the data resulted in the identification of five indicative minerals including natrolite, opal, analcime, kaolinite, and albite; and their spectra were employed for the generation of their distribution maps. Comparison of the results of the data processing with and without smile correction indicated a better classification performance after the smile correction. Quantitative validation of the final mineralogical map was performed using the 100 k geological map and reports of the region. Therefore, the coverage of the extracted minerals were investigated regarding the location of the lithological units in ArcGIS that implies a high coincidence. The mineral distributions in the final map show a high consistency with the geological map of the studied area, and thus it could be utilized successfully to reveal the mineralization trend in the region.