Abstract
Abstract. Imaging spectroscopy/hyperspectral remote sensing technique acquires images in a very narrow and contiguous spectral bands. High spectral resolution data provided by imaging spectrometers enables remote compositional mapping of earth surface. In the present study, we demonstrate the potentials of airborne AVIRIS-NG datasets for identification and mapping of non-metallic minerals. Several minerals such as carbonates, sulphates and phyllosilicate exhibit diagnostic absorption feature in Short Wave Infrared Region (SWIR) (2.0–2.5 μm). Therefore, mapping of wavelength of deepest absorption in SWIR is very useful for exploratory earth surface composition/mineral mapping. To map the mineralogical diversity in the parts of Banswara region, Rajasthan, wavelength of deepest absorption feature and absorption band depth in SWIR region was calculated at each pixel. It was found that majority of pixels showed absorption near ∼2.31, 2.33 and 2.20 μm. Detailed analysis of spectra of image revealed dolomite as dominant mineral at pixels showing deepest absorption at 2.31 μm. Calcite and clays were found to be present at pixels showing deepest absorption feature near 2.33 and 2.20 μm respectively. It is noted that mapping wavelength position of deepest feature is a very fast and reliable indicator of mineralogy. The mineral map of calcite and dolomite shall be useful for locating new mining prospect in the region.
Highlights
Hyperspectral remote sensing or imaging spectrometry is a technique in which images are acquired in very narrow, contiguous spectral band (Goetz et al, 1985)
The present study demonstrates the application of AVIRIS-NG datasets in mapping clays and carbonates in parts of Banswara region
It has been found that mapping wavelength of deepest absorption feature in Short Wave Infrared Region (SWIR) region is an effective technique of assessing the surficial mineralogical diversity
Summary
Hyperspectral remote sensing or imaging spectrometry is a technique in which images are acquired in very narrow, contiguous spectral band (Goetz et al, 1985) It has emerged as powerful, rapid, inexpensive and non-destructive technique and is commonly used in identification of minerals and in some instances determination of their abundance (Hunt and Ashley, 1979, Goetz et al, 1985; Lang et al 1987; Kruse, 1988; Pieters and Mustard, 1988). Several workers have demonstrated the application of hyperspectral datasets for mineralogical mapping (e.g. Kruse et al, 1993, Clark et al, 2003). In these methods, mineral mapping is done by comparing reference spectra with image spectra. Recent advances in hyperspectral imaging technology has led to development of sensors with very high spectral resolutions capable of resolving subtle differences in wavelength position of absorption feature
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