Spaceborne mapping of hydrothermal alteration zones associated with the Mundiyawas-Khera copper deposit, Rajasthan, India, using SWIR bands of ASTER: Implications for exploration targeting

Sengar, Vivek K.; Venkatesh, A. S.; Ray, P. K. Champati; Sahoo, Prabodha Ranjan; Khan, Israil; Chattoraj, Shovan Lal

doi:10.1016/j.oregeorev.2020.103327

Cited by 20 publications

(7 citation statements)

References 49 publications

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“…Various BR and RBD have been used for the delineation of the different rock outcrops like dolomite, calcite, Iron rich-rocks, ultramafics, epidote, clay and mica minerals, etc. [17, 21-24, 42, 58-60] and mineral prospects by the demarcation & mapping of the associated alteration zones [20,22,27,28,37,45,61]. Lithological mapping of the exposed outcrops and their associated features are demarcated with the help of PCA, ICA, and MNF analyses to govern the mineral potentiality of the outcrops [9,17,40,42,44,62,63].…”

Section: à2mentioning

confidence: 99%

“…Relative Band Depth (RBD) is another technique for mineral mapping in which the position and depth of the mineral spectrum were considered for calculation [103]. The RBD governs better discrimination of minerals than BR because it considers the characteristic absorption features and normalizes the effects generated due to topography and albedo [32,37,104]. The bands acquired the shoulder position on absorption spectrum are summed up as (S1 and S2) and divided by the band having minimal absorption value (T; Eq.…”

Section: Image Processingmentioning

confidence: 99%

“…Al-OH consisting of minerals like mica and clay minerals were delineated with the help of different BRs and RBD6 (Table 3). Spectral absorption minima were recorded at band 6 of ASTER at 2.205 μm which highly suitable for the mapping of clay and mica minerals [12,34,37,42,105]. Similarly, Mg-OH and CO 3 À2 containing minerals showed the absorption minima at band 8 of ASTER at 2.336 μm which was used in the RBD8 for mapping of carbonates and ultramafics [34,37,106,107].…”

Section: Image Processingmentioning

confidence: 99%

“…Spectral absorption minima were recorded at band 6 of ASTER at 2.205 μm which highly suitable for the mapping of clay and mica minerals [12,34,37,42,105]. Similarly, Mg-OH and CO 3 À2 containing minerals showed the absorption minima at band 8 of ASTER at 2.336 μm which was used in the RBD8 for mapping of carbonates and ultramafics [34,37,106,107]. The SiO 2 containing minerals/rocks showed the emissivity minima at the band 12 of ASTER at 9.075 μm due to vibrational energy along the Si-O bond.…”

Section: Image Processingmentioning

confidence: 99%

“…Multispectral Remote Sensing is utilized in the domain of geosciences for lithological mapping [9][10][11][12][13][14][15][16], mineral mapping [17][18][19][20][21][22][23][24], identification of the alteration zones related to the base metal mineralization [25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42], structural features as a controlling factor for mineralization [26,28,[42][43][44][45][46] and mapping for demarcating favorable zones of mineralization [21,47,48]. Spectral characteristic absorption features of the rocks and minerals are utilized for the identification and mapping of lithologies and minerals like calcite, dolomite, clay, mica, and ultramafics, etc.…”

Section: Introductionmentioning

confidence: 99%

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Feature-Oriented Principal Component Selection (FPCS) for Delineation of the Geological Units Using the Integration of SWIR and TIR ASTER Data

Jain¹

2022

Recent Remote Sensing Sensor Applications - Satellites and Unmanned Aerial Vehicles (UAVs)

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Geological studies have been performed using the Band Ratios (BR), Relative Band Depth (RBD), Mineral Indices (MI), Principal Component Analysis (PCA), Independent Component Analysis (ICA), lithological and mineral classification techniques from Short-Wave Infrared (SWIR) and Thermal Infrared (TIR) data. The chapter aims to delineate various geological units present in the area using the combination of SWIR and TIR ASTER bands through the Feature-Oriented Principal Component Selection (FPCS) technique. Different BRs and RBDs were applied to map the minerals having Al-OH and Mg-OH compounds with the chemical composition of clay (kaolinite, smectite), mica (sericite, muscovite, illite), ultramafic (lizardite, antigorite, chrysotile), talc, and carbonate (dolomite) from SWIR bands. The MI was used to map quartz-rich, mafic/ultramafic, and carbonate rocks using TIR bands. The BRs, RBDs, and MIs mapped the geological units but every single greyscale image showed a variety of features. To compile these features False Color Composite (FCC) was prepared by the combination of RBDs and MIs in the R:G:B channels which demarked various geological units to a larger extent present in the region. To overcome the limitation, the FPCS technique was applied with the integration of all BRs, RBDs, and MIs. The FPCS technique extracts valuable information from different input bands and shifts the information in the first few bands. The generated eigenvalues and eigenvectors represented the retrieved information in the specific band. The loadings of the eigenvector were used for the selection of the different brands to create the FCC for the delineation of geological strata. The best discrimination was made by the selection of FPCS1, FPCS3, and FPCS6 which differentiated all the geological units like ultramafics, dolomites, thin bands of talc, and muscovite and illite (as phyllite and mica-schist), silica-rich rocks (as quartzite), and granite outcrops.

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