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• We utilized spectral bands of AVIRIS-NG airborne hyperspectral sensor to identify surface signatures of new kimberlite. • We used conjugated map of two spectral mapping algorithms to identify the surface signatures of kimberlite. • Results are also validated using genetic and empirical parameters of known kimberlite emplacement. We have utilized spectral bands of Advanced Visible Infrared Imaging Spectroradiometer Next Generation sensor (AVIRIS-NG) to identify surface signatures of new kimberlite. The main focus of the work is to identify the surface signatures of probable kimberlite occurrence and to substantiate these surface signatures as the prospective areas of detailed exploration. Since, all the discovered kimberlites were reported within ferruginous quartzite (Fe-quartzite), we prepared an AVIRIS-NG image composite to demarcate the spatial extension of ferruginous quartzite. The AVIRIS-NG image spectrum of a known kimberlite was also used, as a reference, to identify the surface signatures of new kimberlite within Fe-quartzite. We applied matched filtering and adaptive coherence estimator algorithms to detect surface signatures of kimberlite. The detected surface anomalies of kimberlite in each spectral map are consistent in shape, number and spatial extent. Subsequently, we integrated these maps into a unified surface anomaly map of kimberlite using multiplication operator for identifying the surface anomalies of kimberlite. We observed that the image spectra of these surface anomalies are similar to the laboratory and image spectra of a known pipe. Most of the detected new anomalies are circular and associated with geological lineaments delineated in the residual gravity anomaly map derived from the EIGEN 6C4 gravity model. The surface anomalies of kimberlite, identified in this research, substantiate the importance of detected anomalies for further exploration. [ABSTRACT FROM AUTHOR]

In this study, we have processed the spectral bands of airborne hyperspectral data of Advanced Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) data for delineating the surface signatures associated with the base metal mineralization in the Pur-Banera area in the Bhilwara district, Rajasthan, India.The primaryhost rocks of the Cu, Pb, Zn mineralization in the area are Banded Magnetite Quartzite (BMQ), unclassified calcareous silicates, and quartzite. We used ratio images derived from the scale and root mean squares (RMS) error imagesusing the multi-range spectral feature fitting (MRSFF) methodto delineate host rocks from the AVIRIS-NG image. The False Color Composites (FCCs) of different relative band depth images, derived from AVIRIS-NG spectral bands, were also used for delineating few minerals. These minerals areeither associated with the surface alteration resulting from the ore-bearing fluid migration orassociated with the redox-controlled supergene enrichments of the ore deposit.The results show that the AVIRIS-NG image products derived in this study can delineate surface signatures of mineralization in 1:10000 to 1:15000 scales to narrow down the targets for detailed exploration.This study alsoidentified the possible structural control over the knownsurface distribution of alteration and lithocap minerals of base metal mineralizationusing the ground-based residual magnetic anomaly map. This observationstrengthens the importance of the identified surface proxiesas an indicator of mineralization. X-ray fluorescence analysis of samples collectedfromselected locations within the study area confirms the Cu-Pb-Zn enrichment. The sulfide minerals were also identified in the microphotographs of polished sections of rock samples collected from the places where surface proxies of mineralization were observed in the field. This study justified the investigation to utilize surface signatures of mineralization identified using AVIRIS-NG dataand validated using field observations, geophysical, geochemical, and petrographical data. [ABSTRACT FROM AUTHOR]