Reflectance spectroscopy-guided broadband spectral derivative approach to detect glauconite-rich ... more Reflectance spectroscopy-guided broadband spectral derivative approach to detect glauconite-rich zones in
In the present study, we have attempted the delineation of limestone using different spectral map... more In the present study, we have attempted the delineation of limestone using different spectral mapping algorithms in ASTER data. Each spectral mapping algorithm derives limestone exposure map independently. Although these spectral maps are broadly similar to each other, they are also different at places in terms of spatial disposition of limestone pixels. Therefore, an attempt is made to integrate the results of these spectral maps to derive an integrated map using minimum noise fraction (MNF) method. The first MNF image is the result of two cascaded principal component methods suitable for preserving complementary information derived from each spectral map. While implementing MNF, noise or non-coherent pixels occurring within a homogeneous patch of limestone are removed first using shift difference method, before attempting principal component analysis on input spectral maps for deriving composite spectral map of limestone exposures. The limestone exposure map is further validated b...
ABSTRACT The successful implementation of Spectral Matching Measures (SMMs) often plays a crucial... more ABSTRACT The successful implementation of Spectral Matching Measures (SMMs) often plays a crucial role in material discrimination and classification using hyperspectral dataset. The commonly exploited SMMs, such as Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), and their hybrid, i.e., SIDSAMtan, show limited discrimination ability while discriminating spectrally similar materials. This study presents three new effective SMMs named Dice Spectral Similarity Coefficient (DSSC), Kumar–Johnson Spectral Similarity Coefficient (KJSSC), and a hybrid of DSSC and KJSSC, i.e., KJDSSCtan, for accurate discrimination of spectrally similar materials. A wide range of hyperspectral datasets of minerals and vegetation acquired under laboratory and real atmospheric conditions were used to compare and evaluate the performance of newly proposed and existing SMMs using Relative Spectral Discrimination Power (RSDPW) statistics. We also assessed the discrimination ability of the proposed and existing SMMs using spectra of selected minerals and vegetation species with an added component of random noise and linearly synthesized mixed spectra. An in-depth comparison and evaluation of different SMMs demonstrated that the discrimination power of the proposed SMMs is significantly higher than existing SMMs. The proposed SMMs also outperform existing SMMs when discriminating noisy and linearly synthesized mixed counterparts. The KJSSC and DSSC show similar efficacy in discriminating spectra of minerals and vegetation, whereas their hybrid measure, i.e., KJDSSCtan shows significantly higher spectral discrimination ability. Therefore, the newly proposed hybrid measure, i.e., KJDSSCtan is recommended over existing SMMs for successful material discrimination and classification using hyperspectral data.
In this study, we have processed the spectral bands of airborne hyperspectral data of Advanced Vi... more 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...
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
International Journal of Applied Earth Observation and Geoinformation, 2020
In spite of the dominance of traditional mineral exploration methods that demand physical charact... more In spite of the dominance of traditional mineral exploration methods that demand physical characterization of rocks and intense field work, remote sensing technologies have also evolved in the recent past to facilitate mineral exploration. In the present study, we have processed visible near infrared (VNIR) and shortwave infrared (SWIR) bands of Advanced space-borne thermal emission and reflection radiometer (ASTER) data to detect surface mineralization signatures in Mundiyawas-Khera area in Alwar basin, northeastern Rajasthan, India using spectral angle mapper (SAM). The potential of SAM method to detect target under variable illumination condition was used to delineate galena, chalcopyrite, malachite etc. as surface signatures of mineralization. It was ensured that the identified surface anomalies were spectrally pure using pixel purity index. Spectral anomalies were validated in the field and also using X-Ray diffraction data. Spectral anomaly maps thus derived were integrated using weight of evidence method with the lineament density, geochemical anomaly, bouger anomaly maps to identify few additional potential areas of mineralization. This study thus establishes the importance of remote sensing in mineral exploration to zero in on potentially ore rich but unexplored zones.
In this study, we have used visible near infrared (VNIR) and shortwave infrared (SWIR) spectral b... more In this study, we have used visible near infrared (VNIR) and shortwave infrared (SWIR) spectral bands of the Operational Land Imager (OLI) sensor of Landsat 8 satellite to delineate promising areas for iron exploration in the parts of Madhya Pradesh, India. OLI bands resampled laboratory reflectance spectra of Banded Iron Formation (BIF) were used as the reference to identify OLI spectral bands suitable in recording spectral features of Iron bearing minerals. Subsequently, BIFs were delineated in the principal component (PC) image prepared using those PC bands; which had opposite Eigen vector loading for the spectral bands; which recorded absorption minima and shoulder of the spectral feature of iron. Within the BIF, iron enriched zones were identified by integrating constrained energy minimization (CEM) maps of BIF, hematite and limonite-goethite. Integrated CEM map delineating iron enrichment zones was validated in the field based on measured Fe values of samples using X-ray Fluorescence Instrument.
Journal of the Indian Society of Remote Sensing, 2017
In this study, visible near infrared, shortwave infrared spectral bands of Landsat 8 satellite se... more In this study, visible near infrared, shortwave infrared spectral bands of Landsat 8 satellite sensor, two polarisation channel of L band ALOS-PALASAR sensor, SRTM-DEM derived digital elevation data were processed to delineate different geomorphic components of alluvial fans of Tista-Mahanada fan complex. We found image composite of independent components, principal components of Landsat 8 bands were effective in delineating proximal and distal fan segments. Fused images of Landsat 8 and ALOS data were used for enhancing incised distributaries and paleochannels. Field data on depositional sequence of fans, were used to substantiate the image based delineation. Topographic breaks along selected longitudinal profiles (identified with the changes in land use and drainage pattern) of digital elevation data were conjugately analysed using Landsat false colour composites. GPR survey along selected transect highlights the vertical dislocation in the recently deposited sequences of alluvial fan regime indicative of post depositional disturbances.
The Wajrakarur kimberlite Pipe 6 in Eastern Dharwar Craton, is hardly explored using latest groun... more The Wajrakarur kimberlite Pipe 6 in Eastern Dharwar Craton, is hardly explored using latest ground-based geophysical techniques. The present study uses the Very Low Frequency Electromagnetic (VLF-EM) method for understanding the aerial extension, depth and geometry of the kimberlite pipe. The VLF-EM data have been analyzed using Fraser Bltering of in-phase component, 3D Euler deconvolution of Fraser Bltered in-phase data, radially average power spectrum (RAPS) of VLF data (raw data) and 2D inversion of VLF data (raw data). The Fraser Bltered in-phase grid anomaly map has witnessed as an eAective tool for mapping extension of the kimberlite pipe. The maxima of Fraser Bltered in-phase component has been observed as a key parameter to delineate the conducting bodies. The high apparent current density in Karous-Hjelt (K-H) pseudo section locate relatively conducting body possibly associated with kimberlite pipe. Two depth interfaces at about 15 and 32 m have been delineated using RAPS. 3D Euler solution indicate dyke-like structure associated with kimberlite pipe having depth solutions ranging from 6 to 40 m with mode of depth 17 m in the study area. 2D resistivity sections indicate that causative bodies are in the depth range of 15-50 m. The results of VLF-EM study are well validated using geological borehole data over the study area reported by Geological Survey of India.
We used Advanced Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral ... more We used Advanced Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral data for deriving automated layered igneous intrusion maps by implementing the support vector machine (SVM) algorithm. We proposed a spectral analysis based approach to identify a set of optimum input spectral bands for deriving SVM-based maps of layered rocks of Sittampundi Layered Complex, India. We used three SVM models: (a) in the first model, we implemented SVM using nine spectral bands for deriving spectral indices to delineate different rocks; (b) in the second model, we used three Principal Component (PC) bands, which suitably preserved the spectral variance of all the bands used for deriving spectral indices of rocks; and (c) In the third model, all the spectral bands of AVIRIS-NG were used as input for the SVM model. We found PC based SVM model was superior as compared to the other two models in deriving automated map of layered rocks.
In this article, we discuss the potential of airborne hyperspectral data in mapping host rocks of... more In this article, we discuss the potential of airborne hyperspectral data in mapping host rocks of mineral deposits and surface signatures of mineralization using AVIRIS-NG data of a few important geological provinces in India. We present the initial results from the study sites covering parts of northwest India, as well as the Sittampundi Layered Complex (SLC) of Tamil Nadu and the Wajrakarur Kimberlite Field (WKF) of Andhra Pradesh from southern India. Modified spectral summary parameters, originally designed for MRO-CRISM data analysis, have been implemented on AVIRIS-NG mosaic of Jahazpur, Rajasthan for the automatic detection of phyllosilicates, carbonates and Fe-Mg-silicates. Spectral analysis over Ambaji and the surrounding areas indicates the presence of calcite across much of the study area with kaolinite occurring as well in the north and east of the study area. The deepest absorption features at around 2.20 and 2.32 μm and integrated band depth were used to identify and map the spatial distribution of phyllosilicates and carbonates. Suitable thresholds of band depths were applied to map prospective zones for marble exploration. The data over SLC showed potential of AVIRIS-NG hyperspectral data in detecting mafic cumulates and chromitites. We also have demonstrated the potential of AVIRIS-NG data in detecting kimberlite pipe exposures in parts of WKF.
In the present study, broad band emissivity, apparent thermal inertia and albedo image products h... more In the present study, broad band emissivity, apparent thermal inertia and albedo image products have been derived based on processing of Advanced Spaceborne Thermal Emission and reflection (ASTER) data and analyzed their potential for delineating different metasedimentary units of Aravalli Group in Rajasthan. The major focus of the work is to analyze the potential of emissivity bands with respect to conjugated image product of emissivity, albedo and inertia for discriminating different rock types. In this regard, it was observed that combined use of emissivity, thermal inertia and albedo was effective for delineating different rock types as the combined variation of thermo-physical and mineralogical properties were recorded in these parameters. On the other hand, broad band emissivity spectra of rocks of the study area had subtle contrast, which was not optimum for the discrimination of different rock types. This was evident in the ASTER derived emissivity composite in which spatial delineation of rocks of the study area was not possible. Therefore, it is concluded that the combined use of albedo, thermal inertia and emissivity was suitable to delineate different metasedimentary rocks. This was also evident from the three dimensional data plot of selected emissivity band, inertia and albedo which separated different rocks from one another.
International Journal of Applied Earth Observation and Geoinformation, 2020
In this study, we proposed an automated lithological mapping approach by using spectral enhanceme... more In this study, we proposed an automated lithological mapping approach by using spectral enhancement techniques and Machine Learning Algorithms (MLAs) using Airborne Visible Infrared Imaging Spectroradiometer-Next Generation (AVIRIS-NG) hyperspectral data in the greenstone belt of the Hutti area, India. We integrated spectral enhancement techniques such as Principal Component Analysis (PCA) and Independent Component Analysis (ICA) transformation and different MLAs for an accurate mapping of rock types. A conjugate utilization of conventional geological map and spectral enhancement products derived from ASTER data were used for the preparation of a high-resolution reference lithology map. Feature selection and extraction methods were applied on the AVIRIS-NG data to derive different input dataset such as (a) all spectral bands, (b) shortwave infrared bands, (c) Joint Mutual Information Maximization (JMIM) based optimum bands, and (d) optimum bands using PCA, to choose optimum input dataset for automated lithological mapping. The comparative analysis of different MLAs shows that the Support Vector Machine (SVM) outperforms other Machine Learning (ML) models. The SVM achieved an Overall Accuracy (OA) and Kappa Coefficient (k) of 85.48% and 0.83, respectively, using JMIM based optimum bands. The JMIM based optimum bands were more suitable than other input datasets to classify most of the lithological units (i.e. metabasalt, amphibolite, granite, acidic intrusive and migmatite) within the study area. The sensitivity analysis performed in this study illustrates that the SVM is less sensitive to the number of samples and mislabeling in the model training than other MLAs. The obtained high-resolution classified map with accurate litho-contacts of amphibolite, metabasalt, and granite can be coupled with an alteration map of the area for targeting the potential zone of gold mineralization.
The contrast in the emissivity spectra of phosphorite and associated carbonate rock can be used a... more The contrast in the emissivity spectra of phosphorite and associated carbonate rock can be used as a guide to delineate phosphorite within dolomite. The thermal emissivity spectrum of phosphorite is characterized by a strong doublet emissivity feature with their absorption minima at 9 µm and 9.5 µm; whereas, host rock dolomite has relatively subdued emissivity minima at ~9 µm. Using the contrast in the emissivity spectra of phosphorite and dolomite, data obtained by the thermal bands of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor were processed to delineate phosphorite within dolomite. A decorrelation stretched ASTER radiance composite could not enhance phosphorite rich zones within the dolomite host rock. However, a decorrelation stretched image composite of selected emissivity bands derived using the emissivity normalization method was suitable to enhance large surface exposures of phosphorite. We have found that the depth of the emissivity minima...
In this article, we have processed Landsat-8 spectral bands, ground gravity, and magnetic data fo... more In this article, we have processed Landsat-8 spectral bands, ground gravity, and magnetic data for delineating the mafic cumulates within the anorthositic-layered complex in Sittampundi, Tamilnadu, India. In this regard, surface anomaly map of mafic cumulates was derived by processing spectral bands of Operational Land Imager (OLI) sensor using matched filtering method. Residual gravity, magnetic anomaly maps are also derived. Spatial position of geophysical anomalies corroborate well with the spectral anomalies. A promising zone of chromitite occurrences is identified at the eastern fringe of the study area based on the concurrence of spectral and geophysical anomalies. Spatial profiles of geophysical and spectral anomalies around this promising zone are similar to the respective spatial profiles observed around the known chromite bearing mafic cumulates. Depth continuity of the mafic cumulates is confirmed by deriving of gravity and magnetic anomaly map at different depth using upward continuation filters to confirm concealed deposit.
We have collected, processed and analysed the reflectance spectra of representative chromitite sa... more We have collected, processed and analysed the reflectance spectra of representative chromitite samples of spot type, clot type and disseminated type textural variants to understand the diagnostic spectral features of each of these samples. We have found that the reflectance spectrum of each textural variant is distinct from the spectra of other variants despite having few common absorption features. Spectral features of chromitite samples are governed by the spectra of two dominant minerals, chromite and chlorite. Spectral features of chromitite at 550 nm and 1100 nm are governed by electronic transition process in Fe 3+ and crystal field effect in Fe 2+ ions present in chromite structure respectively. On the other hand, spectral features at 1400 nm, 1900 nm and 2300 nm are related to the vibration of O-H, H-OH and metal hydroxide bonds in chlorite. Amongst these features, the spectral feature at 1100 nm (due to Fe 2+ in chromite grains) is common to all three major textural varieties of chromitite samples studied here. Electron probe micro analysis (EPMA) data of chromite and chlorite grains of each texture are used to relate the presence and abundance of Fe 2+ (in chromite grains) with absorption feature. Width of the 1100 nm feature has a correlation value 0.95, while depth of the same feature has a correlation value 0.94 with the abundance of chromite mineral estimated using modal analysis of chromite samples. Therefore, spectrometric parameter of 1100 nm spectral feature of chromitite can be used as proxy for estimating modal abundance of chromite in chromitite samples after estimating deposit specific correlation coefficient.
Reflectance spectroscopy-guided broadband spectral derivative approach to detect glauconite-rich ... more Reflectance spectroscopy-guided broadband spectral derivative approach to detect glauconite-rich zones in
In the present study, we have attempted the delineation of limestone using different spectral map... more In the present study, we have attempted the delineation of limestone using different spectral mapping algorithms in ASTER data. Each spectral mapping algorithm derives limestone exposure map independently. Although these spectral maps are broadly similar to each other, they are also different at places in terms of spatial disposition of limestone pixels. Therefore, an attempt is made to integrate the results of these spectral maps to derive an integrated map using minimum noise fraction (MNF) method. The first MNF image is the result of two cascaded principal component methods suitable for preserving complementary information derived from each spectral map. While implementing MNF, noise or non-coherent pixels occurring within a homogeneous patch of limestone are removed first using shift difference method, before attempting principal component analysis on input spectral maps for deriving composite spectral map of limestone exposures. The limestone exposure map is further validated b...
ABSTRACT The successful implementation of Spectral Matching Measures (SMMs) often plays a crucial... more ABSTRACT The successful implementation of Spectral Matching Measures (SMMs) often plays a crucial role in material discrimination and classification using hyperspectral dataset. The commonly exploited SMMs, such as Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), and their hybrid, i.e., SIDSAMtan, show limited discrimination ability while discriminating spectrally similar materials. This study presents three new effective SMMs named Dice Spectral Similarity Coefficient (DSSC), Kumar–Johnson Spectral Similarity Coefficient (KJSSC), and a hybrid of DSSC and KJSSC, i.e., KJDSSCtan, for accurate discrimination of spectrally similar materials. A wide range of hyperspectral datasets of minerals and vegetation acquired under laboratory and real atmospheric conditions were used to compare and evaluate the performance of newly proposed and existing SMMs using Relative Spectral Discrimination Power (RSDPW) statistics. We also assessed the discrimination ability of the proposed and existing SMMs using spectra of selected minerals and vegetation species with an added component of random noise and linearly synthesized mixed spectra. An in-depth comparison and evaluation of different SMMs demonstrated that the discrimination power of the proposed SMMs is significantly higher than existing SMMs. The proposed SMMs also outperform existing SMMs when discriminating noisy and linearly synthesized mixed counterparts. The KJSSC and DSSC show similar efficacy in discriminating spectra of minerals and vegetation, whereas their hybrid measure, i.e., KJDSSCtan shows significantly higher spectral discrimination ability. Therefore, the newly proposed hybrid measure, i.e., KJDSSCtan is recommended over existing SMMs for successful material discrimination and classification using hyperspectral data.
In this study, we have processed the spectral bands of airborne hyperspectral data of Advanced Vi... more 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...
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
International Journal of Applied Earth Observation and Geoinformation, 2020
In spite of the dominance of traditional mineral exploration methods that demand physical charact... more In spite of the dominance of traditional mineral exploration methods that demand physical characterization of rocks and intense field work, remote sensing technologies have also evolved in the recent past to facilitate mineral exploration. In the present study, we have processed visible near infrared (VNIR) and shortwave infrared (SWIR) bands of Advanced space-borne thermal emission and reflection radiometer (ASTER) data to detect surface mineralization signatures in Mundiyawas-Khera area in Alwar basin, northeastern Rajasthan, India using spectral angle mapper (SAM). The potential of SAM method to detect target under variable illumination condition was used to delineate galena, chalcopyrite, malachite etc. as surface signatures of mineralization. It was ensured that the identified surface anomalies were spectrally pure using pixel purity index. Spectral anomalies were validated in the field and also using X-Ray diffraction data. Spectral anomaly maps thus derived were integrated using weight of evidence method with the lineament density, geochemical anomaly, bouger anomaly maps to identify few additional potential areas of mineralization. This study thus establishes the importance of remote sensing in mineral exploration to zero in on potentially ore rich but unexplored zones.
In this study, we have used visible near infrared (VNIR) and shortwave infrared (SWIR) spectral b... more In this study, we have used visible near infrared (VNIR) and shortwave infrared (SWIR) spectral bands of the Operational Land Imager (OLI) sensor of Landsat 8 satellite to delineate promising areas for iron exploration in the parts of Madhya Pradesh, India. OLI bands resampled laboratory reflectance spectra of Banded Iron Formation (BIF) were used as the reference to identify OLI spectral bands suitable in recording spectral features of Iron bearing minerals. Subsequently, BIFs were delineated in the principal component (PC) image prepared using those PC bands; which had opposite Eigen vector loading for the spectral bands; which recorded absorption minima and shoulder of the spectral feature of iron. Within the BIF, iron enriched zones were identified by integrating constrained energy minimization (CEM) maps of BIF, hematite and limonite-goethite. Integrated CEM map delineating iron enrichment zones was validated in the field based on measured Fe values of samples using X-ray Fluorescence Instrument.
Journal of the Indian Society of Remote Sensing, 2017
In this study, visible near infrared, shortwave infrared spectral bands of Landsat 8 satellite se... more In this study, visible near infrared, shortwave infrared spectral bands of Landsat 8 satellite sensor, two polarisation channel of L band ALOS-PALASAR sensor, SRTM-DEM derived digital elevation data were processed to delineate different geomorphic components of alluvial fans of Tista-Mahanada fan complex. We found image composite of independent components, principal components of Landsat 8 bands were effective in delineating proximal and distal fan segments. Fused images of Landsat 8 and ALOS data were used for enhancing incised distributaries and paleochannels. Field data on depositional sequence of fans, were used to substantiate the image based delineation. Topographic breaks along selected longitudinal profiles (identified with the changes in land use and drainage pattern) of digital elevation data were conjugately analysed using Landsat false colour composites. GPR survey along selected transect highlights the vertical dislocation in the recently deposited sequences of alluvial fan regime indicative of post depositional disturbances.
The Wajrakarur kimberlite Pipe 6 in Eastern Dharwar Craton, is hardly explored using latest groun... more The Wajrakarur kimberlite Pipe 6 in Eastern Dharwar Craton, is hardly explored using latest ground-based geophysical techniques. The present study uses the Very Low Frequency Electromagnetic (VLF-EM) method for understanding the aerial extension, depth and geometry of the kimberlite pipe. The VLF-EM data have been analyzed using Fraser Bltering of in-phase component, 3D Euler deconvolution of Fraser Bltered in-phase data, radially average power spectrum (RAPS) of VLF data (raw data) and 2D inversion of VLF data (raw data). The Fraser Bltered in-phase grid anomaly map has witnessed as an eAective tool for mapping extension of the kimberlite pipe. The maxima of Fraser Bltered in-phase component has been observed as a key parameter to delineate the conducting bodies. The high apparent current density in Karous-Hjelt (K-H) pseudo section locate relatively conducting body possibly associated with kimberlite pipe. Two depth interfaces at about 15 and 32 m have been delineated using RAPS. 3D Euler solution indicate dyke-like structure associated with kimberlite pipe having depth solutions ranging from 6 to 40 m with mode of depth 17 m in the study area. 2D resistivity sections indicate that causative bodies are in the depth range of 15-50 m. The results of VLF-EM study are well validated using geological borehole data over the study area reported by Geological Survey of India.
We used Advanced Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral ... more We used Advanced Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral data for deriving automated layered igneous intrusion maps by implementing the support vector machine (SVM) algorithm. We proposed a spectral analysis based approach to identify a set of optimum input spectral bands for deriving SVM-based maps of layered rocks of Sittampundi Layered Complex, India. We used three SVM models: (a) in the first model, we implemented SVM using nine spectral bands for deriving spectral indices to delineate different rocks; (b) in the second model, we used three Principal Component (PC) bands, which suitably preserved the spectral variance of all the bands used for deriving spectral indices of rocks; and (c) In the third model, all the spectral bands of AVIRIS-NG were used as input for the SVM model. We found PC based SVM model was superior as compared to the other two models in deriving automated map of layered rocks.
In this article, we discuss the potential of airborne hyperspectral data in mapping host rocks of... more In this article, we discuss the potential of airborne hyperspectral data in mapping host rocks of mineral deposits and surface signatures of mineralization using AVIRIS-NG data of a few important geological provinces in India. We present the initial results from the study sites covering parts of northwest India, as well as the Sittampundi Layered Complex (SLC) of Tamil Nadu and the Wajrakarur Kimberlite Field (WKF) of Andhra Pradesh from southern India. Modified spectral summary parameters, originally designed for MRO-CRISM data analysis, have been implemented on AVIRIS-NG mosaic of Jahazpur, Rajasthan for the automatic detection of phyllosilicates, carbonates and Fe-Mg-silicates. Spectral analysis over Ambaji and the surrounding areas indicates the presence of calcite across much of the study area with kaolinite occurring as well in the north and east of the study area. The deepest absorption features at around 2.20 and 2.32 μm and integrated band depth were used to identify and map the spatial distribution of phyllosilicates and carbonates. Suitable thresholds of band depths were applied to map prospective zones for marble exploration. The data over SLC showed potential of AVIRIS-NG hyperspectral data in detecting mafic cumulates and chromitites. We also have demonstrated the potential of AVIRIS-NG data in detecting kimberlite pipe exposures in parts of WKF.
In the present study, broad band emissivity, apparent thermal inertia and albedo image products h... more In the present study, broad band emissivity, apparent thermal inertia and albedo image products have been derived based on processing of Advanced Spaceborne Thermal Emission and reflection (ASTER) data and analyzed their potential for delineating different metasedimentary units of Aravalli Group in Rajasthan. The major focus of the work is to analyze the potential of emissivity bands with respect to conjugated image product of emissivity, albedo and inertia for discriminating different rock types. In this regard, it was observed that combined use of emissivity, thermal inertia and albedo was effective for delineating different rock types as the combined variation of thermo-physical and mineralogical properties were recorded in these parameters. On the other hand, broad band emissivity spectra of rocks of the study area had subtle contrast, which was not optimum for the discrimination of different rock types. This was evident in the ASTER derived emissivity composite in which spatial delineation of rocks of the study area was not possible. Therefore, it is concluded that the combined use of albedo, thermal inertia and emissivity was suitable to delineate different metasedimentary rocks. This was also evident from the three dimensional data plot of selected emissivity band, inertia and albedo which separated different rocks from one another.
International Journal of Applied Earth Observation and Geoinformation, 2020
In this study, we proposed an automated lithological mapping approach by using spectral enhanceme... more In this study, we proposed an automated lithological mapping approach by using spectral enhancement techniques and Machine Learning Algorithms (MLAs) using Airborne Visible Infrared Imaging Spectroradiometer-Next Generation (AVIRIS-NG) hyperspectral data in the greenstone belt of the Hutti area, India. We integrated spectral enhancement techniques such as Principal Component Analysis (PCA) and Independent Component Analysis (ICA) transformation and different MLAs for an accurate mapping of rock types. A conjugate utilization of conventional geological map and spectral enhancement products derived from ASTER data were used for the preparation of a high-resolution reference lithology map. Feature selection and extraction methods were applied on the AVIRIS-NG data to derive different input dataset such as (a) all spectral bands, (b) shortwave infrared bands, (c) Joint Mutual Information Maximization (JMIM) based optimum bands, and (d) optimum bands using PCA, to choose optimum input dataset for automated lithological mapping. The comparative analysis of different MLAs shows that the Support Vector Machine (SVM) outperforms other Machine Learning (ML) models. The SVM achieved an Overall Accuracy (OA) and Kappa Coefficient (k) of 85.48% and 0.83, respectively, using JMIM based optimum bands. The JMIM based optimum bands were more suitable than other input datasets to classify most of the lithological units (i.e. metabasalt, amphibolite, granite, acidic intrusive and migmatite) within the study area. The sensitivity analysis performed in this study illustrates that the SVM is less sensitive to the number of samples and mislabeling in the model training than other MLAs. The obtained high-resolution classified map with accurate litho-contacts of amphibolite, metabasalt, and granite can be coupled with an alteration map of the area for targeting the potential zone of gold mineralization.
The contrast in the emissivity spectra of phosphorite and associated carbonate rock can be used a... more The contrast in the emissivity spectra of phosphorite and associated carbonate rock can be used as a guide to delineate phosphorite within dolomite. The thermal emissivity spectrum of phosphorite is characterized by a strong doublet emissivity feature with their absorption minima at 9 µm and 9.5 µm; whereas, host rock dolomite has relatively subdued emissivity minima at ~9 µm. Using the contrast in the emissivity spectra of phosphorite and dolomite, data obtained by the thermal bands of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor were processed to delineate phosphorite within dolomite. A decorrelation stretched ASTER radiance composite could not enhance phosphorite rich zones within the dolomite host rock. However, a decorrelation stretched image composite of selected emissivity bands derived using the emissivity normalization method was suitable to enhance large surface exposures of phosphorite. We have found that the depth of the emissivity minima...
In this article, we have processed Landsat-8 spectral bands, ground gravity, and magnetic data fo... more In this article, we have processed Landsat-8 spectral bands, ground gravity, and magnetic data for delineating the mafic cumulates within the anorthositic-layered complex in Sittampundi, Tamilnadu, India. In this regard, surface anomaly map of mafic cumulates was derived by processing spectral bands of Operational Land Imager (OLI) sensor using matched filtering method. Residual gravity, magnetic anomaly maps are also derived. Spatial position of geophysical anomalies corroborate well with the spectral anomalies. A promising zone of chromitite occurrences is identified at the eastern fringe of the study area based on the concurrence of spectral and geophysical anomalies. Spatial profiles of geophysical and spectral anomalies around this promising zone are similar to the respective spatial profiles observed around the known chromite bearing mafic cumulates. Depth continuity of the mafic cumulates is confirmed by deriving of gravity and magnetic anomaly map at different depth using upward continuation filters to confirm concealed deposit.
We have collected, processed and analysed the reflectance spectra of representative chromitite sa... more We have collected, processed and analysed the reflectance spectra of representative chromitite samples of spot type, clot type and disseminated type textural variants to understand the diagnostic spectral features of each of these samples. We have found that the reflectance spectrum of each textural variant is distinct from the spectra of other variants despite having few common absorption features. Spectral features of chromitite samples are governed by the spectra of two dominant minerals, chromite and chlorite. Spectral features of chromitite at 550 nm and 1100 nm are governed by electronic transition process in Fe 3+ and crystal field effect in Fe 2+ ions present in chromite structure respectively. On the other hand, spectral features at 1400 nm, 1900 nm and 2300 nm are related to the vibration of O-H, H-OH and metal hydroxide bonds in chlorite. Amongst these features, the spectral feature at 1100 nm (due to Fe 2+ in chromite grains) is common to all three major textural varieties of chromitite samples studied here. Electron probe micro analysis (EPMA) data of chromite and chlorite grains of each texture are used to relate the presence and abundance of Fe 2+ (in chromite grains) with absorption feature. Width of the 1100 nm feature has a correlation value 0.95, while depth of the same feature has a correlation value 0.94 with the abundance of chromite mineral estimated using modal analysis of chromite samples. Therefore, spectrometric parameter of 1100 nm spectral feature of chromitite can be used as proxy for estimating modal abundance of chromite in chromitite samples after estimating deposit specific correlation coefficient.
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Papers by Arindam Guha