Alok Porwal

ABSTRACT The across-track illumination variation in Earth Observing-1 (EO-1) Hyperion images is a result of wavelength-shift and full-width-at-half-maximum (FWHM)-shift in the cross-track direction. Correction in across-track illumination variation is necessary for accurate spectral matching and classification. This contribution reviews the available methods for the correction of across-track illumination variation, and evaluates them for correcting a Hyperion image of study area around the Udaipur city in western India. We also describe and demonstrated a new technique for correcting these artefacts. For each band, the spatial trends of (a) nonlinear shifts in the nominal centre wavelengths of bands across the image columns and (b) nonlinear changes in the nominal FWHM of bands across the image columns are modelled using quadratic regression and are compensated using a radiance correction factor estimated from the columns characterized by minimum illumination variations in a spectrally flat area of the image. A series of statistical measures, spectral matching, minimum noise fraction transform (MNF) images, and post-correction classification results were used to evaluate the performance of the proposed algorithm vis-à-vis some of the previous methods on the Hyperion image of the study area. The results indicate that the proposed method effectively corrects the across-track illumination effects in the Hyperion image of the study area, and also show better performance in lithological as well as for land-use and land-cover mapping, as compared to the other previous methods.

Hyperion data contain significant amount of Salt-and-Pepper/random noise and stripes even in L1R radiance images, which give rise to false absorption features appear in the radiance spectra as well as in reflectance spectra after atmospheric correction, such features can potentially mislead spectral analysis. In this paper, we present a hybrid approach for correcting pixels with no radiance values and removing Salt-and-Pepper/random noise and stripes from Hyperion radiance image. In this study, "no-data" valued pixels are identified and corrected using local median filter, an MNF transformation is used in tandem to reduce random noise, a low-pass filtering is used to correct the bad-columns and global stripes, and a Local-Brightness-Normalization based algorithm is used to detect and correct local stripes from Hyperion L1R radiance images to get random noise free and destriped image.

A predictive model for mineral potential mapping based on fuzzy set theory is described. It is tested in the south-central part of the Aravalli province (western India), which hosts a number of conformable sediment-hosted basemetal deposits. Recognition criteria for basemetal mineralisation were identified on the basis of published work on metallogenesis in Aravalli province. A regional GIS was then established in ArcView GIS software using several public-domain geodata sets. These were reviewed, processed, reclassified and gridded to generate multi-class lithological, stratigraphic, structural, magnetic and lineament-density maps. Weights were assigned to each evidential map, and also to each class of the maps, on the basis of their significance as guides to the occurrence of basemetal mineralisation. These were used to calculate fuzzy membership values for all classes. The values thus determined were combined using fuzzy algebraic sum and fuzzy algebraic product operators to gener...

Hyperspectral data pose challenges to image interpretation, because of the need for calibration, redundancy in information, and high data volume due to large dimensionality of the feature space. In this article, a general framework is presented for working with hyperspectral imagery, including removal of atmospheric effects, imaging spectroscopy, dimensionality reduction and classification of imagery. The phenomenon of mixture modelling is briefly discussed, followed by a recent development in mapping the classes at sub-pixel level based on the principle of superresolution.

Mineral prospectivity mapping of an area involves demarcation of potentially mineralized zones based on geologic features associated with the targeted mineral deposits. These features are sometimes directly observable and mapped; more often, their presence is inferred from their responses in various geoscience datasets, which are appropriately processed, generally in a GIS software environment, to derive their spatial proxies, also called predictor maps layers. Most approaches to mineral prospectivity mapping use mathematical models to approximate the relation between predictor map layers and the presence (or absence) of the targeted mineral deposits and to label unique combinations of spatially coincident predictor map layers as mineralized or barren. Essentially, the procedure involves recognizing and distinguishing the patterns of predictor map layers associated with mineralized locations from those associated with barren locations.

Single-image super-resolution (SISR) techniques attempt to reconstruct the finer resolution version of a given image from its coarser version. In the SISR of hyperspectral data sets, the simultaneous consideration of spectral bands is crucial for ensuring the spectral fidelity. However, the high spectral resolution of these data sets affects the performance of conventional approaches. This research proposes the design of 3-D convolutional neural network (CNN)-based SISR architectures that can map the spatial–spectral characteristics of hypercubes to a finer spatial resolution. The proposed approaches facilitate the simultaneous optimization of sparse codes and dictionaries with regard to the super-resolution objective. Our main hypothesis is that the consideration of spectral aspects is essential for the spatial enhancement of hyperspectral images. Also, we propose that the regularized deconvolution of a coarser-scale hypercube, using learned 3-D filters, yields the required high-resolution version. Based on these hypotheses, a convolution–deconvolution framework is proposed to super-resolve the hypercubes in parallel with the reconstruction of a set of regularizing features. Novel sparse code optimization sub-networks proposed in this article give better performance than the existing strategies. The endmember similarities and hyperspectral image prior are considered while designing the proposed loss functions. In order to improve the generalizability, a collaborative spectral unmixing strategy is employed to refine the spectral base of the super-resolved result. The spatial–spectral accuracy of the super-resolved hypercubes, in terms of the validity of regularizing features and endmembers, is explored to devise an optimal ensemble strategy. The experiments, over different data sets, confirm better accuracy of the proposed frameworks compared to the prominent approaches.

Abstract Juventae Chasma, an isolated depression northeast of the Valles Marineris trough system, hosts four mounds of light-toned, layered materials. These are erosional remnants interpreted to consist of sedimentary rocks. The geological setting of Juventae Chasma is a complex amalgamation of terrains and surfaces of different morphologies, ages, and structures. Most previous published studies assumed or interpreted that the light-toned mound-forming materials were deposited in the chasm after it opened or began to open. Here, we use detailed observations of the geologic setting, the nature of chasm wall rocks, and the distribution and nature of the contacts of the light-toned materials with adjacent geologic materials to argue that the light-toned mounds in Juventae Chasma are, more likely, remnants of light-toned materials that existed in the subsurface before the chasm opened up. The rock cut by the chasm was not a monolithic unit, (e.g., lava flows) and might have included both light-toned and dark-toned sedimentary rocks bearing a range of diagenetic properties. The light-toned materials were deposited (as clasts, precipitates, or both) within craters or depressions that were filled, buried, lithified, and then exposed when Juventae Chasma formed. Because the sedimentary rock types and stratal package properties differ from one mound to the next, the buried craters or depressions could have existed at different times and provide sedimentary records of different environments that existed at different times during the planet's early history (Noachian Period). Upon exposure, these materials, as well as chasm wall rocks and chaotic terrain blocks, underwent differential erosion as a function of rock physical properties to produce the geomorphic expressions observed today.

Abstract Herein we provide an overview of science and technology involved in remote sensing, and outlines some practical constraints in applications to geological problems. We further summarize diagnostic spectral features of important geological material that can be detected using satellite- and air-borne remote sensing. Finally, the papers contained in the special issue are briefly introduced.

Thermal Infrared (TIR) remote sensing measures emitted radiation of Earth in the thermal region of electromagnetic spectrum. This information can be useful in studying sub-surface features such as buried palaeochannels, which are ancient river systems that have dried up over time and are now buried under soil cover or overlying sediments in the present landscape. Therefore they have little or no expression on the surface topography. Study of these paleo channels has wide applications in the fields of uranium exploration and ground water hydrology. Identifying paleo channels using remote sensing technique is a cost-effective means of narrowing down search areas and thereby aids in ground exploration. The difference in thermal properties between the paleo channel-fill sediments and the surrounding bed-rock is the key to demarcate these channels. This study uses five TIR bands of day-time Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) L1A data for delineation of paleo-systems in the DeGrussa area of the Capricorn Orogen in Western Australia. The temperature-emissivity separation algorithm is applied to obtain kinetic temperature and emissivity images. Sharp contrasts in kinetic temperature and emissivity values are used to demarcate the channel boundaries. Profiles of topographic elevation, temperature and emissivity values are plotted for different sections of the interpreted channels and compared to distinguish the surface channels from sub-surface channels, and also to interpret the thickness and nature of the paleo channel-fill sediments. The results are validated using core-drilling litho logs and field exploration data.

In this work, we present urban area mapping from full-polarimetric synthetic aperture radar (SAR) data using fuzzy inference system (FIS). In particular, our aim is to utilize the profound knowledge available about scattering mechanism from urban targets to delineate urban environment. In this approach, we have utilized the recently developed polarimetric SAR scattering power decomposition technique (SD-Y4O) given in Bhattacharya et. al. The improved powers along with some other polarimetric parameters were used in this study. A suitable normalization procedure was adapted to handle the skewness in the estimated parameters. The fuzzy if-then rules were constructed from the in-depth knowledge of scattering mechanisms from an urban environment. Suitable methods were introduced to define the fuzzy inference system. The defuzzified membership values were thresholded using an unsupervised clustering method (k-means). The pixels lying in the range [μmax−σ, μmax+σ] corresponds to urban areas where µmax is the largest cluster center and σ is the standard deviation of the cluster corresponding to µmax. The extracted urban area is in visually good agreement with the high resolution optical image. ALOS PALSAR full-polarimetric L-band SAR data has been used in this study.

3D modelling provides a representation of the uncertainty when sparse or no data are available for a region. 3D geological model can provide important insights on the geometrical behavior of the rock units and also the locations of the crustal scale structures which in turn can provide the 3D (depth) and 4D (time) geodynamic evolution of the region. The Aravalli-Delhi Fold Belt which is located in the state of Rajasthan, India covers the geological history from Archaean to Recent. It underwent two stage tectonic evolution during Proterozoic, which lead to the formation of substantial Sediment-Hosted Lead-Zinc deposits i.e. Rampura-Agucha deposit (∼1800 Ma.), Rajpura-Dariba deposit (∼1800 Ma), Pur-Banera deposit (∼1800 Ma) and Zawar deposit (∼1700 Ma). The Sediment-Hosted Lead-Zinc deposits with easy surface expressions have already been discovered based on the conventional 2D conceptual geological models approach, therefore now it is very important to discover and explore the deep-s...

. A two-stage fuzzy inference system (FIS) is applied to prospectivity modelling and exploration-target delineation for REE deposits associated with carbonatite-alkaline complexes in western part of the state of Rajasthan in India. The design of the FIS and selection of the input predictor map are guided by a generalised conceptual model of carbonatite-alkaline-complexes-related REE mineral systems. In the first stage, three FISs are constructed to map the fertility and favourable geodynamic settings, favourable lithospheric architecture, and favourable shallow crustal (near-surface) architecture, respectively, for REE deposits in the study area. In the second stage, the outputs of the above FISs are integrated to map the prospectivity of REE deposits in the study area. Stochastic and systemic uncertainties in the output prospectivity maps are estimated to facilitate decision making regarding the selection of exploration targets. The study led to identification of prospective targets in the Kamthai-Sarnu-Dandeli and Mundwara regions, where project-scale detailed ground exploration is recommended. Low-confidence targets were identified in the south of the Siwana ring complex, north and northeast of Sarnu-Dandeli, south of Barmer, and south of Mundwara. Detailed geochemical sampling and high-resolution magnetic and radiometric surveys are recommended in these areas to increase the level of confidence in the prospectivity of these targets before undertaking project-scale ground exploration. The prospectivity-analysis workflow presented in this paper can be applied to delineation of exploration targets in geodynamically similar regions globally such as Afar province (East Africa), Paraná-Etendeka (South America and Africa), Siberian (Russia), East European Craton-Kola (Eastern Europe), Central Iapetus (North America, Greenland and the Baltic region), and the Pan-superior province (North America).

Most available studies in lithological mapping using spaceborne multispectral and hyperspectral remote sensing images employ different classification and spectral matching algorithms for performing this task; however, our experiment reveals that no single algorithm renders satisfactory results. Therefore, a new approach based on an ensemble of classifiers is presented for lithological mapping using remote sensing images in this paper, which returns enhanced accuracy. The proposed method uses a weighted pooling approach for lithological mapping at each pixel level using the agreement of the class accuracy, overall accuracy and kappa coefficient from the multi-classifiers of an image. The technique is implemented in four steps; (1) classification images are generated using a variety of classifiers; (2) accuracy assessments are performed for each class, overall classification and estimation of kappa coefficient for every classifier; (3) an overall within-class accuracy index is estimat...

Hydrothermal ore deposits provide a record of excess energy flux and mass transfer in the Earth's lithosphere. The heterogeneous distribution of ore deposits in space and time provides a challenge to uniformitarian geodynamic and tectonic concepts, but unusual thermal and structural events often coincide with high mineral endowment. In the Australian Proterozoic continental backarcs and intracratonic rifts host large resources

The Proterozoic Mt Isa Inlier in Queensland, Australia, contains significant hydrothermal base-metal deposits including shale hosted lead-zinc sulphides, Broken Hill-type lead-zinc-silver, as well as iron-oxide copper-gold and Mount Isa-type iron-sulphide copper deposits. Mount Isa-type epithermal copper deposits generally occur in the Western Succession of the Inlier and are hosted by ca 1650 Ma brecciated sedimentary rocks of the Cover Sequences

The Proterozoic Aravalli orogen in the state of Rajasthan, northwestern India, constitutes the most important metal-logenic province for base-metal deposits in India and hosts the entire economically viable lead-zinc resource-base of the country. The orogen evolved through near-orderly ...

The conceptual understanding of crustal extension and rifting is largely based on the premise of structural continuity along strike, even though architecture and strain in extensional provinces can vary substantially. Here we present an example of such along-strike variation: the extension of continental crust in the Menderes Massif of western Turkey. The Menderes Massif is a metamorphic basement complex comprising

ABSTRACT Hydrated minerals have been identified in an unnamed crater (centred at 31ᵒ 26’ 43.71’’S; 72ᵒ 00’ 28.77’’W) located in Thaumasia region in Mars using CRISM multispectral data. This region lies South of the Valles Marineris canyon system. Preliminary work indicates presence of light toned hydrated minerals showing distinct layering. The light-toned layers are similar to the ones found in the Valles Marineris, and in the range of hundred meters. The layers are exposed along the base of the crater wall and at places accumulate as dunes. In this paper we report the mineralogy and stratigraphy of the light-toned layers from the crater and the environs.

Approaches to mineral potential mapping based on weights of evidence generally use binary maps, whereas, real-world geospatial data are mostly multi-class in nature. The consequent reclassification of multi-class maps into binary maps is a simplification that might result in ...

This paper describes the geology and tectonics of the Paleoproterozoic Kumasi Basin, Ghana, West Africa, as applied to predictive mapping of prospectivity for orogenic gold mineral systems within the basin. The main objective of the study was to identify the most prospective ground for orogenic gold deposits within the Paleoproterozoic Kumasi Basin. A knowledge-driven, two-stage fuzzy inference system (FIS) was used for prospectivity modelling. The spatial proxies that served as input to the FIS were derived based on a conceptual model of gold mineral systems in the Kumasi Basin. As a first step, key components of the mineral system were predictively modelled using a Mamdani-type FIS. The second step involved combining the individual FIS outputs using a conjunction (product) operator to produce a continuous-scale prospectivity map. Using a cumulative area fuzzy favourability (CAFF) curve approach, this map was reclassified into a ternary prospectivity map divided into high-prospectivity, moderate-prospectivity and low-prospectivity areas, respectively. The spatial distribution of the known gold deposits within the study area relative to that of the prospective and non-prospective areas served as a means for evaluating the capture efficiency of our model. Approximately 99% of the known gold deposits and occurrences fall within high- and moderate-prospectivity areas that occupy 31% of the total study area. The high- and moderate-prospectivity areas illustrated by the prospectivity map are elongate features that are spatially coincident with areas of structural complexity along and reactivation during D4 of NE–SW-striking D2 thrust faults and subsidiary structures, implying a strong structural control on gold mineralization in the Kumasi Basin. In conclusion, our FIS approach to mapping gold prospectivity, which was based entirely on the conceptual reasoning of expert geologists and ignored the spatial distribution of known gold deposits for prospectivity estimation, effectively captured the main mineralized trends. As such, this study also demonstrates the effectiveness of FIS in capturing the linguistic reasoning of expert knowledge by exploration geologists. In spite of using a large number of variables, the curse of dimensionality was precluded because no training data are required for parameter estimation.

This study assesses the hydrothermal nickel prospectivity of Tasmania, Australia, applying a mineral process exploration approach. For this, a joint knowledge-driven and GIS-based prospectivity analysis by a spatial fuzzy model was carried out. These two approaches were combined to reduce bias and lower the risk in the resulting targeting. This identified the most prospective ground for hydrothermal nickel deposits along the boundary between the Dundas and Rocky Cape regions. A hydrothermal Ni conceptual system was designed, and derived from a probabilistic approach, the probability of three essential processes to happen in the same space was evaluated. Results were presented as prospectivity maps. Based on the previous, key questions on the logic of the approach and the link among the essential processes of the system are posed. INTRODUCTION Hydrothermal Ni deposits and occurrences remain poorly studied, and thus very sparse and incomplete information is available. The overall smal...

The West Musgrave Province preserves a geological history spanning much of the Proterozoic, including two major Grenville-aged orogenic events, ca. 1345-1120 Ma. These were followed by the intraplate Giles Event, ca. 1080-1050 Ma, which is characterised by 1- the voluminous mafic intrusions of the Giles Complex and 2-the deposition of a thick sequence of bimodal volcanic rocks and sedimentary rocks (the Bentley Supergroup). The architecture resulting from these events was subsequently overprinted by later events, the ca. 600-520 Ma Petermann Orogeny, and the ca. 450-350 Ma Alice Springs Orogeny. Here we use aeromagnetic, gravity and magnetotelluric data, constrained by geological mapping and petrophysical data, to characterise the 3D architecture of the region, and to unscramble its structural evolution. Early deformation events are well preserved in places, although they do not permit a robust interpretation of the regional architecture at that time. The architecture of the Giles E...

ABSTRACT Zimbabwe is one of the most metallic endowment cratons on earth. This terrane contains large abundances of Au, Ni, Cr and PGE deposits associated with greenstone belts. This study explores possible undercover continuity of Zimbabwe's greenstone belts based on geological, gravity and magnetic public datasets at the country scale. This research especially zooms into the Harare-Shamva region to interpret magnetic and gravity anomalies associate with the Shamva and Harare greenstone belts in the North East of the country. Three data sets were used: (1) public geological maps and reports; (2) aeromagnetic survey project by the Zimbabwean Government (1983-1992) with 250 m to 1,000 m line-spacing and terrain clearance from 120 to 305 metres; and (3) the National gravity dataset of Zimbabwe (1996) with more than 12,000 gravity measurements collected from 1950's to 1995. In order to obtain the complete Bouguer anomaly, we successively performed standard free air, plateau and terrain corrections. Terrain corrections were computed to a distance of 167 km. In order to be close to the expected density of the granites, a Bouguer reduction density of 2.67 g.cm-3 was used. Geometry of the greenstone belts were addressed removing from the signal the long wavelengths of the Bouguer anomaly. This was achieved using a polynomial of degree 3 to the Bouguer anomaly over the entire country and especially into the Harare-Shamva area. The resulting residual Bouguer anomaly represents the effect of density heterogeneities located below the topography, down to ~10 km.