Hyperspectral Remote Sensing and Geological Applications
TL;DR: In this article, the potential of hyperspectral remote sensing (HRS) technique in various geological applications ranging from lithological mapping to exploration of economic minerals of lesser crustal abundance is reviewed.
Abstract: This article reviews the potential of Hyperspectral Remote Sensing (HRS) technique in various geological applications ranging from lithological mapping to exploration of economic minerals of lesser crustal abundance. This work updates understanding on the subject starting from spectroscopy of minerals to its application in exploring mineral deposits and hydrocarbon reservoirs through different procedures such as atmospheric correction, noise reduction, retrieval of pure spectral endmembers and unmixing. Besides linear unmixing, nonlinear unmixing and parameters attributed to nonlinear behaviour of reflected light are also addressed. A few case studies are included to demonstrate the efficacy of this technique in different geological explorations. Finally, recent developments in this field like ultra spectral imaging from unmanned aerial vehicles and its consequences are pointed out.
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TL;DR: Bimal K. Bhattacharya*, Robert O. Green, Sadasiva Rao, M. Saxena, Shweta Sharma, K. Ajay Kumar, P. Srinivasulu, Shashikant Sharma, D. Dhar, S. Bandyopadhyay, Shantanu Bhatwadekar and Raj Kumar Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380 015, India Jet Propulsion Laboratory, California Institute of Technology, CA 91109, USA National Remote Sensing Centre, India Earth Observation Science Directorate,
Abstract: Bimal K. Bhattacharya*, Robert O. Green, Sadasiva Rao, M. Saxena, Shweta Sharma, K. Ajay Kumar, P. Srinivasulu, Shashikant Sharma, D. Dhar, S. Bandyopadhyay, Shantanu Bhatwadekar and Raj Kumar Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380 015, India Jet Propulsion Laboratory, California Institute of Technology, CA 91109, USA National Remote Sensing Centre, Indian Space Research Organisation, Hyderabad 500 625, India Earth Observation Science Directorate, Indian Space Research Organisation, Bengaluru 560 231, India
69 citations
TL;DR: In this paper, the authors review and update various steps of the techniques used in geological information extraction, such as lithological and mineralogical mapping, ore exploration, and environmental geology.
Abstract: Hyperspectral imaging has been used in a variety of geological applications since its advent in the 1970s. In the last few decades, different techniques have been developed by geologists to analyze hyperspectral data in order to quantitatively extract geological information from the high-spectral-resolution remote sensing images. We attempt to review and update various steps of the techniques used in geological information extraction, such as lithological and mineralogical mapping, ore exploration, and environmental geology. The steps include atmospheric correction, dimensionality processing, endmember extraction, and image classification. It is identified that per-pixel and subpixel image classifiers can generate accurate alteration mineral maps. Producing geological maps of different surface materials including minerals and rocks is one of the most important geological applications. The hyperspectral images classification methods demonstrate the potential for being used as a main tool in the mining industry and environmental geology. To exemplify the potential, we also include a few case studies of different geological applications.
62 citations
Cites background or methods from "Hyperspectral Remote Sensing and Ge..."
...Automated morphological endmember extraction, iterative error analysis, and spatial–spectral endmember extraction (SSEE) are statistical unmixing methods that used spatial statistics to improve the endmember selection.(12,63)...
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...There are several endmember extraction algorithms that are broadly grouped into two main classes including convex geometric-based and statistical-based categories.(12) In widely used linear unmixing model, the spectra of each pixel vector are regarded to be a linear combination of endmembers weighted by their corresponding abundances....
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...5-μm visible- and near-infrared (VNIR) and shortwave infrared (SWIR) spectral range are diagnostic in mineralogic and lithological mapping in different climate and tectonic settings.(12) Due to distinct spectral absorption feature, many minerals and rocks are distinguishable through their spectral patterns....
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TL;DR: In this paper, a review of scientific literatures published on mapping of the economic mineral resources of the Sultanate of Oman using ASTER and simples image processing methods is presented.
37 citations
TL;DR: This study was conducted to prove the capability of AVIRIS-NG hyperspectral remote sensing data to identify zones of profitable mineral deposits.
31 citations
Cites background from "Hyperspectral Remote Sensing and Ge..."
...Last three decades of progressive development of hyperspectral remote sensing have provided some spaceborne and airborne hyperspectral sensors such as airborne imaging spectrometer (AIS), advanced visible infrared imaging spectrometer (AVIRIS), Hyperspectral Digital Imagery Collection Experiment (HYDICE), digital airborne imaging spectrometer (DAIS), Hyperspectral Mapper (HYMAP) and Hyperion for lithological discrimination, mineral identification and mapping [2, 4, 5, 6, 7]....
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TL;DR: An overview of hyperspectral imaging, data exploration and analysis, applications in various disciplines, advantages and disadvantages and future aspects of the technique are presented.
Abstract: Recent advances in remote sensing and geographic information has opened new directions for the development of hyperspectral sensors. Hyperspectral remote sensing, also known as imaging spectroscopy is a new technology. Hyperspectral imaging is currently being investigated by researchers and scientists for the detection and identification of vegetation, minerals, different objects and background. Hyperspectral remote sensing combines imaging and spectroscopy in a single system which often includes large data sets and requires new processing methods. Hyperspectral data sets are generally made of about 100 to 200 spectral bands of relatively narrow bandwidths (5-10 nm), whereas, multispectral data sets are usually composed of about 5 to 10 bands of relatively large bandwidths (70-400 nm). Hyperspectral imagery is collected as a data cube with spatial information collected in the X-Y plane, and spectral information represented in the Z-direction. Hyperspectral remote sensing is applicable in many different disciplines. It was originally developed for mining and geology; it has now spread into fields such as agriculture and forestry, ecology, coastal zone management, geology and mineral exploration. This paper presents an overview of hyperspectral imaging, data exploration and analysis, applications in various disciplines, advantages and disadvantages and future aspects of the technique.
24 citations
References
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TL;DR: In this paper, a transformation known as the maximum noise fraction (MNF) transformation is presented, which always produces new components ordered by image quality, and it can be shown that this transformation is equivalent to principal components transformations when the noise variance is the same in all bands and that it reduces to a multiple linear regression when noise is in one band only.
Abstract: A transformation known as the maximum noise fraction (MNF) transformation, which always produces new components ordered by image quality, is presented. It can be shown that this transformation is equivalent to principal components transformations when the noise variance is the same in all bands and that it reduces to a multiple linear regression when noise is in one band only. Noise can be effectively removed from multispectral data by transforming to the MNF space, smoothing or rejecting the most noisy components, and then retransforming to the original space. In this way, more intense smoothing can be applied to the MNF components with high noise and low signal content than could be applied to each band of the original data. The MNF transformation requires knowledge of both the signal and noise covariance matrices. Except when the noise is in one band only, the noise covariance matrix needs to be estimated. One procedure for doing this is discussed and examples of cleaned images are presented. >
2,576 citations
01 Jan 1940
TL;DR: In this paper, it was shown that the observed intensity of the diffuse light may be explained as scattered radiation if the phase function governing the scattering of starlight by the interstellar matter is strongly forward-throwing.
Abstract: Observations have been obtained to verify the existence of diffuse interstellar radiation. A Fabry photometer, attached to the 40-inch refractor at the Yerkes Observatory, was used to measure the the brightness of regions over a wide range of galactic latitude. The intensities in the photographic region of the spectrum were calibrated by means of the Polar Sequence stars. The mean of four such runs across the Milky Way, on circles of constant latitude $\ell = 40^{\rm{o}}$, shows a maximum brightness of 80 stars of the tenth magnitude per square degree for the diffuse extra-terrestrial radiation. The mean of three runs near $\ell = 140^{\rm{o}}$ shows a maximum of 35 in the same units. It is shown that the observed intensity of the diffuse light may be explained as scattered radiation if the phase function governing the scattering of starlight by the interstellar matter is strongly forward-throwing. The concentration of the diffuse light toward the galactic circle is also in agreement with this property of the phase function. The observations also indicate that the scattering efficiency, or albedo, of the particles is greater than 0.3.
2,498 citations
Journal Article•
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TL;DR: The outputs of spectral unmixing, endmember, and abundance estimates are important for identifying the material composition of mixtures and the applicability of models and techniques is highly dependent on the variety of circumstances and factors that give rise to mixed pixels.
Abstract: Spectral unmixing using hyperspectral data represents a significant step in the evolution of remote decompositional analysis that began with multispectral sensing. It is a consequence of collecting data in greater and greater quantities and the desire to extract more detailed information about the material composition of surfaces. Linear mixing is the key assumption that has permitted well-known algorithms to be adapted to the unmixing problem. In fact, the resemblance of the linear mixing model to system models in other areas has permitted a significant legacy of algorithms from a wide range of applications to be adapted to unmixing. However, it is still unclear whether the assumption of linearity is sufficient to model the mixing process in every application of interest. It is clear, however, that the applicability of models and techniques is highly dependent on the variety of circumstances and factors that give rise to mixed pixels. The outputs of spectral unmixing, endmember, and abundance estimates are important for identifying the material composition of mixtures.
1,917 citations
TL;DR: The initial results show that remote, direct identification of surface materials on a picture-element basis can be accomplished by proper sampling of absorption features in the reflectance spectrum.
Abstract: Imaging spectrometry, a new technique for the remote sensing of the earth, is now technically feasible from aircraft and spacecraft. The initial results show that remote, direct identification of surface materials on a picture-element basis can be accomplished by proper sampling of absorption features in the reflectance spectrum. The airborne and spaceborne sensors are capable of acquiring images simultaneously in 100 to 200 contiguous spectral bands. The ability to acquire laboratory-like spectra remotely is a major advance in remote sensing capability. Concomitant advances in computer technology for the reduction and storage of such potentially massive data sets are at hand, and new analytic techniques are being developed to extract the full information content of the data. The emphasis on the deterministic approach to multispectral data analysis as opposed to the statistical approaches used in the past should stimulate the development of new digital image-processing methodologies.
1,750 citations
Book•
01 Jan 1970TL;DR: The second edition of this classic book as discussed by the authors provides an updated look at crystal field theory and its applications and highlights the properties of minerals that make them compounds of interest to solid-state chemists and physicists as well as to all earth and planetary scientists.
Abstract: The second edition of this classic book provides an updated look at crystal field theory - one of the simplest models of chemical bonding - and its applications. Crystal field theory provides a link between the visible region spectra and thermodynamic properties of numerous rock-forming minerals and gems that contain the elements iron, titanium, vanadium, chromium, manganese, cobalt, nickel or copper. These elements are major constituents of terrestrial planets and significantly influence their geochemical and geophysical properties. A unique perspective of the second edition is that it highlights the properties of minerals that make them compounds of interest to solid-state chemists and physicists as well as to all earth and planetary scientists. This book will be useful as a textbook for advanced students as well as a valuable reference work for all research workers interested in this subject.
1,479 citations