Article

Measuring rock microstructure in hyperspectral mineral maps

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Abstract

A novel method is presented to measure rock microstructure in hyperspectral mineral maps of rock specimens. Shape parameters were calculated from rock objects in segmented mineral maps. Object area, object perimeter, object hull perimeter and fitted ellipses were used to calculate shape parameters such as compactness, convexity and a cookie-cutter parameter. Shape parameters were used to describe a variety of microstructures and mi-crostructural elements. The parameters were tested on microstructures in artificial imagery and subsequently applied to hyperspectral mineral maps of rocks. Analyses of parameters calculated on artificial imagery showed that object shapes could be measured by the flattening of fitted ellipses as a measure of sphericity and elongation, together with the cookie-cutter parameters that measured angularity. Compactness and convexity could differentiate between euhedral, subhedral and anhedral crystal shapes. Aphanitic, phaneritic and porphyritic igneous microstructures could be identified and differentiated by homogeneity and relative object size parameters. The degree of sorting of sedimentary rocks was measured by the distribution of object sizes and statistical parameters describing the distribution. Orientation of single objects was measured by the angle between the major axis of a fitted ellipse and the vertical of the image. Preferred orientations in the rock microstructure were determined by calculation of a standardized resultant of orientation vectors and a mean angle. Layering and banding of the rock was identified by the length of major axes of fitted ellipses relative to the image dimension. The shape parameters calculated on objects in segmented hyperspectral mineral maps of rock specimens were able to discriminate between sedimentary and volcanic microstructures using the size distribution of mineral objects, the presence of a preferred orientation of the rock and a layered microstructure. The volcanic micro-structures could be differentiated by the size distribution of amygdales, phenocrysts and xenocrysts in the rock. Shape parameters could be used to differentiate between xenocrysts and phenocrysts, the latter being more elongated in the studied samples. The study shows that object shape parameters can be used to measure microstructure and microstructural elements in mineral maps, and subsequently discriminate between different rock types and microstructures. The expression of microstructure into numeric parameters is a first step towards quantification of microstructures in mineral maps of rocks. Further development of the methodology could contribute to the creation of unbiased classification scheme of rocks, improved statistical modeling of compositional rock parameters such as mineral ore grades, and the automated recognition of microstructures in large image databases of rocks and drill-core.

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A Portable Infrared Mineral Analyzer II (PIMA II) field spectrometer was used to measure infrared reflectance spectra (1·3-2·5 μm) of split drill core at 1 cm intervals in both the along-core and cross-core directions. These data were formatted into an image cube similar to that acquired by an imaging spectrometer with 600 spectral channels, and multi-spectral and hyperspectral analysis techniques were used for analysis. Colour images and enhancements provided visual displays of the spectral information, while real-time digital extraction of individual spectra allowed identification of minerals. Absorption band-depth mapping and spectral classification were used to map the spatial distribution of specific minerals in the core. Linear spectral unmixing provided estimated mineral abundances. Analysis results demonstrate that multi-spectral and hyperspectral image analysis methods can be used to produce detailed mineralogical maps of drill core. They suggest that the concepts and analytical techniques developed for analysis of hyperspectral image data can be applied to field and laboratory spectra in a variety of disciplines, and raise the question of the use of hyperspectral scanners in the laboratory.
Article
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Three flightlines of Airborne Imaging Spectrometer (AIS) data, acquired over the northern Grapevine Mountains, Nevada, and California, were used to map minerals associated with hydrothermally altered rocks. The data were processed to remove vertical striping, normalized using an equal area normalization, and reduced to reflectance relative to an average spectrum derived from the data. An algorithm was developed to automatically calculate the absorption band parameters band position, band depth, and band width for the strongest absorption feature in each pixel. These parameters were mapped into an intensity, hue, saturation (IHS) color system to produce a single color image that summarized the absorption band information, This image was used to map areas of potential alteration based upon the predicted relationships between the color image and mineral absorption band. Individual AIS spectra for these areas were then examined to identify specific minerals. Two types of alteration were mapped with the AIS data. Areas of quartz-sericite-pyrite alteration were identified based upon a strong absorption feature near 2.21 μm, a weak shoulder near 2.25 μm, and a weak absorption band near 2.35 μm caused by sericite (fine-grained muscovite). Areas of argillic alteration were defined based on the presence of montmorillonite, identified by a weak to moderate absorption feature near 2.21 μm and the absence of the 2.35 μm band. Montmorillonite could not be identified in mineral mixtures. Calcite and dolomite were identified based on sharp absorption features near 2.34 and 2.32 μm, respectively. Areas of alteration identified using the AIS data corresponded well with areas mapped using field mapping, field reflectance spectra, and laboratory spectral measurements.
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Remote sensing imagery needs to be converted into tangible information which can be utilised in conjunction with other data sets, often within widely used Geographic Information Systems (GIS). As long as pixel sizes remained typically coarser than, or at the best, similar in size to the objects of interest, emphasis was placed on per-pixel analysis, or even sub-pixel analysis for this conversion, but with increasing spatial resolutions alternative paths have been followed, aimed at deriving objects that are made up of several pixels. This paper gives an overview of the development of object based methods, which aim to delineate readily usable objects from imagery while at the same time combining image processing and GIS functionalities in order to utilize spectral and contextual information in an integrative way. The most common approach used for building objects is image segmentation, which dates back to the 1970s. Around the year 2000 GIS and image processing started to grow together rapidly through object based image analysis (OBIA - or GEOBIA for geospatial object based image analysis). In contrast to typical Landsat resolutions, high resolution images support several scales within their images. Through a comprehensive literature review several thousand abstracts have been screened, and more than 820 OBIA-related articles comprising 145 journal papers, 84 book chapters and nearly 600 conference papers, are analysed in detail. It becomes evident that the first years of the OBIA/GEOBIA developments were characterised by the dominance of 'grey' literature, but that the number of peer-reviewed journal articles has increased sharply over the last four to five years. The pixel paradigm is beginning to show cracks and the OBIA methods are making considerable progress towards a spatially explicit information extraction workflow, such as is required for spatial planning as well as for many monitoring programmes.
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Understanding the physical relationships of minerals and rocks is essential to interpreting detailed chemical and isotopic mineral analyses. Covering the basic processes behind various rock microstructures, Ron Vernon uses high-quality color illustrations to point out complications of interpretation, emphasize pitfalls, and disclose the latest techniques and approaches. He includes a comprehensive reference list that will be useful for advanced students wishing to delve more deeply.
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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.
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X-ray diffraction studies of clay minerals from disseminated gold deposits in Nevada demonstrate that illite polytypes are often laterally and vertically zoned around ore bodies. Polytypes act as geothermometers indicating temperatures of ore deposition and thus proximity to the hydrothermal fluids during deposition. Visible/infrared reflectance spectroscopy for field identification and mapping of the illite polytypes is evaluated. The results demonstrate that reflectance spectroscopy can be used to assist gold exploration efforts by providing detailed mineralogical information in real time at the field location. As the new generation of imaging spectrometers is developed, it is likely that subtle spectral differences such as those between the illite polytypes will become useful for remote exploration for gold deposits
Chapter
Summary This document is part of Subvolume A of Volume 1 ‘Physical Properties of Rocks’ of Landolt-Börnstein - Group V Geophysics.
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A recent study by Dalm et al. (2014) showed that alteration mineralogy acquired using SWIR point spectrometry could be linked to copper grade distribution for a group of samples from a South American copper mine. Since it was expected that SWIR hyperspectral imagery can provide more detailed information about the alteration mineralogy of these ores, we investigated whether this technique can be used to improve upon the indirect characterization of copper grades. Maps showing the distributions of SWIR-active minerals, white mica crystallinity, white mica composition, and chlorite composition were produced from SWIR hyperspectral images of 43 samples from the Dalm et al. (2014) study. Subsequently, a principle component analysis (PCA) was applied to the relative mineral abundances and the average white mica crystallinity and composition that were extracted from these maps. The PCA showed that this mineralogical data could be used to discriminate a significant portion of the samples with sub-economic copper grades. Furthermore, the study showed that SWIR hyperspectral imaging has the following advantages over SWIR point spectrometry: minerals that are present in relatively low quantities can be detected, the SWIR-active mineralogical composition at the surface of a sample can be quantified, and the texture of samples, such as grain sizes and cross-cutting vein structures, can be characterized. However, these advantages did not improve upon the indirect characterization of copper grades that was achieved using SWIR point spectrometry. This was attributed to the relatively small size of the sample set and the high textural variability between samples.
Article
A new reference library of thermal infrared spectral reflectance measurements of the major rock-forming and alteration minerals has been compiled to support and enhance analysis of data acquired using the CSIRO HyLogger-3 drill-core logging system. The HyLogger-3 is a robotic system that acquires large volumes of bidirectional reflectance spectra from diamond drill core within the wavelength range of visible light, the near infrared and shortwave infrared (400–2500 nm) as well as the thermal infrared from 6000 to 14 000 nm. The library samples were selected as single pure solid mineral crystals or monomineralic hand samples judged to have a similar bidirectional spectral response to that of typical diamond drill cores. Furthermore, a large number of individual mineral samples were chosen to cover the various natural spectral variations within single mineral groups such as, for example, a range of solid solutions of plagioclase. Owing to the bidirectional measurement geometry of the HyLogger-3, spectral variations caused by crystal orientation effects are also expected. Accordingly, reflectance measurements were made for multiple surfaces/facets of each sample, and also for orthogonal orientations of the plane of incidence illumination for each facet measured. All measured spectra were compared with existing library spectra or with spectra measured from validated samples to judge whether the mineral samples could be regarded as pure and, where possible, their chemical composition and mineralogy were validated by X-ray fluorescence and X-ray diffraction. For quality control, all such relevant metadata, including macroscopic descriptions of each sample, were collated in an associated database. In total, the spectral library contains more than 2000 spectra, from 562 specimens, representing 130 mineral groups. This library focuses on the most common rock-forming minerals of relevance to metalliferous exploration and mining, with a few limitations resulting from availability of suitable samples, which will be addressed as new samples become available. Comparisons with emission spectra from existing spectral libraries show good agreement, indicating that this spectral library will also be useful in the remote sensing domain.
Article
Australian Geological Surveys are the custodians of a major national asset in the form of historically drilled and archived drill cores of the top few kilometres of the continent acquired by government agencies and companies over many decades. The AuScope National Virtual Core Library (NVCL) component of the AuScope Earth Model comprises geological/rock samples, technology, people and database/delivery infrastructure located in six nationally distributed nodes and is aimed at extracting additional value from this asset. The technology components of the NVCL comprise an integrated suite of hardware (HyLogger-3) and software (TSG-Core) systems for the imaging and hyperspectral characterisation of drill cores in their original core trays and the interpretation of their contained oxide, carbonate, hydrous and anhydrous silicate mineralogy. The HyLogger-3 includes state-of-the-art Fourier Transform Spectrometers that continuously measure calibrated spectral reflectance from nominal 10 by 18 mm fields of view. These spectra are in turn passed through a series of automatic and semi-automatic pre-processing and mineralogical unmixing algorithms. These, along with numerous other tools in TSG-Core, output a variety of mineralogical and image products for use by scientists in many branches of the earth sciences. This paper provides a functional overview of the HyLogging hardware and software tools available in each of Australia's Geological Surveys.
Article
In mineral exploration, the search of geophysical, geochemical, and mineralogical pathfinders is of critical importance and many techniques have been used to detect the presence of mineralization and related host-rock alterations. In the case of unconformity-type uranium deposits that are spatially linked to unconformities between sedimentary basin and underlying basement rocks, hydrothermal fluid-rock interactions produced extended alteration envelopes which are used to target mineralization and are therefore important guides for uranium exploration.
Book
Understanding ore textures is fundamental to unraveling the genesis of an ore deposit, which in turn allows exploration and mining geologists to build their conceptual models of the deposits they encounter and leads to more successful exploration and exploitation. This book is specifically designed for the field geologist working without the benefits of sophisticated chemical, mineralogical or petrological support. It covers the basic building blocks of textural recognition beginning with infill (direct precipitation from hydrothermal fluids into 'cavities'), alteration (the results of hydrothermal fluid reactions with wall rocks) and overprinting (the normal complexity caused by successive introduction of hydrothermal fluids usually accompanied or preceded by renewed fracturing) and ends with a detailed examination of textures associated with tectonic and intrusive breccias. © Springer-Verlag Berlin Heidelberg 2009. All rights are reserved.
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This is the third volume in the series, following Atlas of rock-forming Minerals in Thin Section (M.A. 80-2791) and Atlas of Igneous Rocks and their Textures (M.A. 83M/1089). It presents over 200 colour photographs of terrigenous clastic rocks, carbonate rocks and other sedimentary rocks (including ironstones, cherts, evaporites, phosphatic sediments and coal). There are appendices on preparing a thin section, staining a thin section of a limestone and preparing a stained acetate peel of a limestone. Although most of the photographs of limestones are from stained thin sections or peels, photographs of unstained limestone sections are also included.-R.A.H.
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The minerals covered in this chapter include only those micas believed to have crystallized from a melt. These include the trioctahedral mica, biotite, and the dioctahedral mica, muscovite. Igneous muscovite is restricted in occurrence to peraluminous plutonic granitoids and, more rarely, extrusive rhyolites. Biotite can occur over nearly the entire spectrum of igneous rocks, from peridotites to granitoids to peralkaline rocks. This chapter is confined to studies of naturally occurring micas, often in conjunction with experimental phase equilibria, which have contributed to an understanding about igneous rocks; their origin, emplacement, crystallization history and conditions, timing, subsolidus events, etc.
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A new method is presented for the exploratory analysis of hyperspectral OMEGA imagery of Mars. It involves mapping the wavelength position and depth of the deepest absorption feature in the range between 2.1 and 2.4 µm, where reflectance spectra of minerals such as phyllosilicates, carbonates and sulphates contain diagnostic absorption features. For each pixel of the image, the wavelength position maps display the wavelength position of the deepest absorption feature in color and its depth in intensity. This can be correlated with (groups of) minerals and their occurrences.
Article
Calcic amphiboles in form of single crystals and in rock samples have been measured using laboratory-based infrared reflectance spectroscopy (IRS) and routine IRS technologies applied in mineral exploration. The composition of amphiboles in selected rock samples was validated with scanning electron microscopy (SEM) and electron microprobe work. Published values for wavenumber frequencies of hydroxyl-related stretching and bending vibrations were compared with the results from our study and both were combined to calculate combinations and overtones of [M1M1M3]-O-H in the short-wave infrared regions of 5000–4080 cm�1 (2000–2450 nm) and 7350 cm�1 (1360 nm) regions, respectively. Detailed comparison of major short-wave infrared absorption features in various calcic amphiboles and talc leads to the conclusion that an absorption feature centred at 2080 nm is diagnostic for talc and can be used to distinguish amphibole from talc. Multiple feature extraction scripts were developed to determine the relative abundance of amphibole and talc, as well as the Mg# of amphiboles in large IRS data sets. Our results show that only the 2390 nm absorption feature in amphibole can be reliably used to determine its abundance and Mg# in mineral assemblages containing other short-wave infrared active minerals. Different mafic and ultramafic lithologies can be inferred from infrared hyperspectral drill core logging and remote sensing datasets, based on the developed scripts.
Article
Close-range hyperspectral imaging is a new method for geological research, in which imaging spectrometry is applied from the ground, allowing the mineralogy and lithology in near-vertical cliff sections to be studied in detail. Contemporary outcrop studies often make use of photorealistic three-dimensional 3D models, derived from terrestrial laser scanning lidar, that facilitate geological interpretation of geometric features. Hyperspectral imaging provides complementary geochemical information that can be combined with lidar models, enhancing quantitative and qualitative analyses. This article describes a complete workflow for applying close-range hyperspectral imaging, from planning the optimal scan conditions and data acquisition, through pre-processing the hyperspectral imagery and spectral mapping, integration with lidar photorealistic 3D models, and analysis of the geological results. Pre-processing of the hyperspectral images involves the reduction of scanner artefacts and image discontinuities, as well as relative reflectance calibration using empirical line correction, based on two calibrated reflection targets. Signal-to-noise ratios better than 70:1 are achieved for materials with 50% reflectance. The lidar-based models are textured with products such as hyperspectral classification maps. Examples from carbonate and siliciclastic geological environments are presented, with results showing that spectrally similar material, such as different dolomite types or sandstone and siltstone, can be distinguished and spectrally mapped. This workflow offers a novel and flexible technique for applications, in which a close-range instrument setup is required and the spatial distribution of minerals or chemical variations is valuable.
Article
Shape is an important aspect of the spatial attributes of land-use segments in remotely sensed imagery, but it is still rarely used as a component in land-use classification or image-based land-use analysis. This study aimed to quantitatively characterize land-use classes using shape metrics. The study was conducted in a case area located in southern China, covering 12 scenes of SPOT-5 images. There were a total of 10 metrics selected for the analysis: convexity (CONV), solidity (SOLI), elongation (ELONG), roundness (ROUND), rectangular fitting (RECT), compactness (COMP), form factor (FORM), square pixel metric (SqP), fractal dimension (FD), and shape index (SI). The last five metrics were used to measure the complexity of shape. Six land-use classes were investigated in the case area: roads; cultivated lands; settlements; rivers; ponds; and forest and grass lands. The results showed that all the typical shape properties of the land-use segments can be well measured by shape metrics. We identified the land-use classes whose values were significantly differentiated from the other classes for each metric. Finally, we selected five shape metrics (SOLI, ELONG, ROUND, RECT, FORM) by visual comparison and statistical analysis of the metrics values, and deduced the “shape metric signatures” (SMS) of the different land-use classes. SMS were found to be accurate and predictive discriminators of land-use classes within the study area. Our results showed that SMS can clearly distinguish spectrally similar land-use classes. The results of this study will help to build a more accurate and intelligent object-oriented classification system for land-use classes.
Article
Remote sensing is the science of acquiring, processing, and interpreting images and related data, acquired from aircraft and satellites, that record the interaction between matter and electromagnetic energy. Remote sensing images are used for mineral exploration in two applications: (1) map geology and the faults and fractures that localize ore deposits; (2) recognize hydrothermally altered rocks by their spectral signatures. Landsat thematic mapper (TM) satellite images are widely used to interpret both structure and hydrothermal alteration. Digitally processed TM ratio images can identify two assemblages of hydrothermal alteration minerals; iron minerals, and clays plus alunite. In northern Chile, TM ratio images defined the prospects that are now major copper deposits at Collahuasi and Ujina. Hyperspectral imaging systems can identify individual species of iron and clay minerals, which can provide details of hydrothermal zoning. Silicification, which is an important indicator of hydrothermal alteration, is not recognizable on TM and hyperspectral images. Quartz has no diagnostic spectral features in the visible and reflected IR wavelengths recorded by these systems. Variations in silica content are recognizable in multispectral thermal IR images, which is a promising topic for research.
Article
A new method for the detection of pre-defined boundaries in single-band image data that uses a rotation-variant template matching (RTM) algorithm is presented. This algorithm matches a miniature image of a pre-defined boundary to image data at various orientations. The image pixels that match boundary criteria are reported in output imagery together with the rotation angle of the template. The method is applied to identify boundaries between hydrothermal alteration zones in processed airborne hyperspectral imagery, based on the presence of white mica minerals. Results Show that boundaries identified with RTM are relatively free of noise and more coherent than those identified with, for instance, image slicing techniques. Identified boundaries can be used for image segmentation. The output of the RTM algorithm also provides information on the type of boundary, whether it is crisp or gradual. This information can be used to better characterize mineral variation in the alteration halo associated with fossil hydrothermal systems. (c) 2008 Elsevier Ltd. All rights reserved.
Article
The utility of multispectral remote sensing techniques for discriminating among materials is based on the differences that exist among their spectral properties. As distinct from spectral variations that occur as a consequence of target condition and environmental factors, intrinsic spectral features that appear in the form of bands and slopes in the visible and near infrared (. 325 to 2. 5 mu m) bidirectional reflection spectra of minerals (and, consequently, rocks) are caused by a variety of electronic and vibrational processes. These processes, such as crystal field effects, charge-transfer, color centers, transitions to the conduction band, and overtone and combination tone vibrational transitions are discussed and illustrated with reference to specific minerals. Spectral data collected from a large selection of minerals are used to generate a ″spectral signature″ diagram that summarizes the optimum intrinsic information available from the spectra of particulate minerals. The diagram provides a ready reference for the interpretation of visible and near infrared features that typically appear in remotely sensed data. In the visible-near infrared region, the most commonly observed features in naturally occurring materials are due to the presence of iron in some form or other, or to the presence of water or OH groups.
Article
Empirical relationships and a field method have been developed for the measurement of the hematite:goethite ratio in Tertiary ooidal ironstones, locally named channel iron deposits, from the Hamersley region of Western Australia using visible to near‐infrared (400 to 1000 nm) refiectance spectrometry. The hematite:goethite ratio is important in the characterisation of these iron deposits as Al, P, water and Si are deleterious components commonly associated with goethite. The channel iron deposits typically comprise iron oxy‐hydroxides with less than 1% Fe (present in maghemite or kenomagnetite), less than 8% Al‐substitution and with a mean crystal dimension of approximately 20 nm. The natural variations in the hematite:goethite ratio of the channel iron deposits were modelled using laboratory mixtures of pure hematite and goethite. The resultant spectral mixing trends produced consistent relationships with the hematite:goethite ratio, especially for the wavelength of the 6A1?4T1 crystal field absorption minimum. Variation in Al‐substitution and crystal size had no apparent effect on the wavelength of this feature though a change in grainsize from > 75 to < 20 μm caused an apparent 30 nm wavelength shift. However, only a 5 nm shift was apparent in spectra taken from unprepared drillchip samples probably because the finer fraction coats larger fragments. The field spectral method was found to be as accurate for measuring the hematite:goethite ratio compared with the laboratory‐based loss on ignition, XRD peaks and thermodifferential analysis techniques. Although geological samples pulverised to < 75 μm yielded the most accurate results, it was found that an additional error of only ± 5 nm was produced using unprepared drillchip samples.
Book
This reference to the basic vocabulary of geology and geophysics has more than 3,000 clear and concise entries defining the entire range of geological phenomena. This book covers such areas as types of rocks and rock formations, deformation processes such as erosion and plate tectonics, volcanoes, glaciers and their effects on topography, geodesy and survey methods, earthquakes and seismology, fuels and mineral deposits.
Book
The author's introduction to remote sensing provides coverage of the subject irrespective of disciplines of study or the academic department in which remote sensing is taught. All the ''classical'' elements of aerial photographic interpretation and photogrammetry are described, but equal emphasis is placed on non-photographic sensing systems and the analysis of data from these systems using digital image processing procedures. This text includes coverage of image restoration, enhancement, classification, and data merging, and new sensor systems such as the Large Format Camera, solid-state linear arrays, the Shuttle Imaging radar systems, the Landsat Thematic Mapper, the SPOT satellite system, and the NOAA Advanced Very High Resolution Radiometer. Also covers imaging spectrometry and lidar systems. It contains extensive illustrations.
Article
Miocene fluvial goethite/hematite channel iron deposits (CID) are part of the Cenozoic Detritals 2 (CzD2), of the Western Australian Pilbara region. They range from gravelly mudstones through granular rocks to intraformational pebble, cobble and rare boulder conglomerates, as infill in numerous meandering palaeochannels in a mature surface that includes Precambrian granitoids, volcanics, metasediments, BIF and ferruginous Palaeogene valley fill. In the Hamersley Province of the Pilbara, the consolidated fine gravels and subordinate interbedded conglomerates, with their leached equivalents, are a major source of export iron ore. This granular ore typically comprises pedogenically derived pelletoids comprising hematite nuclei and goethite cortices (ooids and lesser pisoids), with abundant coarser goethitised wood/charcoal fragments and goethitic peloids, minor clay, and generally minimal porous goethitic matrix, with late-stage episodic solution and partial infill by secondary goethite, silica and siderite (now oxidised) in places. Clay horizons and non-ore polymictic basal and marginal conglomerates are also present. The accretionary pedogenic pelletoids were mostly derived from stripping of a mature ferruginous but apparently well-vegetated surface, developed in the Early to Middle Miocene on a wide variety of susceptible rock types including BIF, basic intrusives and sediments. This deep ferruginisation effectively destroyed most remnants of the original rock textures producing a unique surface, very different to those that produced the underlying CzD1 (Palaeogene) and the overlying CzD3 (Pliocene – Quaternary). The peloids were derived both intraformationally from fragmentation and reworking of desiccated goethite-rich muds, and from the regolith. Tiny wood/charcoal fragments replaced in soil by goethite, and dehydrated to hematite, formed nuclei for many pelletoids. Additionally, abundant small (≤10 mm) fragments of wood/charcoal, now goethite, were probably replaced in situ within the consolidating CID. This profusion of fossil wood, both as pelletoid nuclei and as discrete fragments, suggests major episodic wild fires in heavily vegetated catchments, a point supported by the abundance of kenomagnetite – maghemite developed from goethite in the pelletoids, but less commonly in the peloids. The matrix to the heterogeneous colluvial and intraformational components is essentially goethite, primarily derived from modified chemically precipitated iron hydroxyoxides, resulting from leaching of iron-rich soils in an organic environment, together with goethitic soil-derived alluvial material. Major variations in the granular ore CID after deposition have resulted from intermittent groundwater flow in the channels causing dissolution and reprecipitation of goethite and silica, particularly in the basal CID zones, with surface weathering of eroded exposures playing a role in masking some of these effects. However, significant variations in rock types in both the general CID and the granular ore CID have also resulted from the effects of varied provenance.
Article
A review of progress made in the new field of imaging spectroscopy is presented based on the nine papers making up the special issue of this journal. Background material on the motivation for the new approach to earth remote sensing is discussed. The history, design, and performance of the pioneering sensor for terrestrial high resolution remote sensing, the Airborne Imaging Spectrometer (AIS), are presented. Concluding this paper is a discussion of plans for the future of imaging spectroscopy of the earth.
Article
The Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, has developed a prototype interactive software system called the ‘‘Spectral Image Processing System (SIPS)’’ using ‘‘IDL’’ (the Interactive Data Language) on UNIX‐based workstations. SIPS is designed to take advantage of the combination of high spectral resolution and spatial data presentation unique to imaging spectrometers. It streamlines analysis of these data by allowing scientists to interact with entire datasets in real‐time. SIPS provides visualization tools for rapid exploratory analysis and numerical tools for quantitative modeling. The user interface is X‐windows‐based, user friendly, and provides ‘‘point and click’’ operation. SIPS is being used for multidisciplinary research concentrating on the use of physically‐based analysis methods to enhance scientific results from imging spectrometer data. The objective of this continuing effort is to develop operational techniques for quantitative analysis of imaging spectrometer data and to make them available to the scientific community prior to the launch of imaging spectrometer satellite systems such as the Earth Observing System (EOS) High Resolution Imaging Spectrometer (HIRIS).
Article
A common challenge in remote sensing is the classification of objects that are spectrally similar but represent physically different types of ground cover. In this paper, we describe and apply three complementary shape measures to classify morphologically different waterbodies in a Landsat image. Image segmentation was used to create objects of image pixels containing water, and shape measures were calculated for all obtained objects. A shape-based, a spectra-based and a combined spatial-spectral classification were carried out on a subset of the image using endmembers acquired outside the subset. The spectral classification was based on Euclidean distance. The shape-based and combined spectral-shape classification were based on vector angle, as the chosen shape measures are influenced by the image lattice and could only be used as a relative measure. The results of this approach are discussed and compared to an expert interpretation of the same dataset. Results show that shape measures are affected by image resolution and should be used as a relative measure when objects consist of 500 pixels or less. Although the combined spectral-shape classification was not satisfactory and needs more research, the classification that is solely based on shape measures can distinguish spectrally identical waterbodies and had a score of 94% compared to the expert classification.
Texture analysis for Mars rover images
  • R Castano
  • T Mann
  • E Mjolsness
Castano, R., Mann, T., Mjolsness, E., 1999. Texture analysis for Mars rover images. In: Applications of Digital Image Processing XXII, vol. 3808. pp. 162-173.
Rapid classification of infra-red hyperspectral imagery of rocks with decision trees and wavelength images
  • F J A Van Ruitenbeek
  • H M A Van Der Werff
  • W H Bakker
  • F D Van Der Meer
  • C H Hecker
  • K A A Hein
Van Ruitenbeek, F.J.A., Van der Werff, H.M.A., Bakker, W.H., Van der Meer, F.D., Hecker, C.H., Hein, K.A.A., 2017. Rapid classification of infra-red hyperspectral imagery of rocks with decision trees and wavelength images. http://www.itc.nl/library/papers_ 2017/pres/vanruitenbeek_rap_ppt.pdf, Accessed date: 29 August 2018.
Metamorphism and metamorphic rocks
  • S A Nelson
Nelson, S.A., 2017. Metamorphism and metamorphic rocks. https://www.tulane.edu/ sanelson/eens1110/metamorphic.htm, Accessed date: 29 August 2018.