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Natural samples of the rare earth element (REE)-bearing silicate minerals cerite, mosandrite, kainosite, zircon, and eudialyte were studied using reflectance spectroscopy in the visible to short-wave infrared regions (500 to 2500 nm) and further characterized by scanning electron microscopy and electron microprobe analysis. Spectral features of these minerals are driven primarily by 4f-4f intraconfigurational electronic transitions of trivalent lanthanides, as well as 5f-5f electronic transitions of uranium and vibrational overtones and combinations of H2O and OH–. Spectra of eudialyte are also impacted by relative amounts of IVFe2+ and VFe2+. Respective spectra of these REE-bearing silicate minerals are sufficiently distinct to enable spectral classification. Spectral variability (e.g., band depths and locations) of some specific REE-related absorptions, such as an Er3+- and Yb3+-related absorption near 978 nm and Nd3+-related absorptions near 746, 803, and 875 nm, are interpreted to be driven by cation site differences in the crystal structures. This work adds to the growing understanding of REE-bearing mineral reflectance spectroscopy, which facilitates detection, identification, and quantification of REE-bearing silicate minerals in remote sensing applications. This is especially relevant for hyperspectral imaging spectroscopy with high spatial resolutions where the spectral response of a pixel becomes increasingly dominated by mineralogy rather than lithology. [ABSTRACT FROM AUTHOR]

Reflectance spectroscopy in the visible to short-wave infrared regions (500 to 2500 nm) was carried out using natural samples of the rare earth element (REE) phosphate minerals monazite, xenotime, and britholite. Samples were characterized by scanning electron microscopy and electron microprobe analysis. Absorption band positions were recorded with their probable origins, and spectral variability among the samples is discussed. Spectral features of these minerals are driven primarily by 4f-4f intraconfigurational electronic transitions of trivalent lanthanides. The distinct REE distributions of monazite, xenotime, and britholite drive their bulk spectral patterns, which in turn are sufficiently distinct to enable spectral classification. Spectral variability of some specific REE-related absorptions are interpreted to be driven by differences of the coordination polyhedra for the lanthanide cations between the crystal structures. Spectra of these minerals were also compared against carbonatitehosted REE bearing fluorapatite. The work presented here strengthens the growing foundation for the interpretation of reflectance spectra of these REE phosphate minerals and enables exploitation of the observed features by the remote sensing community for detection, identification, and quantification of REE phosphate minerals. This is especially relevant for hyperspectral imaging spectroscopy with high spatial resolution, where the spectral response of a pixel becomes increasingly dominated by mineralogy. [ABSTRACT FROM AUTHOR]

An understanding of the mineralogy and petrogenesis of rare earth element deposits has significant implications for their economic viability. Lanthanide-bearing compounds are known to produce sharp absorption features in the visible to short-wave infrared region (VIS-SWIR), however, a significant knowledge gap exists between the fields of hyperspectral reflectance spectroscopy and rare earth element mineralogy. Reflectance spectra were collected from four bastnäsite samples, two parisite samples, and one synchysite sample from the visible into the short-wave infrared. These REE fluorocarbonate mineral samples were characterized via scanning electron microscopy and electron probe microanalysis. Sharp absorptions of REE-bearing minerals are mostly the result of 4f-4f intraconfigurational electron transitions and for the light REE-enriched fluorocarbonates, the bulk of the features can be ascribed to Nd3+, Pr3+, Sm3+, and Eu3+. The lanthanide-related spectral responses of the REE fluorocarbonates are consistent across the group, supporting the notion that the REE cation site is very similar in each of these minerals. Carbonate-related spectral responses differed between these minerals, supporting the notion that the crystallographic sites for the carbonate radical differ between bastnäsite, synchysite, and parisite. Exploitable spectral differences include a distinct absorption band at 2243 nm that separates bastnäsite from synchysite and parisite. Similarly, for bastnäsite a dominantly Pr3+-related absorption band located is at 1968 nm, while in synchysite and parisite it occurs at 1961 nm. [ABSTRACT FROM AUTHOR]

Abstract: Hyperspectral remote sensing provides great potential to monitor and study biodiversity of tropical forests through species identification and mapping. In this study, five species were selected to examine crown-level spectral variation within and between species using HYperspectral Digital Collection Experiment (HYDICE) data collected over La Selva, Costa Rica. Spectral angle was used to evaluate the spectral variation in reflectance, first derivative and wavelet-transformed spectral domains. Results indicated that intra-crown spectral variation does not always follow a normal distribution and can vary from crown to crown, therefore presenting challenges to statistically define the spectral variation within species using conventional classification approaches that assume normal distributions. Although derivative analysis has been used extensively in hyperspectral remote sensing of vegetation, our results suggest that it might not be optimal for species identification in tropical forestry using airborne hyperspectral data. The wavelet-transformed spectra, however, were useful for the identification of tree species. The wavelet coefficients at coarse spectral scales and the wavelet energy feature are more capable of reducing variation within crowns/species and capturing spectral differences between species. The implications of this examination of intra- and inter-specific variability at crown-level were: (1) the wavelet transform is a robust tool for the identification of tree species using hyperspectral data because it can provide a systematic view of the spectra at multiple scales; and (2) it may be impractical to identify every species using only hyperspectral data, given that spectral similarity may exist between species and that within-crown/species variability may be influenced by many factors. [Copyright &y& Elsevier]

Abstract: After leaves are clipped their reflectance properties change over time at variable rates. Spectral change can in part be attributed to the changing water content of the leaf, which affects absorption in the VIS, NIR and the SWIR. Maintaining water volume within samples has been the motivation behind many leaf handling techniques. This study has assessed the time constraints between leaf collection and spectral measurement. Specifically the relationship between leaf water content and foliar spectra (350–2500 nm) was examined over time for five tropical trees (common guava (Psidium guajava), purple guava (Psidium littorale), weeping fig (Ficus benjamina), floss silk (Chorisia speciosa), and coffee (Coffea arabica)). This investigation was carried for leaves wrapped with moist gauze around their petiole (treatment leaves) and leaves with no treatment. Spectral measurements and mass measurements were repeated for each leaf once every hour for the first 12 h, then every 4–6 h for 18 h, followed by one measurement after 12 h, and finally once a day until the control samples became air-dry. Foliar reflectance in the visible spectrum was not immediately responsive to water content changes and did not change until wilting of the leaf was observed. The NIR and SWIR wavelength regions were affected immediately by small changes in water content. Thus, by the time wilting was first observed the NIR and SWIR foliar reflectance differed considerably from corresponding fresh leaf reflectance. No common time limit could be observed for leaf clipping and reflectance measurement. Leaves have a variety of water contents and dehydration rates hence measurement time constraints are dependent on the properties of the leaf or species. Rather than using a time limit it is recommended that leaf handling techniques be based upon managing leaf water content and leaf structure. The results of this study indicate that leaves with petioles wrapped in moist paper towel and placed within plastic bags will maintain leaf reflectance longer than equivalent leaves without treatment; samples tested here lasted a minimum of 7 days. θ and D indices (“angle difference” and “root mean square difference”, respectively) revealed a stronger relationship between leaf water content and spectral shape than between leaf water and raw reflectance magnitude. The ratio of 1187/1096 nm, when compared with θ and D indices and individual reflectance bands, showed the highest coefficient of determination with leaf water content (r 2 =0.952). [Copyright &y& Elsevier]

Compact Airborne Spectrographic Imager (CASI) hyperspectral data is used to investigate the effects of topography on the selection of spectral end members, and to assess whether the topographic correction improves the discrimination of rock units for lithologic mapping. A publicly available Digital Elevation Model (DEM), at a scale of 1:50,000, is used to model the radiance variation of the scene as a function of topography, assuming a Lambertian surface. Skylight is estimated and removed from the airborne data using a dark object correction. The CASI data is corrected on a pixel-by-pixel basis to normalize the scene to a uniform solar illumination and viewing geometry. The results show that topography has the effect of expanding end member clusters at times resulting in the overlap of clusters and that the correction process can effectively reduce the variation in detected radiance due to changes in local illumination. When topographic effects are embedded in the hyperspectral data, methods typically used for the selection of end members, such as the convex hull method, can miss end members or result in the selection of nonrepresentative pixels as end members. Thus, end members selected by some conventional methods are very likely “incomplete” or “nonrepresentative” if the topographic effect is embedded in the data. As shown in this study, the topographic correction can reveal hidden end members and achieve a better representation of end members via the statistical center of isolated clusters. [Copyright &y& Elsevier]

This study is the first of two companion papers using hyperspectral data to generate predictive models of oil sand ore and froth characteristics as a potential new means for process control. In Alberta, Canada, shallow oil sands deposits are accessed by surface mining and crushed ore is transported to a processing plant for extraction of bitumen using flotation processes. The ore displays considerable variability in clay, bitumen, and fines which affects their behavior in flotation units. Using oil sand ore spanning a range of bitumen and fines characteristics, flotation experiments were performed to generate froth in a batch extractor to determine ore processability (e.g., separation performance) and froth characteristics (color, bitumen, solids). From hyperspectral observations of ore, models can predict the %bitumen content and %fines (particle passing at 44 and 3.9 µm) of ore but the models with highest r2 (>0.96) predict the solids/bitumen of froth and the processability of ore. Spectral observations collected on ore upstream of the separation vessels could therefore offer a first order assessment of froth quality for an ore blend before the ore enters the plant. These models could also potentially be used to monitor and control the performance of the blending process as another means to control the performance of the flotation process. [ABSTRACT FROM AUTHOR]

This is the second part of a study of predictive models of oil sand ore and froth characteristics using infrared hyperspectral data as a potential new means for process control. In Alberta, Canada, bitumen in shallow oil sands deposits is accessed by surface mining and then extracted from ore using flotation processes. The ore displays variability in the clay, bitumen, and fines content and this variability affects the separability and product quality in flotation units. Flotation experiments were performed on a set of ore samples of different types to generate froth and determine the ore processability (e.g., separation performance) and froth characteristics (bitumen and solids content, fines distribution). We show that point spectra and spectral imagery of good quality can be acquired rapidly (<1 s and <15 s, respectively) and these capture spectral features diagnostic of bitumen and solids. Ensuing models can predict the solids/bitumen (r2 = 0.88) and the %fines and ultrafines (particle passing at 3.9 and 0.5 µm) content of froth (r2 = 0.8 and 0.9, respectively). The latter model could be used to reject froth with a high solids content. Alternately, the strength of the illite-smectite absorption observed in froth could be used to retain all the samples above a pre-defined processability. Given that point spectrometers can currently be acquired for less than half the cost of an imaging system, we recommend the use of the former for future trials in operating environments. [ABSTRACT FROM AUTHOR]

Highlights • Longwave IR spectra were collected from twelve REE-bearing samples. • Stretching and bending modes of the X-O (X = C, Si, P) groups are observed. • No specific features were found for the direct detection of the REEs. Abstract Rare earth elements (REEs) are a group of metals essential to high technology industries. This high demand, combined with a high supply risk, has led to an understanding that REEs are critical to society. Despite the potential that hyperspectral imaging (HSI) data offers for a fast and non-invasive characterization of the REEs, it is still poorly understood whether REEs have some information in the long-wave infrared (LWIR; 8–12 μm) wavelength range that can be used for their identification. To partially fill this gap, we have investigated the spectroscopy of twelve REE-bearing mineral samples using relatively high spatial and spectral resolution LWIR hyperspectral imaging data. These samples were formerly characterized using electron probe microanalysis (EPMA), scanning electron microscopy (SEM), and hyperspectral imaging data acquired in the 0.4–2.5 μm wavelength range. Results from these analyses were compared to and used to guide the analysis of the HSI data recorded in the LWIR range. This information was further compared to a reference spectral library of rare earth oxides. Our findings suggest that the spectral features of the samples can generally be traced to the asymmetric degenerate stretching and bending modes of the X-O (X = C, Si, P) groups. Moreover and contrary to what has been observed in the shorter wavelengths, there are no definitive spectral features in the LWIR wavelength region that could be assigned to any specific REE. [ABSTRACT FROM AUTHOR]

The early identification of natural oil seepages or accidental leaks onshore is not a well explored theme in the literature. Location and mapping of contaminated areas can indicate the presence of a subsurface reservoir and guide direct exploration operations in the oil industry. Superficial occurrences of hydrocarbons (HCs) can also indicate damage to pipelines. Locating small leaks can guide containment, cleaning and repair operations. Remote sensing tools for such purposes usually focus on the effects that oil in the soil causes on the spectral signatures of vegetation. Studies investigating the spectral characteristics of soil and HC mixtures are not prevalent. This study comprises the conception and analysis of a spectral library of mixtures of several mineral substrates impregnated with various concentrations of light to heavy oils (API varying from 19.4 to 41.9), using data acquired with an automated hyperspectral imaging station and processed with wavelets. The wavelet transform allowed the extraction of key spectral features and the discard of secondary information (e.g. noise and continuum), resulting in hyperspectral imagery products that proved suitable to separate different phases in the soil-HC mixture, as well as to identify the type and concentration of HC in the soil. This comprehensive spectral library and the acquired information regarding spectral characteristics of soil-hydrocarbon mixtures, opens opportunities for the development of new processing methods for the direct mapping of onshore seeps and leaks using current and future orbital hyperspectral (Hyperion; EnMap; HyspIRI) and multispectral (WordView-3) sensors. [ABSTRACT FROM AUTHOR]

Leaf traits and physiological performance govern the amount of light reflected from leaves at visible and infrared wavebands. Information on leaf optical properties of tropical trees is scarce. Here, we examine leaf reflectance of Mesoamerican trees for three applications: (1) to compare the magnitude of within- and between-species variability in leaf reflectance, (2) to determine the potential for species identification based on leaf reflectance, and (3) to test the strength of relationships between leaf traits (chlorophyll content, mesophyll attributes, thickness) and leaf spectral reflectance. Within species, shape and amplitude differences between spectra were compared within single leaves, between leaves of a single tree, and between trees. We also investigated the variation in a species' leaf reflectance across sites and seasons. Using forward feature selection and pattern recognition tools, species classification within a single site and season was successful, while classification between sites or seasons was not. The implications of variability in leaf spectral reflectance were considered in light of potential tree crown classifications from remote airborne or satellite-borne sensors. Species classification is an emerging field with broad applications to tropical biologists and ecologists, including tree demographic studies and habitat diversity assessments. [ABSTRACT FROM AUTHOR]