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The paper addresses the challenge of measuring water content and evaporative fluxes from oil sands soft tailings surfaces using hyperspectral observations. Hyperspectral time-series laboratory observations were collected from four different mature fine tailings (MFT) samples displaying variations in swelling potential and bitumen concentration. The samples were allowed to evaporate from an initial state of water saturation to an air-dried state. From these data, several spectral features were evaluated to predict water content and normalized evaporation rate from the optically sensed portion of the tailings surface (less than a few hundred micrometres). For the samples tested, the best estimate of moisture content was achieved using the normalized soil moisture index (NSMI) index (coefficient of determination [R.sup.2] = 0.97). The absolute reflectance at 1920 nm was found to be the best spectral estimator of normalized evaporation ([R.sup.2] = 0.97), with the NSMI index also being valuable ([R.sup.2] = 0.95). In both instances, the NSMI index may be of value for estimations attempted in the field. Remote estimation of moisture content and evaporation could help tailings managers assess the drying process to determine when the deposit has stopped drying at the surface and decide when the next lift should be deposited. In future efforts, the models obtained from this laboratory investigation will be assessed for their applicability in field settings and validated using concurrent sampling. Key words: oil sands, tailings, mature fine tailings, hyperspectral data, moisture content, evaporation. L'article aborde le defi de mesurer la teneur en eau et les flux d'evaporation a partir des surfaces de residus mous des sables bitumineux en utilisant des observations hyperspectrales. Des observations de laboratoire en series chronologiques hyperspectrales ont ete recueillies a partir de quatre matures echantillons de residus fins murs (MFT << mature fine tailings >>) differents presentant des variations de gonflement potentiel et de concentration en bitume. Les echantillons ont ete laisses a s'evaporer a partir d'un etat initial de saturation en eau a un etat seche par air. A partir de ces donnees, plusieurs caracteristiques spectrales ont ete evaluees afin de predire la teneur en eau et le taux d'evaporation normalise a partir de la partie detectee optiquement de la surface des residus (moins de quelque 100 µm. Pour les echantillons testes, la meilleure estimation de la teneur en eau a ete realisee en utilisant l'indice normalise d'humidite de sol (NSMI << normalized soil moisture index >>) (coefficient de determination [R.sup.2] = 0.97). La reflectance absolue a 1920 nm a ete trouvee a etre le meilleur estimateur spectral d'evaporation normalise ([R.sup.2] = 0.97) avec l'indice NSMI etant egalement de la valeur ([R.sup.2] = 0.95). Dans les deux cas, l'indice NSMI peut etre utile pour les estimations des tentatives dans le champ. L'estimation a distance de l'humidite et de l'evaporation pourrait aider les gestionnaires de residus a evaluer le processus de sechage pour determiner quand le depot a cesse de a se secher a la surface et decider quand le prochain elevage doit etre depose. Dans les efforts a l'avenir, les modeles obtenus a partir de cette enquete de laboratoire seront evalues pour leur applicabilite dans les milieux de terrain et valides en utilisant un echantillonnage simultane. [Traduit par la Redaction] Mots-cles : sables bitumineux, steriles, residus fins murs, donnees hyperspectrales, teneur en humidite, evaporation., Introduction The oil sands of northern Alberta comprise the third-largest proven reserves of petroleum in the world (Alberta Energy 2014). Oil sands are a natural unconsolidated mixture of sand, clays [...]

Fractional abundances predicted for a given pixel using spectral mixture analysis (SMA) are most accurate when only the endmembers that comprise it are used, with larger errors occurring if inappropriate endmembers are included in the unmixing process. This paper presents an iterative implementation of SMA (ISMA) to determine optimal per-pixel endmember sets from the image endmember set using two steps: 1) an iterative unconstrained unmixing, which removes one endmember per iteration based on minimum abundance and 2) analysis of the root-mean-square error as a function of iteration to locate the critical iteration defining the optimal endmember set. The ISMA was tested using simulated data at various signal-to-noise ratios (SNRs), and the results were compared with those of published unmixing methods. The ISMA method correctly selected the optimal endmember set 96% of the time for SNR of 100: 1. As a result, per-pixel errors in fractional abundances were lower than for unmixing each pixel using the full endmember set. ISMA was also applied to Airborne Visible/Infrared Imaging Spectrometer hyperspectral data of Cuprite, NV. Results show that the ISMA is effective in obtaining abundance fractions that are physically realistic (sum close to one and nonnegative) and is more effective at selecting endmembers that occur within a pixel as opposed to those that are simply used to improve the goodness of fit of the model but not part of the mixture. Index Terms--Data processing, optimization methods, remote sensing, spectral analysis.

Initiated in 1984, the Committee Earth Observing Satellites' Working Group on Calibration and Validation (CEOS WGCV) pursues activities to coordinate, standardize and advance calibration and validation of civilian satellites and their data. One subgroup of CEOS WGCV, Land Product Validation (LPV), was established in 2000 to define standard validation guidelines and protocols and to foster data and information exchange relevant to the validation of land products. Since then, a number of leaf area index (LAI) products have become available to the science community at both global and regional extents. Having multiple global LAI products and multiple, disparate validation activities related to these products presents the opportunity to realize efficiency through international collaboration. So the LPV subgroup established an international LAI intercomparison validation activity. This paper describes the main components of this international validation effort. The paper documents the current participants, their ground LAI measurements and scaling techniques, and the metadata and infrastructure established to share data. The paper concludes by describing plans for sharing both field data and high-resolution LAI products from each site. Many considerations of this global LAI intercomparison can apply to other products, and this paper presents a framework for such collaboration. Index Terms--Committee on Earth Observing Satellites (CEOS) leaf area index (LAI), validation.

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. Key words: classification; hyperspectral; interspecific; intraspecific; leaf level; Mesoamerica; tropical trees.

In this study, we investigated the use of Bayesian networks for inferring tropical dry forest leaf area index (LAI) from satellite imagery in dry and wet seasons. LAI was chosen as the variable of interest because leaf area is the exchange surface between the photosynthetically active component of the canopy and the atmosphere. Initial network estimates were obtained from ground truth plot data with known forest structure, LAI, and satellite reflectance in the red and near-infrared bands (as observed by the Landsat 7 Enhanced Thematic Mapper Plus sensor). We tested the performance of the Bayesian networks with scoring rules and also with confidence and surprise scores. We evaluated the networks on a per-pixel basis and created both LAI maps of the study area as well predicted the probability maps for the highest LAI states. Results not only demonstrate the predictive power of a Bayesian network but also its explanatory power which is far beyond what is typically available with current pixel classifier approaches such as spectral vegetation indices or other approaches such as neural networks. Index Terms--Bayesian networks, leaf area index (LAI), probabilistic inference, tropical dry forest.

This study investigates the usefulness of thermal infrared reflectance spectroscopy (TIR) to map rock faces in an underground environment. A laboratory Fourier transform infrared (FTIR) spectrometer was used to measure reflectance spectra (500-5000 [cm.sup.-1]) of freshly broken rock surfaces. A total of 37 samples covering 10 different rock types, including barren silicate rocks and rocks with disseminated sulfides, was collected from eight mines around the Sudbury Basin in Ontario. Freshly broken rock surfaces were measured wet and dry to address environmental conditions encountered underground. Spectral data were processed by the second-derivative approach and the spectral angle mapper algorithm (SAM) for rock-type identification. An average of 77% accuracy was achieved for all rock types. The success of this effort implies that hyperspectral analysis using second-derivative spectra is effective to remove the effect of liquid water, local geometry, and disseminated sulfides while preserving diagnostic rock spectral signatures between 700 and 1300 [cm.sup.-1]. Keywords: rock cores, spectroscopy, thermal, underground mining.

Spectral mixture analysis (SMA) has been used extensively in the hyperspectral remote sensing community for the subpixel abundance estimation of targets. However, the task of defining every endmember can be difficult, as evident from the importance attributed to the topic in the recent literature. The effectiveness of SMA can be compromised when the required spectral endmembers are not well constrained in terms of their spectral magnitude and shape. The spectral magnitude of the endmembers is more difficult to obtain than their spectral shape, in part because the effects of the atmosphere and topography are difficult to constrain. This paper presents a derivative spectral unmixing (DSU) model, which is an extension of the spectral mixture analysis and derivative analysis. Using a DSU approach, it is possible to estimate the fraction of an endmember characterized by one or more diagnostic absorption features despite having only a general knowledge of the spectral shapes of the remaining endmembers. The DSU is assessed using spectral data acquired for a lichen-covered rock sample, and the estimated fractions of lichen and rock are assessed against that obtained from a high spatial resolution digital photograph. The results of the laboratory experiments suggests that the DSU is a promising algorithm for the quantitative analysis of hyperspectral data, but experiments on airborne/spaceborne imagery are now required to assess its value for geological mapping. Index Terms--Hyperspectral, spectral derivative, unmixing.

In‐line flocculation of oil sands tailings is a technique widely used in the oil sands industry to dewater fluid fine tailings. In this method, flocculants are added to the tailings to aggregate the fine particles and increase the settling rate and dewatering performance. Among the factors controlling the flocculation performance, the flocculant dose, rate and time of mixing play a crucial role. Consequently, the development of techniques that can monitor flocculation and provide feedback information to adjust flocculant dose and mixing conditions is of significant interest to the oil sands industry. This paper examines how hyperspectral imagery can be used to monitor tailings flocculation through post‐depositional spectral measurements and image analysis. The results show that hyperspectral imagery can detect under‐dosed and over‐sheared samples, but experiments over a wider range of flocculation conditions are required to validate the results and calibrate the method. This study represents the initial step in the development of a spectral method for monitoring and assessment of the flocculation process. [ABSTRACT FROM AUTHOR]

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]

Clay minerals constitute a significant fraction of oil sands tailings; and clay mineralogy, abundance, and morphology can dramatically affect the strength of the tailings during consolidation. The ability of clays to expand or swell in the presence of water is of importance in establishing the post-depositional strength and the geotechnical stability of a tailings deposit for reclamation purposes. The surface activity of oil sands tailings solids is typically determined using the methylene blue index (MBI), an analytical technique that quantifies the ionic absorption capacity of a sample. The present work explores the use of short-wave infrared (SWIR) and long-wave infrared (LWIR) hyperspectral observations for the estimation of the swelling potential or activity of oil sands tailings indicated by MBI. Spectral features in reflectance spectra were characterized in the SWIR and LWIR, in particular those attributed to the presence of quartz and clays. These features were employed to assess the correlation between MBI and remote sensing reflectance measurements collected in the laboratory from air-dried tailings. In the SWIR, a band ratio of reflectance at 2.111 and 1.992 μm was highly correlated with MBI. For the potential estimation of MBI in outdoor settings, where the intervening atmosphere can impact the spectral measurements, a band ratio of reflectance at 1.773 and 1.307 μm provided an estimation of MBI when moisture of tailings did not exceed 0.20 g/g (20 wt%). The best predictions of MBI were obtained in the LWIR using the reflectance peaks at 9.67 µm and 11 µm attributable to clay minerals. [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]

Aim: The general goal of this study is to investigate and analyze patterns of ecophysiological leaf traits and spectral response among life forms (trees, shrubs and lianas) in the Cerrado ecosystem. In this study, we first tested whether life forms are discriminated through leaf level functional traits. We then explored the correlation between leaf-level plant functional traits and spectral reflectance. Location: Serra do Cipo National Park, Minas Gerais, Brazil. Methods: Six ecophysiological leaf traits were selected to best characterize differences between life forms in the woody plant community of the Cerrado. Results were compared to spectral vegetation indices to determine if plant groups provide means to separate leaf spectral responses. Results: Values obtained from leaf traits were similar to results reported from other tropical dry sites. Trees and shrubs significantly differed from lianas in terms of the percentage of leaf water content and Specific Leaf Area. Spectral indices were insufficient to capture the differences of these key traits between groups, though indices were still adequately correlated to overall trait variation. Conclusion: The importance of life forms as biochemical and structurally distinctive groups is a significant finding for future remote sensing studies of vegetation, especially in arid and semi-arid environments. The traits we found as indicative of these groups (SLA and water content) are good candidates for spectral characterization. Future studies need to use the full wavelength (400 nm–2500 nm) in order to capture the potential response of these traits. The ecological linkage to water balance and life strategies encourages these traits as starting points for modeling plant communities using hyperspectral remote sensing. [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]