ALBERT

Description: Reflectance spectra of carbonate minerals in the shortwave infrared (SWIR) and thermal infrared (TIR) wavelength regions contain a number of diagnostic absorption features. The shape of these features depends on various physical and chemical parameters. To accurately identify carbonate minerals or rocks in pure and mixed form, it is necessary to analyze the effects of the parameters on spectral characteristics. In this study, we analyzed spectral absorption feature characteristics of calcite and dolomite in the SWIR (features at 2.3 and 2.5 μm) and TIR (features at 11.5 and 14 μm) wavelength regions, as a function of grain size and carbonate mineral mixtures. Results showed that varying grain sizes and mineral contents in the sample, influence reflectance values and absorption feature characteristics. Absorption band positions of pure and mixed calcite and dolomite in the SWIR and TIR regions for both features were displaced slightly as observed in previous studies. The band positions of calcite and dolomite varied relative to grain size only in the TIR region. These positions shifted to longer wavelengths for the feature at 11.5 μm and to shorter wavelengths for the feature at 14 μm from fine to coarse grain size. The band positions of calcite-dolomite mixtures in the SWIR and TIR regions were determined by the quantity of calcite and dolomite in the sample. These results can be applied for the identification of pure and mixed calcite and dolomite, as well as estimating the relative abundance of both minerals with different grain size and mineral mixtures in a synthetic sample or rock. They can also be used as a preliminary proxy for assessing dolomitization patterns in carbonate rocks.

Description: The development of advanced laboratory-based imaging hyperspectral sensors, such as SisuCHEMA, has created an opportunity to extract compositional information of mineral mixtures from spectral images. Determining proportions of minerals on rock surfaces based on spectral signature is a challenging approach due to naturally-occurring minerals that exist in the form of intimate mixtures, and grain size variations. This study demonstrates the application of SisuCHEMA hyperspectral data to determine mineral components in hand specimens of carbonate rocks. Here, we applied wavelength position, spectral angle mapper (SAM) and linear spectral unmixing (LSU) approaches to estimate the chemical composition and the relative abundance of carbonate minerals on the rock surfaces. The accuracy of these classification methods and correlation between mineral chemistry and mineral spectral characteristics in determining mineral constituents of rocks are also analyzed. Results showed that chemical composition (Ca-Mg ratio) of carbonate minerals at a pixel (e.g., sub-grain) level can be extracted from the image pixel spectra using these spectral analysis methods. The results also indicated that the spatial distribution and the proportions of calcite-dolomite mixtures on the rock surfaces vary between the spectral methods. For the image shortwave infrared (SWIR) spectra, the wavelength position approach was found to be sensitive to all compositional variations of carbonate mineral mixtures when compared to the SAM and LSU approaches. The correlation between geochemical elements and spectroscopic parameters also revealed the presence of these carbonate mixtures with various chemical compositions in the rock samples. This study concludes that the wavelength position approach is a stable and reproducible technique for estimating carbonate mineral chemistry on the rock surfaces using laboratory-based hyperspectral data.

Description: Hydrocarbon seeps cause chemical and mineralogical changes at the surface, which can be detected by remote sensing. This paper aims at the detection of mineral alteration induced by gas seeps in a marly limestone formation, SW Iran. For this purpose, the multispectral Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the high spatial resolution WorldView-2 (WV-2) data were utilized for mapping surficial rock alteration. In addition, the potential of Visible Near Infrared (VNIR) bands of the WV-2 and its high spatial resolution for mapping alterations was determined. Band ratioing, principal component analysis (PCA), data fusion and the boosted regression trees (BRT) were applied to enhance and classify the altered and unaltered marly limestone formation. The alteration zones were identified and mapped by remote sensing analyses. Integrating the WV-2 into the ASTER data improved the spatial accuracy of the BRT classifications. The results showed that the BRT classification of the multiple band imagery (created from ASTER and WV-2) using regions of interest (ROIs) around field data provides the best discrimination between altered and unaltered areas. It is suggested that the WV-2 dataset can provide a potential tool along higher spectral resolution data for mapping alteration minerals related to hydrocarbon seeps in arid and semi-arid areas.

Description: Reflectance spectra of carbonate minerals in the shortwave infrared (SWIR) and thermal infrared (TIR) wavelength regions contain a number of diagnostic absorption features. The shape of these features depends on various physical and chemical parameters. To accurately identify carbonate minerals or rocks in pure and mixed form, it is necessary to analyze the effects of the parameters on spectral characteristics. In this study, we analyzed spectral absorption feature characteristics of calcite and dolomite in the SWIR (features at 2.3 and 2.5 μm) and TIR (features at 11.5 and 14 μm) wavelength regions, as a function of grain size and carbonate mineral mixtures. Results showed that varying grain sizes and mineral contents in the sample, influence reflectance values and absorption feature characteristics. Absorption band positions of pure and mixed calcite and dolomite in the SWIR and TIR regions for both features were displaced slightly as observed in previous studies. The band positions of calcite and dolomite varied relative to grain size only in the TIR region. These positions shifted to longer wavelengths for the feature at 11.5 μm and to shorter wavelengths for the feature at 14 μm from fine to coarse grain size. The band positions of calcite-dolomite mixtures in the SWIR and TIR regions were determined by the quantity of calcite and dolomite in the sample. These results can be applied for the identification of pure and mixed calcite and dolomite, as well as estimating the relative abundance of both minerals with different grain size and mineral mixtures in a synthetic sample or rock. They can also be used as a preliminary proxy for assessing dolomitization patterns in carbonate rocks.

Description: Sentinel-2A MSI is the Landsat-like spatial resolution (10–60 m) super-spectral instrument of the European Space Agency (ESA), aimed at additional data continuity for global land surface monitoring with Landsat and Satellite Pour l’Observation de la Terre (SPOT) missions. Several simulation studies have been conducted in the last several years to show the potential of Sentinel-2A MSI (MultiSpectral Instrument). Now that real data are available, the first confirmations of this potential and comparisons with other operational systems are being made. This paper aims at evaluating Sentinel-2A MSI band ratio products that are relevant for geological remote sensing. A Sentinel-2A MSI and a Landsat 8 OLI (Operational Land Imager) scene were processed from their respective levels L1C and L1T to level L2A (bottom of atmosphere reflectance). Then, three band ratios originally defined for Landsat TM (Thematic Mapper) were used to map mineralogy associated with a hydrothermal alteration system in southeast Spain. The results obtained with Sentinel-2A MSI were compared with those obtained with Landsat 8 OLI and a simulated Sentinel-2A MSI dataset that was used before actual data were released. Results show that the images appear similar to the human eye having a correlation of approximately 0.8 and higher, but that the associated data ranges differ significantly. The resulting products are also compared to a published geologic map of the study area, and it is shown that the resulting maps correspond with the conceptual geologic model of the epithermal deposit.

Description: Shortwave infrared (SWIR) spectroscopy can be applied directly to analyze the mineral chemistry of raw or geologic materials. It provides diagnostic spectral characteristics of the chemical composition of minerals, information that is invaluable for the identification and quality control of such materials. The present study aims to investigate the potential of SWIR spectroscopy as an alternative quality control technique for the mineral chemistry analysis of Portland cement-grade limestone. We used the spectroscopic (wavelength position and depth of absorption feature) and geochemical characteristics of limestone samples to estimate the abundance and composition of carbonate and clay minerals on rock surfaces. The depth of the carbonate (CO3) and Al-OH absorption features are linearly correlated with the contents of CaO and Al2O3 in the samples, respectively, as determined by portable X-ray fluorescence (PXRF) measurements. Variations in the wavelength position of CO3 and Al-OH absorption features are related to changes in the chemical compositions of the samples. The results showed that the dark gray and light gray limestone samples are better suited for manufacturing Portland cement clinker than the dolomitic limestone samples. This finding is based on the CaO, MgO, Al2O3, and SiO2 concentrations and compositions. The results indicate that SWIR spectroscopy is an appropriate approach for the chemical quality control of cement raw materials.

Description: The soil minerals determine essential soil properties such as the cation exchange capacity, texture, structure, and their capacity to form bonds with organic matter. Any alteration of these organo-mineral interactions due to the soil moisture variations needs attention. Visible near-infrared imaging spectroscopy is capable of assessing spectral soil constituents that are responsible for the organo-mineral interactions. In this study, we hypothesized that the alterations of the surface soil mineralogy occur due to the moisture variations. For eight weeks, under laboratory conditions, imaging spectroscopy data were collected on a 72 h basis for three Silty Loam soils varying in the organic matter (no, low and high) placed at the drying-field capacity, field capacity and waterlogging-field capacity treatments. Using the Spectral Information Divergence image classifier, the image area occupied by the Mg-clinochlore, goethite, quartz coated 50% by goethite, hematite dimorphous with maghemite was detected and quantified (percentage). Our results showed these minerals behaved differently, depending on the soil type and soil treatment. While for the soils with organic matter, the mineralogical alterations were evident at the field capacity state, for the one with no organic matter, these changes were insignificant. Using imaging spectroscopy data on the Silty Loam soil, we showed that the surface mineralogy changes over time due to the moisture conditions.

Description: In hyperspectral image classification, so-called spectral endmembers are used as reference data. These endmembers are either extracted from an image or taken from another source. Research has shown that endmembers extracted from an image usually perform best when classifying a single image. However, it is unclear if this also holds when classifying multi-temporal hyperspectral datasets. In this paper, we use spectral angle mapper, which is a frequently used classifier for hyperspectral datasets to classify multi-temporal airborne visible/infrared imaging spectrometer (AVIRIS) hyperspectral imagery. Three classifications are done on each of the images with endmembers being extracted from the corresponding image, and three more classifications are done on the three images while using averaged endmembers. We apply image-to-image registration and change detection to analyze the consistency of the classification results. We show that the consistency of classification accuracy using the averaged endmembers (around 65%) outperforms the classification results generated using endmembers that are extracted from each image separately (around 40%). We conclude that, for multi-temporal datasets, it is better to have an endmember collection that is not directly from the image, but is processed to a representative average.

Description: The soil minerals determine essential soil properties such as the cation exchange capacity, texture, structure, and their capacity to form bonds with organic matter. Any alteration of these organo-mineral interactions due to the soil moisture variations needs attention. Visible near-infrared imaging spectroscopy is capable of assessing spectral soil constituents that are responsible for the organo-mineral interactions. In this study, we hypothesized that the alterations of the surface soil mineralogy occur due to the moisture variations. For eight weeks, under laboratory conditions, imaging spectroscopy data were collected on a 72 h basis for three Silty Loam soils varying in the organic matter (no, low and high) placed at the drying-field capacity, field capacity and waterlogging-field capacity treatments. Using the Spectral Information Divergence image classifier, the image area occupied by the Mg-clinochlore, goethite, quartz coated 50% by goethite, hematite dimorphous with maghemite was detected and quantified (percentage). Our results showed these minerals behaved differently, depending on the soil type and soil treatment. While for the soils with organic matter, the mineralogical alterations were evident at the field capacity state, for the one with no organic matter, these changes were insignificant. Using imaging spectroscopy data on the Silty Loam soil, we showed that the surface mineralogy changes over time due to the moisture conditions.