Hyperspectral analysis of clay minerals

A study was carried out by collecting soil samples from parts of Gwalior and Shivpuri district, Madhya Pradesh in order to assess the dominant clay mineral of these soils using hyperspectral data, as 0.4 to 2.5 μm spectral range provides abundant and unique information about many important earth-surface minerals. Understanding the spectral response along with the soil chemical properties can provide important clues for retrieval of mineralogical soil properties. The soil samples were collected based on stratified random sampling approach and dominant clay minerals were identified through XRD analysis. The absorption feature parameters like depth, width, area and asymmetry of the absorption peaks were derived from spectral profile of soil samples through DISPEC tool. The derived absorption feature parameters were used as inputs for modelling the dominant soil clay mineral present in the unknown samples using Random forest approach which resulted in kappa accuracy of 0.795. Besides, an attempt was made to classify the Hyperion data using Spectral Angle Mapper (SAM) algorithm with an overall accuracy of 68.43 %. Results showed that kaolinite was the dominant mineral present in the soils followed by montmorillonite in the study area.

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Thermogravimetry/evolved water analysis (TG/EWA) combined with XRD for improved quantitative whole-rock analysis of clay minerals in sandstones

Clay Minerals ◽

10.1180/claymin.1995.030.1.03 ◽

1995 ◽

Vol 30 (1) ◽

pp. 27-38 ◽

Cited By ~ 8

Author(s):

D. M. Thornley ◽

T. J. Primmer

Keyword(s):

Clay Minerals ◽

Clay Mineral ◽

Water Analysis ◽

Infrared Detector ◽

Size Fraction ◽

Xrd Analysis ◽

X Ray Diffraction ◽

Northern North Sea ◽

Rock Analysis

AbstractCurrent methods of quantitative whole-rock clay mineral analysis of sandstones often provide little more than an estimate of clay mineral abundances, especially where the total clay mineral content is <10 wt% of the sandstone. More accurate determinations of clay mineral abundance in the whole rock can be made by combining thermogravimetry/evolved water analysis (TG/EWA) and X-ray diffraction (XRD) data. The TGA/EWA system incorporates a purpose built thermobalance linked to a water specific infrared detector which is used to measure quantitatively the clay mineral dehydroxylation water evolved from the whole rock when heated from 250°C to 900°C. This gives a measure of the total hydroxyl content of the clay minerals in the whole rock which, when combined with XRD analysis of a separated clay size-fraction, enables individual clay mineral abundances in the whole-rock sample to be determined. Results on artificial sand/clay mineral mixtures prepared with known amounts of different clay minerals (chlorite, illite and kaolinite) show that the accuracy of the combined method is most influenced by the accuracy of the XRD data. Errors associated with TG/EWA were found to be negligible by comparison. A case study is included in which the technique has been used to determine accurately the illite abundance in the Magnus Sandstone Reservoir, Northern North Sea.

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New Hyperspectral Procedure to Discriminate Intertidal Macroalgae

Remote Sensing ◽

10.3390/rs14020346 ◽

2022 ◽

Vol 14 (2) ◽

pp. 346

Author(s):

Florian Douay ◽

Charles Verpoorter ◽

Gwendoline Duong ◽

Nicolas Spilmont ◽

François Gevaert

Keyword(s):

Spectral Response ◽

Hyperspectral Data ◽

Species Level ◽

Embedded Sensors ◽

Viewing Angle ◽

Species Classification ◽

Spectral Angle Mapper ◽

New Approach ◽

Classification Approach ◽

First Derivative

The recent development and miniaturization of hyperspectral sensors embedded in drones has allowed the acquisition of hyperspectral images with high spectral and spatial resolution. The characteristics of both the embedded sensors and drones (viewing angle, flying altitude, resolution) create opportunities to consider the use of hyperspectral imagery to map and monitor macroalgae communities. In general, the overflight of the areas to be mapped is conconmittently associated accompanied with measurements carried out in the field to acquire the spectra of previously identified objects. An alternative to these simultaneous acquisitions is to use a hyperspectral library made up of pure spectra of the different species in place, that would spare field acquisition of spectra during each flight. However, the use of such a technique requires developed appropriate procedure for testing the level of species classification that can be achieved, as well as the reproducibility of the classification over time. This study presents a novel classification approach based on the use of reflectance spectra of macroalgae acquired in controlled conditions. This overall approach developed is based on both the use of the spectral angle mapper (SAM) algorithm applied on first derivative hyperspectral data. The efficiency of this approach has been tested on a hyperspectral library composed of 16 macroalgae species, and its temporal reproducibility has been tested on a monthly survey of the spectral response of different macro-algae species. In addition, the classification results obtained with this new approach were also compared to the results obtained through the use of the most recent and robust procedure published. The classification obtained shows that the developed approach allows to perfectly discriminate the different phyla, whatever the period. At the species level, the classification approach is less effective when the individuals studied belong to phylogenetically close species (i.e., Fucus spiralis and Fucus serratus).

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Quantitative XRD bulk and clay mineralogical determination of paleosol sections of Unayzah and Basal Khuff clastics in Saudi Arabia

Powder Diffraction ◽

10.1017/s088571561200022x ◽

2012 ◽

Vol 27 (2) ◽

pp. 126-130 ◽

Cited By ~ 2

Author(s):

Shouwen Shen ◽

Syed R. Zaidi ◽

Bader A. Mutairi ◽

Ahmed A. Shehry ◽

Husin Sitepu ◽

...

Keyword(s):

Clay Minerals ◽

Clay Mineral ◽

Mixed Layer ◽

Size Fraction ◽

Xrd Analysis ◽

Ratio Method ◽

Type I ◽

Rock Formations ◽

Refinement Method

Quantitative X-ray diffraction (XRD) analysis is performed on 172 samples mainly containing paleosol sections of Unayzah and Basal Khuff clastics taken from the core of one well drilled by Saudi Aramco. Quantitative XRD bulk mineralogical determination is achieved using the Rietveld refinement method whereas quantitative XRD clay mineralogical determination of clay-size fraction is obtained using the reference intensity ratio method. The XRD results indicate that the samples from paleosol sections consist mainly of quartz and feldspar (microcline and albite) as framework constituents. Cement minerals include dolomite, hematite, anhydrite, siderite, gypsum, calcite, and pyrite. Clay minerals are important constituents in paleosols. The XRD results show that clay minerals in the samples are illite, mixed-layer illite/smectite, kaolinite, and chlorite. No discrete smectite is present in the samples. The clay mineral associations in these samples of paleosol sections can be classified into three types: Type I predominantly consists of illite and a mixed layer of illite/smectite; Type II of kaolinite; and Type III of illite and a mixed layer of illite/smectite, but also significant amounts of kaolinite. The change of clay mineral association type with sample depth can indicate the change of paleoclimate and paleoenvironment. For example, kaolinite usually forms under strongly leaching conditions such as abundant rainfall, good drainage, and acid waters. Therefore, XRD mineralogical data of paleosol sections are important for petroleum geologists to study paleoclimate and paleoenvironment and to predict the reservoir quality of the associated rock formations.

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Spectral Response Assessment of Moss-Dominated Biological Soil Crust Coverage Under Dry and Wet Conditions

Remote Sensing ◽

10.3390/rs12071158 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1158

Author(s):

Xiang Chen ◽

Tao Wang ◽

Shulin Liu ◽

Fei Peng ◽

Wenping Kang ◽

...

Keyword(s):

Spectral Response ◽

Biological Soil Crust ◽

Hyperspectral Data ◽

Absorption Feature ◽

Landsat 8 ◽

Soil Crust ◽

Red Edge ◽

Dry And Wet Conditions ◽

Low Coverage

Biological soil crusts (BSCs) are a major functional vegetation unit, covering extensive parts of drylands worldwide. Therefore, several multispectral indices have been proposed to map the spatial distribution and coverage of BSCs. BSCs are composed of poikilohydric organisms, the activity of which is sensitive to water availability. However, studies on dry and wet BSCs have seldom considered the mixed coverage gradient that is representative of actual field conditions. In this study, in situ spectral data and photographs of 136 pairs of dry and wet plots were collected to determine the influence of moisture conditions on BSC coverage detection. Then, BSC spectral reflectance and continuum removal (CR) reflectance responses to wetting were analyzed. Finally, the responses of four commonly used indices (i.e., normalized difference vegetation index (NDVI); crust index (CI); biological soil crust index (BSCI); and band depth of absorption feature after CR in the red band, (BD_red)), calculated from in situ hyperspectral data resampled to two multispectral data channels (Landsat-8 and Sentinel-2), were compared in dry and wet conditions. The results indicate that: (i) on average, the estimated BSC coverage using red-green-blue (RGB) images is 14.98% higher in wet than in dry conditions (P < 0.001); (ii) CR reflectance features of wet BSCs are more obvious than those of dry BSCs in both red and red-edge bands; and (iii) NDVI, CI, and BSCI for BSC coverage of 0%–60% under dry and wet conditions are close to those of dry and wet bare sand, respectively. NDVI and BD_red cannot separate dead wood and BSC with low coverage. This study demonstrates that low-coverage moss-dominated BSC is not easily detected by the four indices. In the future, remote-sensing data obtained during the rainy season with red and red-edge bands should be considered to detect BSCs.

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Caracterización de minerales de arcilla y óxidos de hierro mediante espectroscopía de reflectancia difusa (VNIR–SWIR)

Revista de Teledetección ◽

10.4995/raet.2020.13331 ◽

2020 ◽

pp. 49

Author(s):

A. Báscones ◽

M. Suárez ◽

M. Ferrer-Julià ◽

E. García-Meléndez ◽

E. Colmenero-Hidalgo ◽

...

Keyword(s):

Clay Minerals ◽

Spectral Response ◽

Absorption Feature ◽

Geometrical Parameters ◽

X Ray Diffraction ◽

Absorption Bands ◽

Mineral Phases ◽

Soils And Sediments ◽

Absorption Features ◽

Linear Correlations

<p>The mineralogical analysis was carried out through the spectral properties developed by samples of soils and sediments from the northwestern edge of the Duero Basin. The absorptions produced by the oxides and Feoxyhydroxides (mainly hematite and goethite) are located in VNIR zones (400-1200 nm), while the absorption bands that are present in the SWIR spectra (1200-2500 nm) are related to the chemical composition of clay minerals. The reflectance spectra measured in the laboratory have been normalized by using the methods of Continuum Removal (CR) and the second derivative (SD). This last method can solve the band overlapping because it quantifies subtle drops in the curve. This has allowed the absorption bands to be examined separately by measurement of their geometrical parameters. The proportion of the minerals affects the spectral response and, accordingly, the values of the parameters. Linear correlations were conducted between these values and the proportion of the different mineral phases obtained by X-ray diffraction. In the studied parameters, the correlation between the band center (BC) position in the maximum absorption around the wavelengths at 890-960 nm and the absorption feature depth at 470 nm (D470) has enabled a relative estimation of the proportion of hematite/goethite. As for the distribution of the different clay minerals, a correlation has been established between the proportion of kaolinite and the absorption bands depth at 1415 and 2210 nm, and in the absorption features near 1390 and 2160 nm, analyzed in SD.<em></em></p>

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Unsupervised Identification of Targeted Spectra Applying Rank1-NMF and FCC Algorithms in Long-Wave Hyperspectral Infrared Imagery

Remote Sensing ◽

10.3390/rs13112125 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2125

Author(s):

Bardia Yousefi ◽

Clemente Ibarra-Castanedo ◽

Martin Chamberland ◽

Xavier P. V. Maldague ◽

Georges Beaudoin

Keyword(s):

Matched Filter ◽

Principal Component ◽

Hyperspectral Data ◽

Clustering Methods ◽

Spectral Angle Mapper ◽

Long Wave ◽

Clustering Approach ◽

Spectral Comparison ◽

Computational Simplicity ◽

Mineral Identification

Clustering methods unequivocally show considerable influence on many recent algorithms and play an important role in hyperspectral data analysis. Here, we challenge the clustering for mineral identification using two different strategies in hyperspectral long wave infrared (LWIR, 7.7–11.8 μm). For that, we compare two algorithms to perform the mineral identification in a unique dataset. The first algorithm uses spectral comparison techniques for all the pixel-spectra and creates RGB false color composites (FCC). Then, a color based clustering is used to group the regions (called FCC-clustering). The second algorithm clusters all the pixel-spectra to directly group the spectra. Then, the first rank of non-negative matrix factorization (NMF) extracts the representative of each cluster and compares results with the spectral library of JPL/NASA. These techniques give the comparison values as features which convert into RGB-FCC as the results (called clustering rank1-NMF). We applied K-means as clustering approach, which can be modified in any other similar clustering approach. The results of the clustering-rank1-NMF algorithm indicate significant computational efficiency (more than 20 times faster than the previous approach) and promising performance for mineral identification having up to 75.8% and 84.8% average accuracies for FCC-clustering and clustering-rank1 NMF algorithms (using spectral angle mapper (SAM)), respectively. Furthermore, several spectral comparison techniques are used also such as adaptive matched subspace detector (AMSD), orthogonal subspace projection (OSP) algorithm, principal component analysis (PCA), local matched filter (PLMF), SAM, and normalized cross correlation (NCC) for both algorithms and most of them show a similar range in accuracy. However, SAM and NCC are preferred due to their computational simplicity. Our algorithms strive to identify eleven different mineral grains (biotite, diopside, epidote, goethite, kyanite, scheelite, smithsonite, tourmaline, pyrope, olivine, and quartz).

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DFT Study of Electronic Structure and Optical Properties of Kaolinite, Muscovite, and Montmorillonite

Crystals ◽

10.3390/cryst11060618 ◽

2021 ◽

Vol 11 (6) ◽

pp. 618

Author(s):

Layla Shafei ◽

Puja Adhikari ◽

Wai-Yim Ching

Keyword(s):

Mechanical Properties ◽

Optical Properties ◽

Electronic Structure ◽

Hydrogen Bonds ◽

Clay Minerals ◽

Clay Mineral ◽

Bond Order ◽

Deep Understanding ◽

Pharmaceutical Applications ◽

Structure Properties

Clay mineral materials have attracted attention due to their many properties and applications. The applications of clay minerals are closely linked to their structure and composition. In this paper, we studied the electronic structure properties of kaolinite, muscovite, and montmorillonite crystals, which are classified as clay minerals, by using DFT-based ab initio packages VASP and the OLCAO. The aim of this work is to have a deep understanding of clay mineral materials, including electronic structure, bond strength, mechanical properties, and optical properties. It is worth mentioning that understanding these properties may help continually result in new and innovative clay products in several applications, such as in pharmaceutical applications using kaolinite for their potential in cancer treatment, muscovite used as insulators in electrical appliances, and engineering applications that use montmorillonite as a sealant. In addition, our results show that the role played by hydrogen bonds in O-H bonds has an impact on the hydration in these crystals. Based on calculated total bond order density, it is concluded that kaolinite is slightly more cohesive than montmorillonite, which is consistent with the calculated mechanical properties.

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Chemical Properties of Heavy Metal-Contaminated Soils from a Korean Military Shooting Range: Evaluation of Pb Sources Using Pb Isotope Ratios

Applied Sciences ◽

10.3390/app11157099 ◽

2021 ◽

Vol 11 (15) ◽

pp. 7099

Author(s):

Inkyeong Moon ◽

Honghyun Kim ◽

Sangjo Jeong ◽

Hyungjin Choi ◽

Jungtae Park ◽

...

Keyword(s):

Heavy Metals ◽

Heavy Metal ◽

Contaminated Soils ◽

Management Strategies ◽

Chemical Properties ◽

Heavy Metal Concentration ◽

Soil Samples ◽

Shooting Range ◽

Geochemical Properties ◽

Mineral Phases

In this study, the geochemical properties of heavy metal-contaminated soils from a Korean military shooting range were analyzed. The chemical behavior of heavy metals was determined by analyzing the soil pH, heavy metal concentration, mineral composition, and Pb isotopes. In total, 24 soil samples were collected from a Korean military shooting range. The soil samples consist of quartz, albite, microcline, muscovite/illite, kaolinite, chlorite, and calcite. Lead minerals, such as hydrocerussite and anglesite, which are indicative of a transformation into secondary mineral phases, were not observed. All soils were strongly contaminated with Pb with minor concentrations of Cu, Ni, Cd, and Zn. Arsenic was rarely detected. The obtained results are indicated that the soils from the shooting range are contaminated with heavy metals and have evidences of different degree of anthropogenic Pb sources. This study is crucial for the evaluation of heavy metal-contaminated soils in shooting ranges and their environmental effect as well as for the establishment of management strategies for the mitigation of environmental risks.

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The influence of biochar on the content of carbon and the chemical transformations of fallow and grassland humic acids

Scientific Reports ◽

10.1038/s41598-021-85239-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Marta Cybulak ◽

Zofia Sokołowska ◽

Patrycja Boguta

Keyword(s):

Humic Acids ◽

Chemical Properties ◽

Soil Samples ◽

Low Molecular Weight ◽

Organic Carbon Content ◽

Chemical Transformations ◽

Limited Information ◽

Grassland Soils ◽

Low Degree ◽

Humification Degree

AbstractThere is limited information regarding the effect of biochar (BioC) on the fertility of fallow and grassland soils, as well as on the properties of their humic acids (HAs). The objective of this study was to evaluate with a 3-year field experiment the influence of BioC on the organic matter (OM) in Haplic Luvisol. BioC (obtained via wood waste pyrolysis at 650 °C) was applied to the soil of subplots under fallow and grassland at doses of 0, 1, 2 and 3 kg m−2. The soil samples were collected eight times. The physicochemical properties were determined for the soil and BioC by analysing the density, pH, surface charge, ash, and organic carbon content. Based on the changes in the structure of the HAs and their quantity in the soils, the chemical properties of the HAs were determined. The maximum BioC dose caused an increase in the content of Corg and HAs. BioC did not influence the humification degree coefficients of the HAs originated from fallow, whereas in the grassland, there were significant changes observed in these coefficient values, indicating that BioC may stimulate and accelerate the humification process of soil HAs. Increasing the BioC doses caused an increase in the soil’s HA content, suggesting an increase in soil sorption capacity. The fluorescence data showed BioC addition to the soil caused an increase in the number of structures characterised by low molecular weight and a low degree of humification.

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Hyperspectral Data Simulation (Sentinel-2 to AVIRIS-NG) for Improved Wildfire Fuel Mapping, Boreal Alaska

Remote Sensing ◽

10.3390/rs13091693 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1693

Author(s):

Anushree Badola ◽

Santosh K. Panda ◽

Dar A. Roberts ◽

Christine F. Waigl ◽

Uma S. Bhatt ◽

...

Keyword(s):

Land Cover ◽

Spectral Resolution ◽

Hyperspectral Image ◽

Spectral Response ◽

Spectral Characteristics ◽

Hyperspectral Data ◽

Spectral Unmixing ◽

High Spectral Resolution ◽

Fuel Mapping ◽

Sentinel 2

Alaska has witnessed a significant increase in wildfire events in recent decades that have been linked to drier and warmer summers. Forest fuel maps play a vital role in wildfire management and risk assessment. Freely available multispectral datasets are widely used for land use and land cover mapping, but they have limited utility for fuel mapping due to their coarse spectral resolution. Hyperspectral datasets have a high spectral resolution, ideal for detailed fuel mapping, but they are limited and expensive to acquire. This study simulates hyperspectral data from Sentinel-2 multispectral data using the spectral response function of the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor, and normalized ground spectra of gravel, birch, and spruce. We used the Uniform Pattern Decomposition Method (UPDM) for spectral unmixing, which is a sensor-independent method, where each pixel is expressed as the linear sum of standard reference spectra. The simulated hyperspectral data have spectral characteristics of AVIRIS-NG and the reflectance properties of Sentinel-2 data. We validated the simulated spectra by visually and statistically comparing it with real AVIRIS-NG data. We observed a high correlation between the spectra of tree classes collected from AVIRIS-NG and simulated hyperspectral data. Upon performing species level classification, we achieved a classification accuracy of 89% for the simulated hyperspectral data, which is better than the accuracy of Sentinel-2 data (77.8%). We generated a fuel map from the simulated hyperspectral image using the Random Forest classifier. Our study demonstrated that low-cost and high-quality hyperspectral data can be generated from Sentinel-2 data using UPDM for improved land cover and vegetation mapping in the boreal forest.

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