Detection of Interlayered Illite/Smectite Clay Minerals with XRD, SEM Analyses and Reflectance Spectroscopy.

Accurate determination of clay minerals can be challenging due to the natural occurrence of interlayered phases, i.e., layers of different clay species such as illite and smectite. The overlap of peaks of the constituent minerals (e.g., illite and smectite), and the similarity of diffraction patterns when not treated with ethylene glycol, hampers identification, especially when the clay content is low. We investigated the occurrence of interlayered illite/smectite in a rock sample from Rodalquilar, Spain, using X-ray diffraction, scanning electron microscopy and reflectance spectroscopy in the short-wave infrared wavelength range. For the first time, a precise determination of interlayered I/S conducted on the extracted clay fraction treated with ethylene glycol using such different approaches was provided. X-ray diffraction results demonstrated the presence of an I/S peak at around 8.4° in the untreated fraction coupled with a peak splitting at 6.7° and 9.4° 2θ when solvated with ethylene glycol. While spectroscopy indicated the occurrence of interlayered structures as a mixture of the two constituent minerals, the results of X-ray analysis showed that the interlayered clay consisted of two discrete phases (illite and smectite). The two discrete phases were observed in both the whole rock analysis and in the extracted clay fraction. This study shows that X-ray diffraction and validation with a scanning electron microscope is a mandatory, integrating tool for detecting interlayered phases since reflectance spectroscopy alone cannot be used to differentiate between interlayered clay minerals and non-interlayered mixtures. This work highlights the limits and advantages of three sensors (X-ray diffraction, scanning electron microscopy and reflectance spectroscopy) to investigate clay mixtures and interlayering, representing a significant contribution to confidence in the interpretation of interlayered clays, this being essential in mineral exploration and prospecting.

Spatio-temporal landslide inventory and susceptibility assessment using Sentinel-2 in the Himalayan mountainous region of Pakistan.

The 2005 Kashmir earthquake has triggered widespread landslides in the Himalayan mountains in northern Pakistan and surrounding areas, some of which are active and are still posing a significant risk. Landslides triggered by the 2005 Kashmir earthquake are extensively studied; nevertheless, spatio-temporal landslide susceptibility assessment is lacking. This can be partially attributed to the limited availability of high temporal resolution remote sensing data. We present a semi-automated technique to use the Sentinel-2 MSI data for co-seismic landslide detection, landslide activities monitoring, spatio-temporal change detection, and spatio-temporal susceptibility mapping. Time series Sentinel-2 MSI images for the period of 2016-2021 and ALOS PALSAR DEM are used for semi-automated landslide inventory map development and temporal change analysis. Spectral information combined with topographical, contextual, textural, and morphological characteristics of the landslide in Sentinel-2 images is applied for landslide detection. Subsequently, spatio-temporal landslide susceptibility maps are developed utilizing the weight of evidence statistical modeling with seven causative factors, i.e., elevation, slope, geology, aspect, distance to fault, distance to roads, and distance to streams. The results reveal that landslide occurrence increased from 2016 to 2021 and that the coverage of areas of relatively high susceptibility has increased in the study area.

Mineral Interpretation Discrepancies Identified between Infrared Reflectance Spectra and X-ray Diffractograms.

Mineral composition can be determined using different methods such as reflectance spectroscopy and X-ray diffraction (XRD). However, in some cases, the composition of mineral maps obtained from reflectance spectroscopy with XRD shows inconsistencies in the mineral composition interpretation and the estimation of (semi-)quantitative mineral abundances. We show why these discrepancies exist and how should they be interpreted. Part of the explanation is related to the sample choice and preparation; another part is related to the fact that clay minerals are active in the short-wave infrared, whereas other elements in the composition are not. Together, this might lead to distinctly different interpretations for the same material, depending on the methods used. The main conclusion is that both methods can be useful, but care should be given to the limitations of the interpretation process. For infrared reflectance spectroscopy, the lack of an actual threshold value for the H-OH absorption feature at 1900 nm and the poorly defined Al-OH absorption feature at 2443 nm, as well as for XRD, detection limit, powder homogenizing, and the small amount of montmorillonite below 1 wt.%, was the source of discrepancies.

Monitoring Soil Moisture Dynamics Using Electrical Resistivity Tomography under Homogeneous Field Conditions.

There is a gap between lab experiments where resistivity-soil moisture relations are generally very good and field studies in complex environmental settings where relations are always less good and complicated by many factors. An experiment was designed where environmental settings are more controlled, the best outside laboratory, to assess the transferability from lab to outdoor. A field experiment was carried out to evaluate the use of electric resistivity tomography (ERT) for monitoring soil moisture dynamics over a period of 67 days. A homogeneous site in the central part of The Netherlands was selected consisting of grass pasture on an aeolian sand soil profile. ERT values were correlated to gravimetric soil moisture samples for five depths at three different dates. Correlations ranged from 0.43 to 0.73 and were best for a soil depth of 90 cm. Resistivity patterns over time (time-lapse ERT) were analyzed and related to rainfall events where rainfall infiltration patterns could be identified. Duplicate ERT measurements showed that the noise level of the instrument and measurements is low and generally below 3% for the soil profile below the mixed layer but above the groundwater. Although the majority of the measured resistivity patterns could be well explained, some artefacts and dynamics were more difficult to clarify, even so in this homogeneous field situation. The presence of an oak tree with its root structure and a ditch with surface water with higher conductivity may have an impact on the resistivity pattern in the soil profile and over time. We conclude that ERT allows for detailed spatial measurement of local soil moisture dynamics resulting from precipitation although field experiments do not yield accuracies similar to laboratory experiments. ERT approaches are suitable for detailed spatial analyses where probe or sample-based methods are limited in reach or repeatability.

Adjusting spectral indices for spectral response function differences of very high spatial resolution sensors simulated from field spectra.

The use of data from multiple sensors is often required to ensure data coverage and continuity, but differences in the spectral characteristics of sensors result in spectral index values being different. This study investigates spectral response function effects on 48 spectral indices for cultivated grasslands using simulated data of 10 very high spatial resolution sensors, convolved from field reflectance spectra of a grass covered dike (with varying vegetation condition). Index values for 48 indices were calculated for original narrow-band spectra and convolved data sets, and then compared. The indices Difference Vegetation Index (DVI), Global Environmental Monitoring Index (GEMI), Enhanced Vegetation Index (EVI), Modified Soil-Adjusted Vegetation Index (MSAVI2) and Soil-Adjusted Vegetation Index (SAVI), which include the difference between the near-infrared and red bands, have values most similar to those of the original spectra across all 10 sensors (1:1 line mean 1:1R2 > 0.960 and linear trend mean ccR2 > 0.997). Additionally, relationships between the indices' values and two quality indicators for grass covered dikes were compared to those of the original spectra. For the soil moisture indicator, indices that ratio bands performed better across sensors than those that difference bands, while for the dike cover quality indicator, both the choice of bands and their formulation are important.

Thermal infrared spectrometer for Earth science remote sensing applications-instrument modifications and measurement procedures.

In this article we describe a new instrumental setup at the University of Twente Faculty ITC with an optimized processing chain to measure absolute directional-hemispherical reflectance values of typical earth science samples in the 2.5 to 16 µm range. A Bruker Vertex 70 FTIR spectrometer was chosen as the base instrument. It was modified with an external integrating sphere with a 30 mm sampling port to allow measuring large, inhomogeneous samples and quantitatively compare the laboratory results to airborne and spaceborne remote sensing data. During the processing to directional-hemispherical reflectance values, a background radiation subtraction is performed, removing the effect of radiance not reflected from the sample itself on the detector. This provides more accurate reflectance values for low-reflecting samples. Repeat measurements taken over a 20 month period on a quartz sand standard show that the repeatability of the system is very high, with a standard deviation ranging between 0.001 and 0.006 reflectance units depending on wavelength. This high level of repeatability is achieved even after replacing optical components, re-aligning mirrors and placement of sample port reducers. Absolute reflectance values of measurements taken by the instrument here presented compare very favorably to measurements of other leading laboratories taken on identical sample standards.

A Spatial-Spectral Approach for Visualization of Vegetation Stress Resulting from Pipeline Leakage.

Hydrocarbon leakage into the environment has large economic and environmental impact. Traditional methods for investigating seepages and their resulting pollution, such as drilling, are destructive, time consuming and expensive. Remote sensing is an efficient tool that offers a non-destructive investigation method. Optical remote sensing has been extensively tested for exploration of onshore hydrocarbon reservoirs and detection of hydrocarbons at the Earth's surface. In this research, we investigate indirect manifestations of pipeline leakage by way of visualizing vegetation anomalies in airborne hyperspectral imagery. Agricultural land-use causes a heterogeneous landcover; variation in red edge position between fields was much larger than infield red edge position variation that could be related to hydrocarbon pollution. A moving and growing kernel procedure was developed to normalzie red edge values relative to values of neighbouring pixels to enhance pollution related anomalies in the image. Comparison of the spatial distribution of anomalies with geochemical data obtained by drilling showed that 8 out of 10 polluted sites were predicted correctly while 2 out of 30 sites that were predicted clean were actually polluted.

Seismic evidence for water deep in Earth's upper mantle.

Water in the deep upper mantle can influence the properties of seismic discontinuities in the mantle transition zone. Observations of converted seismic waves provide evidence of a 20- to 35-kilometer-thick discontinuity near a depth of 410 kilometers, most likely explained by as much as 700 parts per million of water by weight.