Freek D. van der Meer

Tracing fluid pathways in fossil hydrothermal systems with near-infrared spectroscopy

We present a new method to detect and reconstruct fluid pathways in fossil hydrothermal systems that is based on systematic study of white micas in hydrothermally altered rock, using near-infrared spectroscopy. This method, developed in an Early Archean volcanic sequence in the Panorama district in Western Australia, uses new near-infrared spectroscopic data and published geological and geochemical data of fossil submarine hydrothermal systems in the area. Analysis of new near-infrared spectroscopic data revealed that the abundance of white mica and its Al content in altered volcanic rock vary systematically along fossil fluid pathways, from zones of low-temperature recharge to zones of high-temperature discharge, as a function of hydrothermal fluid chemistry, temperature of alteration, coexisting minerals, and composition of volcanic host rock. The abundance of white mica relative to that of chlorite and the Al content of white micas can be used to discriminate among the hydrothermal alteration facies along these fluid pathways, which permits detection and reconstruction of fossil fluid pathways.

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.

Sequential indicator conditional simulation and indicator kriging applied to discrimination of dolomitization in GER 63-channel imaging spectrometer data

Laboratory reflectance spectra of synthetic mixtures of the carbonate minerals calcite and dolomite were measured in the visible and near-infrared wavelength region (0.4–2.5 μm) using a high-spectral resolution laboratory spectrometer. The instrument measured reflectivity with an accuracy of 0.001 μm, allowing detailed resolution of the carbonate spectrum. The spectra of calcite and dolomite could be characterized by the presence of a strong absorption band centered at 2.3465 μm for pure calcite and at 2.3039 μm for pure dolomite. Nine mixtures of intermediate composition were analyzed demonstrating that the position of the carbonate absorption band is semilinearly related to the calcite content of the sample. Theoretically, this model allows mapping of dolomitization from high-spectral resolution remotely sensed imagery, GER 63-channel imaging spectrometer data from southern Spain were used to attempt such a mapping. First, pixels of vegetation were removed. For the remaining pixels, the wavelength center of the carbonate absorption band was detected and converted to a category of calcite fraction. The percentage of calcite for the remaining pixels was estimated using direct indicator kriging (IK) and sequential conditional indicator simulation, assuming that the calcite content could be represented as a category variable (SCIS category variable) and as a continuous variable (SCIS continuous variable). Four realizations of an SCIS (category variable) showed that on the average, 60 percent of the data was simulated in the same class and over 90 percent of the data within one class difference. A comparison with field samples showed that IK estimates of calcite content were within 20 percent accurate. The SCIS (continuous variable) does not perform as well with differences between −45% and +26% calcite; however, simulation reproduces the spatial variability better.

Impact of DEM source and resolution on topographic seismic amplification

Abstract The impact of topographic attributes on the uneven distribution of seismic response and associated devastation has frequently been observed and documented during seismic events, but has rarely been investigated at a regional scale. Existing numerical and experimental techniques applied to explore the impact of topographic attributes in the aggravation of seismic response, have been limited to isolated and/or synthetic hills and ridges. Predicting the realistic regional impact of topographic seismic response is strongly dependent on the resolution and accuracy of regional topographic information. This study evaluates the topographic attributes and seismic parameters computed from multi-resolution and source DEMs, to investigate the impact of data source and resolution on the derived topographic seismic response. Methodologies are developed to readily derive the spatial distribution of relevant topographic attributes and seismic parameters, utilizing the multi-resolution and source DEMs. The impact of DEM source and resolution on slope gradient, relative height of terrain and shear wave velocity ( V S 30 ) are addressed. It is observed that, even though, relatively coarse resolution DEMs underestimate the critical sites of steep slope gradient and the lower V S 30 zones, this has limited impact on the derived normalized topographic aggravation factor. The free and easily accessible DEMs provide an opportunity for reasonable prediction of topographic seismic response, especially in near-real time. The slope gradient is observed to be the most sensitive topographic attribute to amplified seismic response, followed by the relative height.

Effect of Grain Size and Mineral Mixing on Carbonate Absorption Features in the SWIR and TIR Wavelength Regions

Abstract: 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

Imaging spectrometry for geological remote sensing

Without use of imaging spectrometry, imaging of the Earths surface from aircraft and from spacecraft is hampered by the low spectral resolution and limited number of spectral bands, typically less than 10 bands of 100 to 200 nm width. Imaging spectrometry in remote sensing concerns the acquisition of image data in many narrow (< 40 nm wide) contiguous spectral bands with the ultimate goal of producing detailed spectral reflectance curves for each pixel in the image. Many minerals and rocks have unique spectral signatures with characteristic absorption features that are 20 to 40 nm wide. Imaging spectrometers allow to depict these narrow features and thus map surface mineralogy based on spectral image characterization. This paper gives a review of imaging spectrometry and addresses the following topics: airborne and spaceborne systems available, spectral and geometric data pre-processing, atmospheric correction, techniques for thematic data analysis, and applications in the field of geological remote sensing. In the final section a case study is described where imaging spectrometer data is used for mapping surface mineralogy in a hydrothermal alteration system, thus guiding gold exploration.Without use of imaging spectrometry, imaging of the Earths surface from aircraft and from spacecraft is hampered by the low spectral resolution and limited number of spectral bands, typically less than 10 bands of 100 to 200 nm width. Imaging spectrometry in remote sensing concerns the acquisition of image data in many narrow (< 40 nm wide) contiguous spectral bands with the ultimate goal of producing detailed spectral reflectance curves for each pixel in the image. Many minerals and rocks have unique spectral signatures with characteristic absorption features that are 20 to 40 nm wide. Imaging spectrometers allow to depict these narrow features and thus map surface mineralogy based on spectral image characterization. This paper gives a review of imaging spectrometry and addresses the following topics: airborne and spaceborne systems available, spectral and geometric data pre-processing, atmospheric correction, techniques for thematic data analysis, and applications in the field of geological remote sensing. In the final section a case study is described where imaging spectrometer data is used for mapping surface mineralogy in a hydrothermal alteration system, thus guiding gold exploration.

Calibration of Airborne Visible/Infrared Imaging Spectrometer Data (AVIRIS) to reflectance and mineral mapping in hydrothermal alteration zones: An example from the “Cuprite mining district”

Abstract High‐spectral resolution images (AVIRIS) over the Cuprite mining area have been used to evaluate atmospheric calibration algorithms and test several mineral mapping techniques. Four normalization techniques have been applied: (1) the Flat‐Field Method, (2) the Equal Area normalization technique using the Internal Average Reflectance (IAR) Spectrum, (3) the Empirical Line Method, and (4) the Atmospheric Absorption Removal Method (ATREM) which uses a standard empirical atmosphere model. The algorithms have been evaluated in terms of their ability to remove both solar irradiance and atmospheric absorption features, noise, artifacts, and spectral interpretability. Signal‐to‐noise ratio (SNR) has been calculated as the ratio of the mean of the digital number (DN) values (reflectivity)) and the standard deviation of the DN values (noise) for pixel spectra. An empirical relation was found between SNR and number of pixel spectra averaged. Spectral interpretability was evaluated by using the difference sp...

Hyperspectral image classification by a variable interval spectral average and spectral curve matching combined algorithm

Classification of hyperspectral images has been receiving considerable attention with many new applications reported from commercial and military sectors. Hyperspectral images are composed of a large number of spectral channels, and have the potential to deliver a great deal of information about a remotely sensed scene. However, in addition to high dimensionality, hyperspectral image classification is compounded with a coarse ground pixel size of the sensor for want of adequate sensor signal to noise ratio within a fine spectral passband. This makes multiple ground features jointly occupying a single pixel. Spectral mixture analysis typically begins with pixel classification with spectral matching techniques, followed by the use of spectral unmixing algorithms for estimating endmembers abundance values in the pixel. The spectral matching techniques are analogous to supervised pattern recognition approaches, and try to estimate some similarity between spectral signatures of the pixel and reference target. In this paper, we propose a spectral matching approach by combining two schemes—variable interval spectral average (VISA) method and spectral curve matching (SCM) method. The VISA method helps to detect transient spectral features at different scales of spectral windows, while the SCM method finds a match between these features of the pixel and one of library spectra by least square fitting. Here we also compare the performance of the combined algorithm with other spectral matching techniques using a simulated and the AVIRIS hyperspectral data sets. Our results indicate that the proposed combination technique exhibits a stronger performance over the other methods in the classification of both the pure and mixed class pixels simultaneously.

Can infrared spectroscopy be used to measure change in potassium nitrate concentration as a proxy for soil particle movement

Displacement of soil particles caused by erosion influences soil condition and fertility. To date, the cesium 137 isotope (137Cs) technique is most commonly used for soil particle tracing. However when large areas are considered, the expensive soil sampling and analysis present an obstacle. Infrared spectral measurements would provide a solution, however the small concentrations of the isotope do not influence the spectral signal sufficiently. Potassium (K) has similar electrical, chemical and physical properties as Cs. Our hypothesis is that it can be used as possible replacement in soil particle tracing. Soils differing in texture were sampled for the study. Laboratory soil chemical analyses and spectral sensitivity analyses were carried out to identify the wavelength range related to K concentration. Different concentrations of K fertilizer were added to soils with varying texture properties in order to establish spectral characteristics of the absorption feature associated with the element. Changes in position of absorption feature center were observed at wavelengths between 2,450 and 2,470 nm, depending on the amount of fertilizer applied. Other absorption feature parameters (absorption band depth, width and area) were also found to change with K concentration with coefficient of determination between 0.85 and 0.99. Tracing soil particles using K fertilizer and infrared spectral response is considered suitable for soils with sandy and sandy silt texture. It is a new approach that can potentially grow to a technique for rapid monitoring of soil particle movement over large areas.

Estimating and simulating the degree of serpentinization of peridotites using hyperspectral remotely sensed imagery

The mineral products resulting from the process of serpentinization, by which primary magnesium silicate minerals in peridotites are replaced by hydrous serpentine-group minerals, are of economic importance since Alpine-type peridotites are the host rocks for virtually all large asbestos deposits, which may be attributed mainly to the serpentine-group mineral chrysotile. Conventional field mapping of the distribution of highly serpentinized areas is time consuming and requires detailed sampling and laboratory analysis. In 0.4- to 2.5-μm reflectance spectra of serpentinized peridotites, serpentinization is responsible for a decrease in contrast of olivine-pyroxene iron absorption features and an appearance and increase in OH− absorption features near 1.4 μm and 2.3 μm associated with serpentine minerals. The degree of serpentinization is positively correlated with the depth of the 1.4-μm and 2.3-μm absorption features for samples containing more than 55 weight percent serpentine minerals. Small amounts of magnetite in a sample obscure the spectral contrast and decrease the overall brightness of weakly serpentinized samples. A methodology is used for mapping serpentine minerals in ultrabasic rocks from imaging spectrometer data, which includes (1) vegetation masking, (2) calculating the absorption band depth of the 2.3-μm absorption feature in unmasked pixels, (3) translating this value into percent serpentine minerals using an empirical linear model, and (4) estimating the degree of serpentinization at the remaining locations using conditional simulation techniques or ordinary block kriging. From the results of this study, it can be concluded that mapping the degree of serpentinization from high-spectral resolution imagery is possible within marginal statistical fluctuations. Conditional simulation reproduces the spatial and statistical variability of the data set; however, it sacrifices the local accuracy. Direct estimation using ordinary kriging provides a better local estimate but does not honor the statistics and spatial dispersion of the original data.