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USGS2019

Defining the limits of spectrally based bathymetric mapping on a large river

Remote sensing has emerged as a powerful method of characterizing river systems but is subject to several important limitations. This study focused on defining the limits of spectrally based mapping in a large river. We used multibeam echosounder (MBES) surveys and hyperspectral images from a deep, clear-flowing channel to develop techniques for inferring the maximum detectable depth, d m a x "> d m a x , directly from an image and identifying optically deep areas that exceed d m a x "> d m a x . Optimal Band Ratio Analysis (OBRA) of progressively truncated subsets of the calibration data provided an estimate of d m a x "> d m a x by indicating when depth retrieval performance began to deteriorate due to the presence of depths greater than the sensor could detect. We then partitioned the calibration data into shallow and optically deep ( d > d m a x "> d > d m a x ) classes and fit a logistic regression model to estimate the probability of optically deep water, P r ( O D ) "> P r ( O D ) . Applying a P r ( O D ) "> P r ( O D ) threshold value allowed us to delineate optically deep areas and thus only attempt depth retrieval in relatively shallow locations. For the Kootenai River, d m a x "> d m a x reached as high as 9.5 m at one site, with accurate depth retrieval ( R 2 = 0.94 "> R 2 = 0.94 ) in areas with d < d m a x "> d < d m a x . As a first step toward scaling up from short reaches to long river segments, we evaluated the portability of depth-reflectance relations calibrated at one site to other sites along the river. This analysis highlighted the importance of calibration data spanning a broad range of depths. Due to the inherent limitations of passive optical depth retrieval in large rivers, a hybrid field- and remote sensing-based approach would be required to obtain complete bathymetric coverage.

Idaho↗

USGS2007

Determination of elements in National Bureau of Standards' geological reference materials SRM 278 obsidian and SRM 688 basalt by inductively coupled argon plasma-atomic emission spectrometry

Two new geologic reference materials, issued by the National Bureau of Standards as standard reference materials, have been analyzed by a precise, accurate, and rapid method of analysis for their element content. The described procedure uses a multi‐acid, low temperature digestion in a closed teflon vessel, followed by the simultaneous determination of 50 elements by inductively coupled argon plasma‐optical emission spectrometry. A preconcentration procedure was applied to a separate digestion for the accurate and precise determination of the rare earth elements. Average concentrations of 39 elements for SRM 278 obsidian and 36 elements for SRM 688 basalt are reported. The results for most elements are in good agreement with the certified values and those reported in the literature. Data for as many as 12 elements are reported for these samples for the first time.

Geostandards Newsletter↗

USGS1988

Selected annotated bibliographies for adaptive filtering of digital image data

Digital spatial filtering is an important tool both for enhancing the information content of satellite image data and for implementing cosmetic effects which make the imagery more interpretable and appealing to the eye. Spatial filtering is a context-dependent operation that alters the gray level of a pixel by computing a weighted average formed from the gray level values of other pixels in the immediate vicinity. Traditional spatial filtering involves passing a particular filter or set of filters over an entire image. This assumes that the filter parameter values are appropriate for the entire image, which in turn is based on the assumption that the statistics of the image are constant over the image. However, the statistics of an image may vary widely over the image, requiring an adaptive or "smart" filter whose parameters change as a function of the local statistical properties of the image. Then a pixel would be averaged only with more typical members of the same population. This annotated bibliography cites some of the work done in the area of adaptive filtering. The methods usually fall into two categories, (a) those that segment the image into subregions, each assumed to have stationary statistics, and use a different filter on each subregion, and (b) those that use a two-dimensional "sliding window" to continuously estimate the filter either the spatial or frequency domain, or may utilize both domains. They may be used to deal with images degraded by space variant noise, to suppress undesirable local radiometric statistics while enforcing desirable (user-defined) statistics, to treat problems where space-variant point spread functions are involved, to segment images into regions of constant value for classification, or to "tune" images in order to remove (nonstationary) variations in illumination, noise, contrast, shadows, or haze. Since adpative filtering, like nonadaptive filtering, is used in image processing to accomplish various goals, this bibliography is organized in subsections based on application areas. Contrast enhancement, edge enhancement, noise suppression, and smoothing are typically performed in order imaging process, (for example, degradations due to the optics and electronics of the sensor, or to blurring caused by the intervening atmosphere, uniform motion, or defocused optics). Some of the papers listed may apply to more than one of the above categories; when this happens the paper is listed under the category for which the paper's emphasis is greatest. A list of survey articles is also supplied. These articles are general discussions on adaptive filters and reviews of work done. Finally, a short list of miscellaneous articles are listed which were felt to be sufficiently important to be included, but do not fit into any of the above categories. This bibliography, listing items published from 1970 through 1987, is extensive, but by no means complete. It is intended as a guide for scientists and image analysts, listing references for background information as well as areas of significant development in adaptive filtering.

Open-File Report↗

USGS2012

The high-pressure electronic structure of magnesiowustite (Mg, Fe)O: applications to the physics and chemistry of the lower mantle

The electronic structure of magnesiowustite is investigated using self-consistent field X α scattered wave (SCF- X α-SW) molecular orbital calculations on (FeO 6 ) 10− and (FeMg 12 O 14 ) 2− clusters. Calculated one-electron transition energies are used to interpret the optical spectrum of (Mg, Fe)O. The results are applied to the electrical and thermal conductivity of the lower mantle. The spin pairing of Fe 2+ and the effect of pressure on bonding in magnesiowustite, with some inferences regarding the incorporation of oxygen in the outer core, is also addressed. The approach used here appears to give a reliable description of the energy and pressure dependence of the spin-allowed 5 T 2 g → 5 E g ligand field transition and the spin-pairing transition of Fe 2+ in (Mg, Fe)O. However, the oxygen to metal charge transfer transitions in (Mg, Fe)O are not as reliably determined insofar as the p - d band gap varies with cluster size and the energies of the charge transfer states cannot be found without including configurational interaction. Nevertheless, it is argued that the charge transfer transitions that are intrinsic to (Fe, Mg)O are of a sufficiently high energy to be irrelevant to the electrical and thermal conductivity of the lower mantle. This is especially true if Fe 2+ adopts the low-spin configuration. The geophysically significant properties of (Fe, Mg)O probably result from defect Fe 3+ .

Journal of Geophysical Research↗

USGS2021

Using bottom trawls to monitor subsurface water clarity in marine ecosystems

Biophysical processes that affect subsurface water clarity play a key role in ecosystem function. However, subsurface water clarity is poorly monitored in marine ecosystems because doing so requires in-situ sampling that is logistically difficult to conduct and sustain. Novel solutions are thus needed to improve monitoring of subsurface water clarity. To that end, we developed a sampling method and data processing algorithm that enable the use of bottom trawl fishing gear as a platform for conducting subsurface water clarity monitoring using trawl-mounted irradiance sensors without disruption to fishing operations. The algorithm applies quality control checks to irradiance measurements and calculates the downwelling diffuse attenuation coefficient, K d , and optical depth, ζ – apparent optical properties (AOPs) that characterize the rate of decrease in downwelling irradiance and relative irradiance transmission to depth, respectively. We applied our algorithm to irradiance measurements, obtained using bottom-trawl-mounted archival tags equipped with a photodiode collected during NOAA’s Alaska Fisheries Science Center annual summer bottom trawl surveys of the eastern Bering Sea continental shelf from 2004 to 2018. We validated our AOPs by quantitatively comparing surface-weighted K d from tags to the multi-sensor K d (490) product from the Ocean Colour Climate Change Initiative project (OC-CCI) and qualitatively evaluating whether tag K d was consistent with patterns of subsurface chlorophyll-a concentrations predicted by a coupled regional physical-biological model (Bering10K-BESTNPZ). We additionally examined patterns and trends in water clarity in the eastern Bering Sea. Key findings are: 1) water clarity decreased significantly from 2004 to 2018; 2) a recurrent, pycnocline-associated, maximum in K d occurred over much of the northwestern shelf, putatively due to a subsurface chlorophyll maximum; and 3) a turbid bottom layer (nepheloid layer) was present over a large portion of the eastern Bering Sea shelf. Our study demonstrates that bottom trawls can provide a useful platform for monitoring water clarity, especially when trawling is conducted as part of a systematic stock assessment survey.

Alaska↗

USGS2003

Continuous measurement of suspended-sediment discharge in rivers by use of optical backscatterance sensors

Optical sensors have been used to measure turbidity and suspended-sediment concentration by many marine and estuarine studies, and optical sensors can provide automated, continuous time series of suspended-sediment concentration and discharge in rivers. Three potential problems with using optical sensors are biological fouling, particle-size variability, and particle-reflectivity variability. Despite varying particle size, output from an optical backscatterance sensor in the Sacramento River at Freeport, California, USA, was calibrated successfully to discharge-weighted, cross-sectionally averaged suspended-sediment concentration, which was measured with the equal discharge-, or width-increment, methods and an isokinetic sampler. A correction for sensor drift was applied to the 3-year time series. However, the calibration of an optical backscatterance sensor used in the Colorado River at Cisco, Utah, USA, was affected by particle-size variability. The adjusted time series at Freeport was used to calculate hourly suspended-sediment discharge that compared well with daily values from a sediment station at Freeport. The appropriateness of using optical sensors in rivers should be evaluated on a site-specific basis and measurement objectives, potential particle size effects, and potential fouling should be considered.

California, Utah↗

USGS2023

Providing a framework for seagrass mapping in United States coastal ecosystems using high spatial resolution satellite imagery

Seagrasses have been widely recognized for their ecosystem services, but traditional seagrass monitoring approaches emphasizing ground and aerial observations are costly, time-consuming, and lack standardization across datasets. This study leveraged satellite imagery from Maxar's WorldView-2 and WorldView-3 high spatial resolution, commercial satellite platforms to provide a consistent classification approach for monitoring seagrass at eleven study areas across the continental United States, representing geographically, ecologically, and climatically diverse regions. A single satellite image was selected at each of the eleven study areas to correspond temporally to reference data representing seagrass coverage and was classified into four general classes: land, seagrass, no seagrass, and no data. Satellite-derived seagrass coverage was then compared to reference data using either balanced agreement, the Mann-Whitney U test, or the Kruskal-Wallis test, depending on the format of the reference data used for comparison. Balanced agreement ranged from 58% to 86%, with better agreement between reference- and satellite-indicated seagrass absence (specificity ranged from 88% to 100%) than between reference- and satellite-indicated seagrass presence (sensitivity ranged from 17% to 73%). Results of the Mann-Whitney U and Kruskal-Wallis tests demonstrated that satellite-indicated seagrass percentage cover had moderate to large correlations with reference-indicated seagrass percentage cover, indicative of moderate to strong agreement between datasets. Satellite classification performed best in areas of dense, continuous seagrass compared to areas of sparse, discontinuous seagrass and provided a suitable spatial representation of seagrass distribution within each study area. This study demonstrates that the same methods can be applied across scenes spanning varying seagrass bioregions, atmospheric conditions, and optical water types, which is a significant step toward developing a consistent, operational approach for mapping seagrass coverage at the national and global scales. Accompanying this manuscript are instructional videos describing the processing workflow, including data acquisition, data processing, and satellite image classification. These instructional videos may serve as a management tool to complement field- and aerial-based mapping efforts for monitoring seagrass ecosystems.

Alaska, California, Delaware, Florida, Maine, Mary↗

USGS2024

Physics-based satellite-derived bathymetry (SDB) using Landsat OLI images

The estimation of depth in optically shallow waters using satellite imagery can be efficient and cost-effective. Active sensors measure the distance traveled by an emitted laser pulse propagating through the water with high precision and accuracy if the bottom peak intensity of the waveform is greater than the noise level. However, passive optical imaging of optically shallow water involves measuring the radiance after the sunlight undergoes downward attenuation on the way to the sea floor, and the reflected light is then attenuated while moving back upward to the water surface. The difficulty of satellite-derived bathymetry (SDB) arises from the fact that the measured radiance is a result of a complex association of physical elements, mainly the optical properties of the water, bottom reflectance, and depth. In this research, we attempt to apply physics-based algorithms to solve this complex problem as accurately as possible to overcome the limitation of having only a few known values from a multispectral sensor. Major analysis components are atmospheric correction, the estimation of water optical properties from optically deep water, and the optimization of bottom reflectance as well as the water depth. Specular reflection of the sky radiance from the water surface is modeled in addition to the typical atmospheric correction. The physical modeling of optically dominant components such as dissolved organic matter, phytoplankton, and suspended particulates allows the inversion of water attenuation coefficients from optically deep pixels. The atmospheric correction and water attenuation results are used in the ocean optical reflectance equation to solve for the bottom reflectance and water depth. At each stage of the solution, physics-based models and a physically valid, constrained Levenberg–Marquardt numerical optimization technique are used. The physics-based algorithm is applied to Landsat Operational Land Imager (OLI) imagery over the shallow coastal zone of Guam, Key West, and Puerto Rico. The SDB depths are compared to airborne lidar depths, and the root mean squared error (RMSE) is mostly less than 2 m over water as deep as 30 m. As the initial choice of bottom reflectance is critical, along with the bottom reflectance library, we describe a pure bottom unmixing method based on eigenvector analysis to estimate unknown site-specific bottom reflectance.

Remote Sensing↗

USGS2021

A review of spatially resolved techniques and applications of organic petrography in shale petroleum systems

This review examines new techniques and applications of organic petrography in source-rock reservoir petroleum systems that have occurred along with development of the global ‘shale revolution’ in energy resources. The review is limited to techniques and instrumentation that provide spatially resolved information, typically at or below microscales, for dispersed organic matter occurring in situ in samples of shale and mudrock. A brief summary of ion beam sample preparation is followed by discussion of the most common analytical techniques and applications. Advantages and limitations of each technique, including requisite sample preparation, types of information generated [e.g., molecular or elemental (isotopic) abundance], sensitivity, and resolution are discussed. In a few cases, techniques not yet applied to organic petrology of shale or mudrock are described (e.g., X-ray photoelectron spectroscopy imaging), in anticipation of near-term future application. The most common in situ techniques applied for characterization of organic matter in shale and mudrock include optical (including fluorescence) and electron microscopies, Raman, fluorescence, and infrared spectroscopies, and surficial measurements via force microscopy. Techniques that show growing application to organic petrography of shale include tip-enhanced photothermal infrared spectroscopy, mass spectrometry imaging, and synchrotron-based spectroscopies, among others. It is anticipated that the future of dispersed organic matter petrography will hold continued development of integrated instrument techniques (e.g., simultaneous or sequential correlative microscopies and/or spectroscopies of the same location), increased instrumental resolution, increased use of multiscale and multimodal organic petrography investigations, and three-dimensional imaging and chemical speciation mapping applications via multiple analytical approaches.

International Journal of Coal Geology↗

USGS2003

Optical dating of tufa via in situ aeolian sand grains: A case example from the Southern High Plains, USA

Precipitated carbonates (commonly termed tufas or travertines) maybe of considerable utility for palaeoenvironmental reconstruction. Their potential, however, for such reconstruction is commonly limited by difficulties associated with their absolute age control. Attempts to date such deposits via uranium series techniques have been complicated by their chemically open behaviour. Here we describe an alternative approach to date tufa deposits associated with ephemeral saline lake basins from the Southern High Plains, USA. We have optically dated sand grains of a mixed aeolian/fluvial (spring fed) origin as the integrating dosimeter. We assume that the grains are fully resetting prior to their incorporation into the tufa deposits and employ a time-dependent disequilibrium dosimetric model to account for the build-up of uranium series daughter products. The approach was applied to a set of four samples with known stratigraphic association. We obtained stratigraphically sensible optical ages ranging from 78??8 to 56??4ka. These data are consistent with existing palaeoenvironmental models of regional recharge. ?? 2003 Elsevier Science Ltd. All rights reserved.

Conference Paper↗

USGS2007

Loess sedimentation in Tibet: provenance, processes, and link with Quaternary glaciations

Well-preserved loess deposits are found on the foothills of mountains along the middle reaches of the Yarlung Zangbo River in southern Tibet. Optically stimulated luminescence (OSL) dating is used to determine loess ages by applying the single-aliquot regeneration technique. Geochemical, mineralogical, and granulometric measurements were carried out to allow a comparison between loess from Tibet and the Chinese Loess Plateau. Our results demonstrate that (i) the loess deposits have a basal age of 13-11 ka, suggesting they accumulated after the last deglaciation, (ii) loess in southern Tibet has a "glacial" origin, resulting from eolian sorting of glaciofluvial outwash deposits from braided river channels or alluvial fans by local near-surface winds, and (iii) the present loess in the interior of Tibet has accumulated since the last deglaciation when increased monsoonal circulation provided an increased vegetation cover that was sufficient for trapping eolian silt. The lack of full-glacial loess is either due to minimal vegetation cover or possibly due to the erosion of loess as glaciofluvial outwash during the beginning of each interglacial. Such processes would have been repeated during each glacial-interglacial cycle of the Quaternary. ?? 2007 Elsevier Ltd. All rights reserved.

Quaternary Science Reviews↗

USGS2018

LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models

Metabolism is a fundamental process in ecosystems that crosses multiple scales of organization from individual organisms to whole ecosystems. To improve sharing and reuse of published metabolism models, we developed LakeMetabolizer, an R package for estimating lake metabolism from in situ time series of dissolved oxygen, water temperature, and, optionally, additional environmental variables. LakeMetabolizer implements 5 different metabolism models with diverse statistical underpinnings: bookkeeping, ordinary least squares, maximum likelihood, Kalman filter, and Bayesian. Each of these 5 metabolism models can be combined with 1 of 7 models for computing the coefficient of gas exchange across the air–water interface ( k ). LakeMetabolizer also features a variety of supporting functions that compute conversions and implement calculations commonly applied to raw data prior to estimating metabolism (e.g., oxygen saturation and optical conversion models). These tools have been organized into an R package that contains example data, example use-cases, and function documentation. The release package version is available on the Comprehensive R Archive Network (CRAN), and the full open-source GPL-licensed code is freely available for examination and extension online. With this unified, open-source, and freely available package, we hope to improve access and facilitate the application of metabolism in studies and management of lentic ecosystems.

Inland Waters↗

USGS2009

Satellite optical and radar data used to track wetland forest impact and short-term recovery from Hurricane Katrina

Satellite Landsat Thematic Mapper (TM) and RADARSAT-1 (radar) satellite image data collected before and after the landfall of Hurricane Katrina in the Pearl River Wildlife Management Area on the Louisiana-Mississippi border, USA, were applied to the study of forested wetland impact and recovery. We documented the overall similarity in the radar and optical satellite mapping of impact and recovery patterns and highlighted some unique differences that could be used to provide consistent and relevant ecological monitoring. Satellite optical data transformed to a canopy foliage index (CFI) indicated a dramatic decrease in canopy cover immediately after the storm, which then recovered rapidly in the Taxodium distichum (baldcypress) and Nyssa aquatica (water tupelo) forest. Although CFI levels in early October indicated rapid foliage recovery, the abnormally high radar responses associated with the cypress forest suggested a persistent poststorm difference in canopy structure. Impact and recovery mapping results showed that even though cypress forests experienced very high wind speeds, damage was largely limited to foliage loss. Bottomland hardwoods, experiencing progressively lower wind speeds further inland, suffered impacts ranging from increased occurrences of downed trees in the south to partial foliage loss in the north. In addition, bottomland hardwood impact and recovery patterns suggested that impact severity was associated with a difference in stand structure possibly related to environmental conditions that were not revealed in the prehurricane 25-m optical and radar image analyses.

Wetlands↗

USGS2004

Biogeochemical transformation of Fe minerals in a petroleum-contaminated aquifer

The Bemidji aquifer in Minnesota, USA is a well-studied site of subsurface petroleum contamination. The site contains an anoxic groundwater plume where soluble petroleum constituents serve as an energy source for a region of methanogenesis near the source and bacterial Fe(III) reduction further down gradient. Methanogenesis apparently begins when bioavailable Fe(III) is exhausted within the sediment. Past studies indicate that Geobacter species and Geothrix fermentens -like organisms are the primary dissimilatory Fe-reducing bacteria at this site. The Fe mineralogy of the pristine aquifer sediments and samples from the methanogenic (source) and Fe(III) reducing zones were characterized in this study to identify microbiologic changes to Fe valence and mineral distribution, and to identify whether new biogenic mineral phases had formed. Methods applied included X-ray diffraction; X-ray fluorescence (XRF); and chemical extraction; optical, transmission, and scanning electron microscopy; and Mössbauer spectroscopy. All of the sediments were low in total Fe content (≈ 1%) and exhibited complex Fe-mineralogy. The bulk pristine sediment and its sand, silt, and clay-sized fractions were studied in detail. The pristine sediments contained Fe(II) and Fe(III) mineral phases. Ferrous iron represented approximately 50% of Fe TOT . The relative Fe(II) concentration increased in the sand fraction, and its primary mineralogic residence was clinochlore with minor concentrations found as a ferroan calcite grain cement in carbonate lithic fragments. Fe(III) existed in silicates (epidote, clinochlore, muscovite) and Fe(III) oxides of detrital and authigenic origin. The detrital Fe(III) oxides included hematite and goethite in the form of mm-sized nodular concretions and smaller-sized dispersed crystallites, and euhedral magnetite grains. Authigenic Fe(III) oxides increased in concentration with decreasing particle size through the silt and clay fraction. Chemical extraction and Mössbauer analysis indicated that this was a ferrihydrite like-phase. Quantitative mineralogic and Fe(II/III) ratio comparisons between the pristine and contaminated sediments were not possible because of textural differences. However, comparisons between the texturally-similar source (where bioavailable Fe(III) had been exhausted) and Fe(III) reducing zone sediments (where bioavailable Fe(III) remained) indicated that dispersed detrital, crystalline Fe(III) oxides and a portion of the authigenic, poorly crystalline Fe(III) oxide fraction had been depleted from the source zone sediment by microbiologic activity. Little or no effect of microbiologic activity was observed on silicate Fe(III). The presence of residual “ferrihydrite” in the most bioreduced, anoxic plume sediment (source) implied that a portion of the authigenic Fe(III) oxides were biologically inaccessible in weathered, lithic fragment interiors. Little evidence was found for the modern biogenesis of authigenic ferrous-containing mineral phases, perhaps with the exception of thin siderite or ferroan calcite surface precipitates on carbonate lithic fragments within source zone sediments.

Geochimica et Cosmochimica Acta↗

USGS2016

Toward a quantitative and empirical dissolved organic carbon budget for the Gulf of Maine, a semienclosed shelf sea

A time series of organic carbon export from Gulf of Maine (GoM) watersheds was compared to a time series of biological, chemical, bio-optical, and hydrographic properties, measured across the GoM between Yarmouth, NS, Canada, and Portland, ME, U.S. Optical proxies were used to quantify the dissolved organic carbon (DOC) and particulate organic carbon in the GoM. The Load Estimator regression model applied to river discharge data demonstrated that riverine DOC export (and its decadal variance) has increased over the last 80 years. Several extraordinarily wet years (2006–2010) resulted in a massive pulse of chromophoric dissolved organic matter (CDOM; proxy for DOC) into the western GoM along with unidentified optically scattering material (<0.2 μm diameter). A survey of DOC in the GoM and Scotian Shelf showed the strong influence of the Gulf of Saint Lawrence on the DOC that enters the GoM. A deep plume of CDOM-rich water was observed near the coast of Maine which decreased in concentration eastward. The Forel-Ule color scale was derived and compared to the same measurements made in 1912–1913 by Henry Bigelow. Results show that the GoM has yellowed in the last century, particularly in the region of the extension of the Eastern Maine Coastal Current. Time lags between DOC discharge and its appearance in the GoM increased with distance from the river mouths. Algae were also a significant source of DOC but not CDOM. Gulf-wide algal primary production has decreased. Increases in precipitation and DOC discharge to the GoM are predicted over the next century.

Gulf of Maine↗

USGS2020

Pacific Continental Shelf Environmental Assessment (PaCSEA): Characterization of Seasonal Water Masses within the Northern California Current System Using Airborne Remote Sensing off Northern California, Oregon, and Washington, 2011–2012

Here, we use ocean color measurements (Figure 1) and sea surface temperature (SST) data collected using sensors mounted on low-flying aircraft to characterize NCCS water masses and identify patterns among seasons and between years. To accomplish this, we applied k-means clustering to measured and derived ecologically-relevant physical and bio-optical variables (SST, Chla, absorbance by colored dissolved organic matter [aCDOM], proxy particle load). These classifications will be used in the future to evaluate species habitat distributions in the NCCS.

California, Oregon, Washington↗

USGS2010

Active remote sensing of snow using NMM3D/DMRT and comparison with CLPX II airborne data

We applied the Numerical Maxwell Model of three-dimensional simulations (NMM3D) in the Dense Media Radiative Theory (DMRT) to calculate backscattering coefficients. The particles' positions are computer-generated and the subsequent Foldy-Lax equations solved numerically. The phase matrix in NMM3D has significant cross-polarization, particularly when the particles are densely packed. The NMM3D model is combined with DMRT in calculating the microwave scattering by dry snow. The NMM3D/DMRT equations are solved by an iterative solution up to the second order in the case of small to moderate optical thickness. The numerical results of NMM3D/DMRT are illustrated and compared with QCA/DMRT. The QCA/DMRT and NMM3D/DMRT results are also applied to compare with data from two specific datasets from the second Cold Land Processes Experiment (CLPX II) in Alaska and Colorado. The data are obtained at the Ku-band (13.95 GHz) observations using airborne imaging polarimetric scatterometer (POLSCAT). It is shown that the model predictions agree with the field measurements for both co-polarization and cross-polarization. For the Alaska region, the average snow depth and snow density are used as the inputs for DMRT. The grain size, selected from within the range of the ground measurements, is used as a best-fit parameter within the range. For the Colorado region, we use the Variable Infiltration Capacity Model (VIC) to obtain the input snow profiles for NMM3D/DMRT. ?? 2010 IEEE.

IEEE Journal of Selected Topics in Applied Earth O↗

USGS2024

Structure and morphology of chars and activated carbons obtained from thermal treatment of coal and biomass origin materials, including their wastes: Results from the ICCP Microscopy of Carbon Materials Working Group

This paper describes the evaluation of petrographic textures in char and activated carbon derived from coal, coal by-products and biomass, formed during carbonization and activation processes. This work represents the results of interlaboratory exercises from 2016 to 2022 of the Microscopy of Carbon Materials Working Group in Commission III of the International Committee for Coal and Organic Petrology. The interlaboratory exercises were run on photomicrograph samples. For textural characterization of carbon materials, the existing American Society for Testing and Materials (ASTM) classification system for metallurgical coke was applied. Morphological differences were evaluated in 29 carbon material types, including 22 char samples, and 7 activated carbon (AC) samples obtained experimentally using conventional direct/indirect and microwave heating technologies. This approach gives an extended view on the identification of microporous carbons, and how a certain heat treatment develops a certain optical texture and structure in a raw material. The requested evaluation of carbon materials was related to their porosity, origin, extent, and characteristics, which are particular to each carbon material type. Because carbon matrices can form a wide range of optical textures during heat treatment it is important to demonstrate which carbon occurrences will have a crucial role in industrial applications dominated by adsorption phenomena. The interlaboratory exercises included 17 participants from 14 laboratories. Four sets of digital black and white and colour photomicrographs were distributed, which in total comprised 184 fields of different types of carbon material. The results were evaluated based on four levels: (i) optical texture (isotropic/anisotropic), (ii) optical type and size (punctiform, mosaic, fiber, ribbon, domain), iii) morphology (porous, non-porous/massive), and (iv) particle origin (precursor type). The statistical method applied to evaluate the results was based on “raw agreement indices”. Comparative analyses of the average values of the level of overall agreement showed homogeneity in the results, the mean value was 89%, with a minimum value of 87% and a maximum value of 91% for those who participated in at least three out of four exercises.

International Journal of Coal Geology↗