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USGS2006

In situ study of mass transfer in aqueous solutions under high pressures via Raman spectroscopy: A new method for the determination of diffusion coefficients of methane in water near hydrate formation conditions

A new method was developed for in situ study of the diffusive transfer of methane in aqueous solution under high pressures near hydrate formation conditions within an optical capillary cell. Time-dependent Raman spectra of the solution at several different spots along the one-dimensional diffusion path were collected and thus the varying composition profile of the solution was monitored. Diffusion coefficients were estimated by the least squares method based on the variations in methane concentration data in space and time in the cell. The measured diffusion coefficients of methane in water at the liquid (L)-vapor (V) stable region and L-V metastable region are close to previously reported values determined at lower pressure and similar temperature. This in situ monitoring method was demonstrated to be suitable for the study of mass transfer in aqueous solution under high pressure and at various temperature conditions and will be applied to the study of nucleation and dissolution kinetics of methane hydrate in a hydrate-water system where the interaction of methane and water would be more complicated than that presented here for the L-V metastable condition. ?? 2006 Society for Applied Spectroscopy.

Applied Spectroscopy↗

USGS2025

Earthquake magnitude and source parameter estimation with a distributed acoustic sensing dataset in the Gorda subduction zone

Distributed acoustic sensing (DAS) systems offer a cost‐effective way to create large‐scale strainmeter arrays for seismological applications using fiber‐optic cables. DAS‐based strain measurements are known to be influenced by various factors, bringing into question their general reliability for accurate earthquake characterization. A 15‐km‐long DAS deployment in northern California was operational within 3 days of the 2022 M w 6.4 Ferndale earthquake and ran continuously throughout the aftershock sequence. We utilize these aftershock data to validate DAS‐based strain measurements in two ways. We first test the accuracy of DAS‐based magnitude estimates from peak dynamic strains by comparing them with magnitude and attenuation scaling relations derived independently from traditional borehole strainmeter (BSM) data. We demonstrate that DAS‐based magnitudes are comparable to BSM‐based magnitudes when corrections for variations in site response along the fiber‐optic cable are properly made. Magnitude errors are spatially correlated, potentially because of factors such as finite‐fault effects (e.g., stress drop) or more complex, unmodeled path attenuation or because of wave propagation effects in heterogeneous media. We then apply more advanced source characterization methodology to the DAS data using a time‐domain empirical Green’s function (EGF) deconvolution approach to measure details of the moment rate history. The EGF approach using DAS data depends on careful treatment of distorting factors such as anthropogenic sources of noise and optical phase wrapping but successfully isolates source spectra for moderate‐magnitude earthquakes: source spectral ratios obtained from DAS data, broadband seismometer data, and BSM data in the same region show consistent results, revealing differences in directivity and spectral shape among earthquakes. Although further research is needed to refine source‐time‐function estimation techniques for DAS data, particularly for larger magnitude events, these case studies demonstrate the clear potential of DAS for earthquake source characterization.

California↗

USGS2004

Structural and spectral features of selenium nanospheres produced by Se-respiring bacteria

Certain anaerobic bacteria respire toxic selenium oxyanions and in doing so produce extracellular accumulations of elemental selenium [Se(0)]. We examined three physiologically and phylogenetically diverse species of selenate- and selenite-respiring bacteria, Sulfurospirillum barnesii, Bacillus selenitireducens, and Selenihalanaerobacter shriftii, for the occurrence of this phenomenon. When grown with selenium oxyanions as the electron acceptor, all of these organisms formed extracellular granules consisting of stable, uniform nanospheres (diameter, ???300 nm) of Se(0) having monoclinic crystalline structures. Intracellular packets of Se(0) were also noted. The number of intracellular Se(0) packets could be reduced by first growing cells with nitrate as the electron acceptor and then adding selenite ions to washed suspensions of the nitrate-grown cells. This resulted in the formation of primarily extracellular Se nanospheres. After harvesting and cleansing of cellular debris, we observed large differences in the optical properties (UV-visible absorption and Raman spectra) of purified extracellular nanospheres produced in this manner by the three different bacterial species. The spectral properties in turn differed substantially from those of amorphous Se(0) formed by chemical oxidation of H2Se and of black, vitreous Se(0) formed chemically by reduction of selenite with ascorbate. The microbial synthesis of Se(0) nanospheres results in unique, complex, compacted nanostructural arrangements of Se atoms. These arrangements probably reflect a diversity of enzymes involved in the dissimilatory reduction that are subtly different in different microbes. Remarkably, these conditions cannot be achieved by current methods of chemical synthesis.

Applied and Environmental Microbiology↗

USGS1998

Salts on Europa's surface detected by Galileo's near infrared mapping spectrometer

Reflectance spectra in the 1- to 2.5-micrometer wavelength region of the surface of Europa obtained by Galileo's Near Infrared Mapping Spectrometer exhibit distorted water absorption bands that indicate the presence of hydrated minerals. The laboratory spectra of hydrated salt minerals such as magnesium sulfates and sodium carbonates and mixtures of these minerals provide a close match to the Europa spectra. The distorted bands are only observed in the optically darker areas of Europa, including the lineaments, and may represent evaporite deposits formed by water, rich in dissolved salts, reaching the surface from a water-rich layer underlying an ice crust.

Science↗

USGS2020

Organic matter integration, overprinting, and the relative fraction of optically active organic carbon in a human-impacted watershed

Rivers continually integrate terrestrial organic matter (OM) into their waters, in a process that transfers 1.9 Pg C yr –1 as the primary linkage between oceanic and terrestrial carbon cycles. Yet rivers are not simple, conservative OM integrators. Patchy local land uses (wetlands, bogs, agriculture) release OM that can disproportionately alter river biogeochemistry and overprint upstream carbon. These releases are quantifiable at the plot scale but remain unpredictable across river reaches and watersheds, critically inhibiting our ability to scale up terrestrial-aquatic linkages to regional/global carbon cycling models. We evaluated OM overprinting distance along a human-influenced watershed to quantify river integration of terrestrial OM and to bridge the quantification gap between habitats and waterway biogeochemistry. We investigated changes in dissolved organic carbon (DOC) concentration and dissolved organic matter (DOM) composition (lignin phenols, fluorescence excitation-emission spectra using parallel factor analysis [PARAFAC], and the relative fraction of optically active DOM [EEM DOC ]). DOC concentrations increased continually ( p < 0.001) downstream, from median 1.0 mg L –1 at 30 km (headwaters) to 3.3 mg L –1 at the river mouth. This rate of increase corresponded to a DOC overprinting distance—the longitudinal distance over which DOC concentrations double—of 13 km. Mainstem DOC overprinting distance ranged from 8 km (winter, rainy season) to 21 km (summer, dry season with irrigation), highlighting stronger overprinting during increased hydraulic connectivity. Stronger overprinting also correlated to higher EEM DOC ( p < 0.001). Overprinting distance effectively quantifies river integration of DOM along the terrestrial-aquatic interface, helping to refine bottom-up carbon cycle estimates, inform upscaling of site-specific fluxes, and to track land use and climate influence on river biogeochemistry.

California↗

USGS1987

Molecular orbital (SCF-Xα-SW) theory of metal-metal charge transfer processes in minerals

A number of mixed valence iron oxides and silicates (e.g., magnetite, ilvaite) exhibit thermally induced electron delocalization between adjacent Fe 2+ and Fe 3+ ions and optically induced electronic transitions which are assigned to Fe 2+ →Fe 3+ intervalence charge transfer. In this paper, the mechanism of electron delocalization (i.e., polarons versus itinerant electrons) and the nature of optically induced intervalence charge-transfer in minerals are investigated using molecular orbital theory. SCF-Xα-SW molecular orbital calculations were done for several mixed-valence (Fe 2 O 10 ) 15− clusters corresponding to edgesharing Fe 2+ and Fe 3+ coordination polyhedra. A spinunrestricted formalism was used so that the effect of ferromagnetic versus antiferromagnetic coupling of adjacent Fe 2+ and Fe 3+ cations could be determined. The molecular orbital results can be related to the polaron theory of solid state physics and the perturbation theory formalism used by Robin and Day (1967) and others to describe electron transfer in mixed valence compounds. Intervalence charge-transfer results from the overlap of Fe(3d) orbitals across the shared edges of adjacent FeO 6 polyhedra to give weak Fe-Fe bonds. Electron delocalization, however, requires that adjacent Fe cations be ferromagnetically coupled. Antiferromagnetic coupling results in distinguishable Fe 2+ and Fe 3+ cations. Electronic transitions between the Fe-Fe bonding and Fe-Fe antibonding orbitals results in the optically-induced intervalence charge transfer bands observed in the electronic spectra of mixed valence minerals. Such transitions are predicted to be polarized along the metal-metal bond direction, in agreement with experimental observations.

Physics and Chemistry of Minerals↗

USGS2014

Spectral masking of goethite in abandoned mine drainage systems: implications for Mars

Remote sensing studies of the surface of Mars use visible- to near-infrared (VNIR) spectroscopy to identify hydrated and hydroxylated minerals, which can be used to constrain past environmental conditions on the surface of Mars. However, due to differences in optical properties, some hydrated phases can mask others in VNIR spectra, complicating environmental interpretations. Here, we examine the role of masking in VNIR spectra of natural precipitates of ferrihydrite, schwertmannite, and goethite from abandoned mine drainage (AMD) systems in southeastern Pennsylvania. Mixtures of ferrihydrite, schwertmannite, and goethite were identified in four AMD sites by using X-ray diffractometry (XRD), and their XRD patterns compared to their VNIR spectra. We find that both ferrihydrite and schwertmannite can mask goethite in VNIR spectra of natural AMD precipitates. These findings suggest that care should be taken in interpreting environments on Mars where ferrihydrite, schwertmannite, or goethite are found, as the former two may be masking the latter. Additionally, our findings suggest that outcrops on Mars with both goethite and ferrihydrite/schwertmannite VNIR signatures may have high relative abundances of goethite, or the goethite may exist in a coarsely crystalline phase.

Pennsylvania↗

USGS2008

Characterizing the marsh dieback spectral response at the plant and canopy level with hyperspectral and temporal remote sensing data

We describe newly developed remote sensing tools to map the localized occurrences and regional distribution of the marsh dieback in coastal Louisiana (Fig. 1). As a final goal of our research and development, we identified what spectral features accompanied the onset of dieback and could be directly linked to the optical signal measured at the satellite. In order to accomplish our research goal, we carried out two interlinked objectives. First, we determined the spectral features within the hyperspectral spectra of the impacted plant that could be linked to the spectral return. This was accomplished by measuring the differences in leaf optical properties of impacted and non impacted marsh plants in such a way that the measured differences could be linked to the dieback onset and progression. The spectral analyses were constrained to selected wavelengths (bands of reflectance data) historically associated with changes in leaf composition and structure caused by changes in the plant biophysical environment. Second, we determined what changes in the canopy reflectance (canopy signal sensed at the satellite) could be linked to dieback onset and progression. Third, we transformed a suite of six Landsat Thematic Mapper images collected before, during, and in the final stages of dieback to maps of dieback occurrences. ??2008 IEEE.

Conference Paper↗

USGS2004

Remote sensing and the optical properties of the narrow cylindrical leaves of Juncus roemerianus

To develop a more complete foundation for remote sensing of the marsh grass Juncus roemerianus, we measured the optical properties of its cylindrical leaves at sites of different canopy height, biomass composition and amount, and connectivity to ocean flushing. To measure the leaf optical properties, we adapted a technique used for conifer needles. After establishing the reliability and limits of the adapted technique to the wider J.roemerianus leaves, mean transmittance and reflectance spectra were compared to associated leaf diameters from two dates in 1999 and 2002 and at each site. Transmittance was inversely related to leaf diameter. Mean transmittance and reflectance generated from reoccupation of many field sites in 2002 indicated little or no difference in transmittance between years, a slight reflectance difference in the visible (<2%) and a slightly higher reflectance difference in the near infrared (NIR) (<4%). Site comparison indicated limited ability to separate leaf transmittance but not reflectance by marsh type (e.g., low, medium, high) or biomass. Excluding one outlier, we found leaf transmittances could be adequately represented as 1% ?? 0.2% in the visible and 9% ?? 1% in the NIR and leaf reflectances represented from 14% to 16% in the visible and 71% to 75% in the NIR (the reflectance ranges represent 1999 and 2002 means). Reflectance and transmittance spectra associated with the dead J. roemerianus leaves displayed a spectrally flat increase from the visible to the NIR wavelengths. In total, we documented the atypical optical properties of the cylindrical J. roemerianus leaves and showed that to a first approximation, single means could represent leaf transmittance and visible leaf reflectance across all marsh zones and, after accounting for sample standardization, possibly the NIR reflectance as well.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2022

Spectral mixture analysis for surveillance of harmful algal blooms (SMASH): A field-, laboratory-, and satellite-based approach to identifying cyanobacteria genera from remotely sensed data

Algal blooms around the world are increasing in frequency and severity, often with the possibility of adverse effects on human and ecosystem health. The health and economic impacts associated with harmful algal blooms, or HABs, provide compelling rationale for developing new methods for monitoring these events via remote sensing. Although concentrations of chlorophyll- a and key pigments like phycocyanin are routinely estimated from satellite images and used to infer algal or cyanobacterial cell counts, current methods are unable to provide information on the taxonomic composition of a bloom. This study introduced a new approach capable of differentiating among genera based on their reflectance characteristics: Spectral Mixture Analysis for Surveillance of HABs, or SMASH. The foundation of SMASH is a multiple endmember spectral mixture analysis (MESMA) algorithm that takes a library of cyanobacteria endmembers and a hyperspectral image as input and estimates the fractional abundance of each genus, plus water, on a per-pixel basis. Importantly, we assume that the water column consists of only pure water and cyanobacteria, implying that our linear spectral unmixing models do not account for other optically active constituents such as suspended sediment and colored dissolved organic matter (CDOM). We used reflectance spectra for 12 genera measured under a microscope to populate an algal spectral library and applied the SMASH workflow to satellite images from four waterbodies across the United States. Normalized spectral separability scores indicated that the 12 genera were distinct from one another and the MESMA algorithm reproduced known input fractions for simulated mixtures that included all pairwise combinations of genera and water. We used Upper Klamath Lake as an example to illustrate data products generated via SMASH: maps of the normalized difference chlorophyll index and cyanobacterial index, a MESMA-based classification of algal genera, fraction images for each endmember, and a root mean square error (RMSE) image that summarizes uncertainty. For Upper Klamath Lake, these outputs highlighted a complex algal bloom featuring several genera, primarily Aphanizomenon , and intricate spatial patterns associated with gyres. The maximum RMSE constraint imposed on the MESMA algorithm provided a means of avoiding false positive detection of genera not present in a waterbody but must not be set so low as to leave much of an image unclassified in cases where genera included in the library are present. Comparison of endmember fractions with relative biovolumes calculated from field samples indicated that taxonomic information from SMASH was consistent with field observations. For example, the algorithm successfully identified Microcystis in Owasco Lake but avoided misclassifying Asterionella , a genus not yet included in our library, in Detroit Lake. This proof-of-concept investigation demonstrates the potential of SMASH to enhance our understanding of algal blooms, particularly with respect to their spatial and temporal dynamics.

New York, Oregon, Texas↗

USGS2005

The evolution of Titan's mid-latitude clouds

Spectra from Cassini's Visual and Infrared Mapping Spectrometer reveal that the horizontal structure, height, and optical depth of Titan's clouds are highly, dynamic. Vigorous cloud centers are seen to rise from the middle to the upper troposphere within 30 minutes and dissipate within the next hour. Their development indicates that Titan's clouds evolve convectively; dissipate through rain; and, over the next several hours, waft downwind to achieve their great longitude extents. These and other characteristics suggest that temperate clouds originate from circulation-induced convergence, in addition to a forcing at the surface associated with Saturn's tides, geology, and/or surface composition.

Science↗

USGS2016

Spectrally based mapping of riverbed composition

Remote sensing methods provide an efficient means of characterizing fluvial systems. This study evaluated the potential to map riverbed composition based on in situ and/or remote measurements of reflectance. Field spectra and substrate photos from the Snake River, Wyoming, USA, were used to identify different sediment facies and degrees of algal development and to quantify their optical characteristics. We hypothesized that accounting for the effects of depth and water column attenuation to isolate the reflectance of the streambed would enhance distinctions among bottom types and facilitate substrate classification. A bottom reflectance retrieval algorithm adapted from coastal research yielded realistic spectra for the 450 to 700 nm range; but bottom reflectance-based substrate classifications, generated using a random forest technique, were no more accurate than classifications derived from above-water field spectra. Additional hypothesis testing indicated that a combination of reflectance magnitude (brightness) and indices of spectral shape provided the most accurate riverbed classifications. Convolving field spectra to the response functions of a multispectral satellite and a hyperspectral imaging system did not reduce classification accuracies, implying that high spectral resolution was not essential. Supervised classifications of algal density produced from hyperspectral data and an inferred bottom reflectance image were not highly accurate, but unsupervised classification of the bottom reflectance image revealed distinct spectrally based clusters, suggesting that such an image could provide additional river information. We attribute the failure of bottom reflectance retrieval to yield more reliable substrate maps to a latent correlation between depth and bottom type. Accounting for the effects of depth might have eliminated a key distinction among substrates and thus reduced discriminatory power. Although further, more systematic study across a broader range of fluvial environments is needed to substantiate our initial results, this case study suggests that bed composition in shallow, clear-flowing rivers potentially could be mapped remotely.

Geomorphology↗

USGS2010

Determining sources of dissolved organic carbon and disinfection byproduct precursors to the McKenzie River, Oregon

This study was conducted to determine the main sources of dissolved organic carbon (DOC) and disinfection byproduct (DBP) precursors to the McKenzie River, Oregon (USA). Water samples collected from the mainstem, tributaries, and reservoir outflows were analyzed for DOC concentration and DBP formation potentials (trihalomethanes [THMFPs] and haloacetic acids [HAAFPs]). In addition, optical properties (absorbance and fluorescence) of dissolved organic matter (DOM) were measured to provide insight into DOM composition and assess whether optical properties are useful proxies for DOC and DBP precursor concentrations. Optical properties indicative of composition suggest that DOM in the McKenzie River mainstem was primarily allochthonous - derived from soils and plant material in the upstream watershed. Downstream tributaries had higher DOC concentrations than mainstem sites (1.6 ?? 0.4 vs. 0.7 ?? 0.3 mg L-1) but comprised <5% of mainstem flows and had minimal effect on overall DBP precursor loads. Water exiting two large upstream reservoirs also had higher DOC concentrations than the mainstem site upstream of the reservoirs, but optical data did not support in situ algal production as a source of the added DOC during the study. Results suggest that the first major rain event in the fall contributes DOM with high DBP precursor content. Although there was interference in the absorbance spectra in downstream tributary samples, fluorescence data were strongly correlated to DOC concentration (R 2 = 0.98), THMFP (R2 = 0.98), and HAAFP (R2 = 0.96). These results highlight the value of using optical measurements for identifying the concentration and sources of DBP precursors in watersheds, which will help drinking water utilities improve source water monitoring and management programs. Copyright ?? 2010 by the American Society of Agronomy.

Journal of Environmental Quality↗

USGS1995

Relative performance of several inexpensive accelerometers

We examined the performance of several low-cost accelerometers for highly cost-driven applications in recording earthquake strong motion. We anticipate applications for such sensors in providing the lifeline and emergency-response communities with an immediate, comprehensive picture of the extent and characteristics of likely damage. We also foresee their use as 'filler' instruments sited between research-grade instruments to provide spatially detailed and near-field records of large earthquakes (on the order of 1000 stations at 600-m intervals in San Fernando Valley, population 1.2 million, for example). The latter applications would provide greatly improved attenuation relationships for building codes and design, the first examples of mainshock information (that is, potentially nonlinear regime) for microzonation, and a suite of records for structural engineers. We also foresee possible applications in monitoring structural inter-story drift during earthquakes, possibly leading to local and remote alarm functions as well as design criteria. This effort appears to be the first of its type at the USGS. It is spurred by rapid advances in sensor technology and the recognition of potential non-classical applications. In this report, we estimate sensor noise spectra, relative transfer functions and cross-axis sensitivity of six inexpensive sensors. We tested three micromachined ('silicon-chip') sensors in addition to classical force-balance and piezoelectric examples. This sample of devices is meant to be representative, not comprehensive. Sensor noise spectra were estimated by recording system output with the sensor mounted on a pneumatically supported 545-kg optical-bench isolation table. This isolation table appears to limit ground motion to below our system noise level. These noise estimates include noise introduced by signal-conditioning circuitry, the analog-to-digital converter (ADC), and noise induced in connecting wiring by ambient electromagnetic fields in our suburban laboratory. These latter sources are believed to dominate sensor noise in the quieter sensors we tested. Transfer functions were obtained relative to a research grade force-balance accelerometer (a Kinemetrics TM FBA-11) by shaking the sensors simultaneously on the same shake table and taking spectral ratios with the output of the FBA- 11. This reference sensor is said to have 120 db dynamic range (-+20 bits, though we only digitized it at 16 bits resolution and drove it with relatively small signals). We did not test temperature sensitivity, which is thought to be a significant issue at least for the silicon devices. Though these tests were not designed to be definitive (our anticipated applications do not demand research-grade precision), our tests do appear to have been successful in estimating relative transfer functions from about 0.3 to 50 Hz. Most sensors performed adequately in this range, with essentially fiat relative transfer functions. Noise tests appear to measure sensor noise well for the noisier (generally less expensive) instruments from about 0.1 to 50 Hz.

Open-File Report↗

USGS2007

A whole image approach using field measurements for transforming EO1 Hyperion hyperspectral data into canopy reflectance spectra

To maximize the spectral distinctiveness (information) of the canopy reflectance, an atmospheric correction strategy was implemented to provide accurate estimates of the intrinsic reflectance from the Earth Observing 1 (EO1) satellite Hyperion sensor signal. In rendering the canopy reflectance, an estimate of optical depth derived from a measurement of downwelling irradiance was used to drive a radiative transfer simulation of atmospheric scattering and attenuation. During the atmospheric model simulation, the input whole-terrain background reflectance estimate was changed to minimize the differences between the model predicted and the observed canopy reflectance spectra at 34 sites. Lacking appropriate spectrally invariant scene targets, inclusion of the field and predicted comparison maximized the model accuracy and, thereby, the detail and precision in the canopy reflectance necessary to detect low percentage occurrences of invasive plants. After accounting for artifacts surrounding prominent absorption features from about 400nm to 1000nm, the atmospheric adjustment strategy correctly explained 99% of the observed canopy reflectance spectra variance. Separately, model simulation explained an average of 88%??9% of the observed variance in the visible and 98% ?? 1% in the near-infrared wavelengths. In the 34 model simulations, maximum differences between the observed and predicted reflectances were typically less than ?? 1% in the visible; however, maximum reflectance differences higher than ?? 1.6% (<??2.3%) at more than a few wavelengths were observed at three sites. In the near-infrared wavelengths, maximum reflectance differences remained less than ??3% for 68% of the comparisons (??1 standard deviation) and less than ??6% for 95% of the comparisons (??2 standard deviation). Higher reflectance differences in the visible and near-infrared wavelengths were most likely associated with problems in the comparison, not in the model generation. ?? 2005 US Government.

International Journal of Remote Sensing↗

USGS2004

Pancam multispectral imaging results from the Spirit Rover at Gusev crater

Panoramic Camera images at Gusev crater reveal a rock-strewn surface interspersed with high- to moderate-albedo fine-grained deposits occurring in part as drifts or in small circular swales or hollows. Optically thick coatings of fine-grained ferric iron-rich dust dominate most bright soil and rock surfaces. Spectra of some darker rock surfaces and rock regions exposed by brushing or grinding show near-infrared spectral signatures consistent with the presence of mafic silicates such as pyroxene or olivine. Atmospheric observations show a steady decline in dust opacity during the mission, and astronomical observations captured solar transits by the martian moons, Phobos and Deimos, as well as a view of Earth from the martian surface.

Science↗

USGS1998

Infrared measurements of pristine and disturbed soils 1. Spectral contrast differences between field and laboratory data

Comparison of emissivity spectra (8-13 ??m) of pristine soils in the field with laboratory reflectance spectra of the same soils showed that laboratory spectra tend to have less spectral contrast than field spectra (see following article). We investigated this the phenomenon by measuring emission spectra of both undisturbed (in situ) and disturbed soils (prepared as if for transport to the laboratory). The disturbed soils had much less spectral contrast than the undisturbed soils in the reststrahlen region near 9 ??m. While the increased porosity of a disturbed soil can decrease spectral contrast due to multiple scattering, we hypothesize that the effect is dominantly the result of a difference in grain-size distribution of the optically active layer (i.e., fine particle coatings). This concept was proposed by Salisbury et al. (1994) to explain their observations that soils washed free of small particles adhering the larger grains exhibited greater spectral contrast than unwashed soils. Our laboratory reflectance spectra of wet- and dry-sieved soils returned from field sites also show greater spectral contrast for wet-sieved (washed) soils. We therefore propose that undisturbed soils in the field can be characterized as 'clean' soils (washed free of fine particles at the surface due to rain and wind action) and that disturbed soils represent 'dirty' soils (contaminated with fine particle coatings). The effect of packing soils in the field and laboratory also increases spectral contrast but not to the magnitude of that observed for undisturbed and wet-sieved soils. Since it is a common practice to use laboratory spectra of field samples to interpret spectra obtained remotely, we suggest that the influence of fine particle coatings on disturbed soils, if unrecognized, could influence interpretations of remote sensing data.Comparison of emissivity spectra (8-13 ??m) of pristine soils in the field with laboratory reflectance spectra of the same soils showed that laboratory spectra tend to have less spectral contrast than field spectra (see following article). We investigated this phenomenon by measuring emission spectra of both undisturbed (in situ) and disturbed soils (prepared as if for transport to the laboratory). The disturbed soils had much less spectral contrast than the undisturbed soils in the reststrahlen region near 9 ??m. While the increased porosity of a disturbed soil can decrease spectral contrast due to multiple scattering, we hypothesize that the effect is dominantly the result of a difference in grain-size distribution of the optically active layer (i.e., fine particle coatings). This concept was proposed by Salisbury et al. (1994) to explain their observations that soils washed free of small particles adhering to larger grains exhibited greater spectral contrast than unwashed soils. Our laboratory reflectance spectra of wet- and dry-sieved soils returned from field sites also show greater spectral contrast for wet-sieved (washed) soils. We therefore propose that undisturbed soils in the field can be characterized as `clean' soils (washed free of fine particles at the surface due to rain and wind action) and that disturbed soils represent `dirty' soils (contaminated with fine particle coatings). The effect of packing soils in the field and laboratory also increases spectral contrast but not to the magnitude of that observed for undisturbed and wet-sieved soils. Since it is a common practice to use laboratory spectra of field samples to interpret spectra obtained remotely, we suggest that the influence of fine particle coatings on disturbed soils, if unrecognized, could influence interpretations of remote sensing data.

Remote Sensing of Environment↗

USGS2019

Remote sensing of river bathymetry: Evaluating a range of sensors, platforms, and algorithms on the upper Sacramento River, California, USA

Remote sensing has become an increasingly viable tool for characterizing fluvial systems. In this study, we used field measurements from a 1.6 km reach of the upper Sacramento River, CA, to evaluate the potential of mapping water depths from a range of platforms, sensors, and depth retrieval methods. Field measurements of water column optical properties also were compared to similar data sets from other rivers to provide context for our results. We considered field spectra, a multispectral satellite image, hyperspectral data collected from conventional and unmanned aircraft, and a bathymetric LiDAR and applied a generalized version of Optimal Band Ratio Analysis (OBRA) and the K nearest neighbors regression (KNN) machine learning algorithm. Linear, quadratic, exponential, power, and lowess OBRA models enabled more flexible curve-fitting in calibrating spectrally based quantities to depth; an exponential formulation avoided artifacts associated with other model types. KNN increased observed vs. predicted R2 values, particularly for the satellite image; we also found that pre-processing of satellite images was unnecessary and that a basic data product could be used for depth retrieval. Bathymetric LiDAR was highly accurate and precise in shallow water, but a lack of bottom returns from areas greater than 2 m deep resulted in large gaps in coverage. The maximum detectable depth imposes an important constraint on fluvial remote sensing and a hybrid approach combined with field surveys of deep areas might be a more realistic operational strategy for bathymetric mapping. Future work will focus on scaling up from short reaches to long river segments.

California↗