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USGS2007

A multiple-tracer approach for identifying sewage sources to an urban stream system

The presence of human-derived fecal coliform bacteria (sewage) in streams and rivers is recognized as a human health hazard. The source of these human-derived bacteria, however, is often difficult to identify and eliminate, because sewage can be delivered to streams through a variety of mechanisms, such as leaking sanitary sewers or private lateral lines, cross-connected pipes, straight pipes, sewer-line overflows, illicit dumping of septic waste, and vagrancy. A multiple-tracer study was conducted to identify site-specific sources of sewage in Accotink Creek, an urban stream in Fairfax County, Virginia, that is listed on the Commonwealth's priority list of impaired streams for violations of the fecal coliform bacteria standard. Beyond developing this multiple-tracer approach for locating sources of sewage inputs to Accotink Creek, the second objective of the study was to demonstrate how the multiple-tracer approach can be applied to other streams affected by sewage sources. The tracers used in this study were separated into indicator tracers, which are relatively simple and inexpensive to apply, and confirmatory tracers, which are relatively difficult and expensive to analyze. Indicator tracers include fecal coliform bacteria, surfactants, boron, chloride, chloride/bromide ratio, specific conductance, dissolved oxygen, turbidity, and water temperature. Confirmatory tracers include 13 organic compounds that are associated with human waste, including caffeine, cotinine, triclosan, a number of detergent metabolites, several fragrances, and several plasticizers. To identify sources of sewage to Accotink Creek, a detailed investigation of the Accotink Creek main channel, tributaries, and flowing storm drains was undertaken from 2001 to 2004. Sampling was conducted in a series of eight synoptic sampling events, each of which began at the most downstream site and extended upstream through the watershed and into the headwaters of each tributary. Using the synoptic sampling approach, 149 sites were sampled at least one time for indicator tracers; 52 of these sites also were sampled for confirmatory tracers at least one time. Through the analysis of multiple-tracer levels in the synoptic samples, three major sewage sources to the Accotink Creek stream network were identified, and several other minor sewage sources to the Accotink Creek system likely deserve additional investigation. Near the end of the synoptic sampling activities, three additional sampling methods were used to gain better understanding of the potential for sewage sources to the watershed. These additional sampling methods included optical brightener monitoring, intensive stream sampling using automated samplers, and additional sampling of several storm-drain networks. The samples obtained by these methods provided further understanding of possible sewage sources to the streams and a better understanding of the variability in the tracer concentrations at a given sampling site. Collectively, these additional sampling methods were a valuable complement to the synoptic sampling approach that was used for the bulk of this study. The study results provide an approach for local authorities to use in applying a relatively simple and inexpensive collection of tracers to locate sewage sources to streams. Although this multiple-tracer approach is effective in detecting sewage sources to streams, additional research is needed to better detect extremely low-volume sewage sources and better enable local authorities to identify the specific sources of the sewage once it is detected in a stream reach.

Virginia↗

USGS2025

Landsat surface product validation instrumentation: The BigMAC exercise

Users of Earth remotely sensed optical imagery are increasingly demanding a surface reflectance or surface temperature product instead of the top-of-atmosphere products that have been produced historically. Validating the accuracy of surface products remains a difficult task since it involves assessment across a range of atmospheric profiles, as well as many different land surface types. Thus, standard approaches from the satellite calibration community do not apply and new technologies need to be developed. The Big Multi-Agency Campaign (BigMAC) was developed to assess current technologies that might be used for validation of surface products derived from satellite imagery, with emphasis on Landsat. Conducted in August, 2021, in Brookings, SD, USA, a variety of measurement technologies were fielded and assessed for accuracy, precision, and deployability. Each technology exhibited its strengths and weaknesses. Handheld spectroradiometers are capable of surface reflectance measurements with accuracies in the 0.01 - 0.02 absolute reflectance units, but are expensive to deploy. Unmanned Aircraft System (UAS)-based radiometers have the potential of making measurements with similar accuracy, but are also difficult to deploy. Mirror-based empirical line methods showed improving accuracy potential, but deployment also remains an issue. However, there are inexpensive radiometers designed for long-term autonomous use that exhibited good accuracy and precision, as well as being easy to deploy. Thermal measurement technologies showed accuracy potential in the 1 - 2K range, and some easily deployable instruments are available. Results from BigMAC indicate there are technologies available today to begin making operational surface reflectance/temperature measurements and strong potential for improvements in the future.

Sensors↗

USGS2023

Critical minerals: Germanium and cobalt in the Bornite deposit, southwestern Brooks Range, Alaska

Increasing demand for Ge and Co has led to a renewed interest and focus on advancing our understanding of the occurrence, distribution, and sequestration of these critical elements in known ore deposits. A workflow using a variety of analytical techniques and co-registered datasets has been developed and was applied to the carbonate hosted Bornite Cu-Co (Zn,-Ge) deposit in Alaska, where a new orebody (“the South Reef”) was discovered in 2011. The South Reef is host to substantial amounts of high-grade Cu, Co, and appreciable Zn, but also contains localised elevated concentrations of Ge. We describe the mineralogy and paragenesis of the South Reef based on detailed optical petrography, scanning electron microscopy, scanning electron microscopy-based automated mineralogy, and mapping μ-X-ray fluorescence analysis. Germanium was found to exist in renierite, white mica, illite, galena and feldspars within the South Reef. Cobalt was found to occur in cobaltiferous pyrite, carrollite, and cobaltite.

Alaska↗

USGS2008

MODIS and SeaWIFS on-orbit lunar calibration

The Moon plays an important role in the radiometric stability monitoring of the NASA Earth Observing System's (EOS) remote sensors. The MODIS and SeaWIFS are two of the key instruments for NASA's EOS missions. The MODIS Protoflight Model (PFM) on-board the Terra spacecraft and the MODIS Flight Model 1 (FM1) on-board the Aqua spacecraft were launched on December 18, 1999 and May 4, 2002, respectively. They view the Moon through the Space View (SV) port approximately once a month to monitor the long-term radiometric stability of their Reflective Solar Bands (RSB). SeaWIFS was launched on-board the OrbView-2 spacecraft on August 1, 1997. The SeaWiFS lunar calibrations are obtained once a month at a nominal phase angle of 7??. The lunar irradiance observed by these instruments depends on the viewing geometry. The USGS photometric model of the Moon (the ROLO model) has been developed to provide the geometric corrections for the lunar observations. For MODIS, the lunar view responses with corrections for the viewing geometry are used to track the gain change for its reflective solar bands (RSB). They trend the system response degradation at the Angle Of Incidence (AOI) of sensor's SV port. With both the lunar observation and the on-board Solar Diffuser (SD) calibration, it is shown that the MODIS system response degradation is wavelength, mirror side, and AOI dependent. Time-dependent Response Versus Scan angle (RVS) Look-Up Tables (LUT) are applied in MODIS RSB calibration and lunar observations play a key role in RVS derivation. The corrections provided by the RVS in the Terra and Aqua MODIS data from the 412 nm band are as large as 16% and 13%, respectively. For SeaWIFS lunar calibrations, the spacecraft is pitched across the Moon so that the instrument views the Moon near nadir through the same optical path as it views the Earth. The SeaWiFS system gain changes for its eight bands are calibrated using the geometrically-corrected lunar observations. The radiometric corrections to the SeaWiFS data, after more than ten years on orbit, are 19% at 865 nm, 8% at 765 nm, and 1-3% in the other bands. In this report, the lunar calibration algorithms are reviewed and the RSB gain changes observed by the lunar observations are shown for all three sensors. The lunar observations for the three instruments are compared using the USGS photometric model. The USGS lunar model facilitates the cross calibration of instruments with different spectra bandpasses whose measurements of the Moon differ in time and observing geometry.

Conference Paper↗

USGS2004

Acoustic and optical borehole-wall imaging for fractured-rock aquifer studies

Imaging with acoustic and optical televiewers results in continuous and oriented 360° views of the borehole wall from which the character, relation, and orientation of lithologic and structural planar features can be defined for studies of fractured-rock aquifers. Fractures are more clearly defined under a wider range of conditions on acoustic images than on optical images including dark-colored rocks, cloudy borehole water, and coated borehole walls. However, optical images allow for the direct viewing of the character of and relation between lithology, fractures, foliation, and bedding. The most powerful approach is the combined application of acoustic and optical imaging with integrated interpretation. Imaging of the borehole wall provides information useful for the collection and interpretation of flowmeterand other geophysical logs, core samples, and hydraulic and water-quality data from packer testing and monitoring.

Journal of Applied Geophysics↗

USGS2021

Characterization of groundwater quality and discharge with emphasis on selenium in an irrigated agricultural drainage near Delta, Colorado, 2017–19

Selenium is a water-quality constituent of concern for aquatic ecosystems in the lower Gunnison River Basin. Selenium is derived from bedrock of the Mancos Shale and is mobilized and transported to groundwater and surface water by application of irrigation water. Although it is recognized that groundwater contributes an appreciable amount of selenium to surface water, few studies have addressed interactions between the two. The U.S. Geological Survey in cooperation with the Colorado Water Conservation Board conducted a study during 2017–19 to characterize the quality and quantity of groundwater discharging to an agricultural drainage near Delta, Colorado, locally known as Sunflower Drain. Water quality in the study area is characterized by high dissolved solids with elevated concentrations of selenium and nitrate resulting from dissolution of soluble salts in the Mancos Shale. Selenium concentrations have decreased by 50 percent since the early 2000s, possibly in response to irrigation system improvements. Stable water isotopes indicate streamflow is dominated by canal water during the irrigation season (April to October) and, during the nonirrigation season (November to March), is dominated by groundwater that has undergone some degree of evaporation. Pesticide and pharmaceutical compounds were infrequently detected, and results indicate they were derived from sources outside the study area such that they do not appear to be useful as tracers of groundwater sources. Stable isotopes of nitrate indicate that nitrate originates from the Mancos Shale, and the isotopic composition is enriched by denitrification in the groundwater system. Using a mass-balance approach, estimated groundwater discharge rates to Sunflower Drain ranged from 0.15 to 0.27 cubic feet per second per mile with one losing reach identified. Selenium, sulfate, and nitrate concentrations in groundwater estimated by mass-balance calculations were similar to concentrations measured in the Poly 17 observation well, located in a largely irrigated area in east tributary. One tributary reach had higher concentrations of selenium, sulfate, and nitrate likely reflecting localized inputs of more concentrated groundwater, similar to the concentrations in the Poly 7 observation well, which is downgradient from a residential area in the west tributary. Three pilot studies were conducted, including fiber optic distributed temperature sensing to detect groundwater discharge zones in the stream channel, a passive seismic technique to estimate depth to bedrock, and use of radon-222 as a geochemical tracer of groundwater discharge. All three techniques show promise as additional approaches for investigating groundwater discharge surface-water systems in irrigated drainage areas on Mancos Shale. The factors that affect groundwater movement mainly include when and where irrigation water is transported and applied, and the distribution of bedrock of the Mancos Shale and overlying alluvial deposits. The average groundwater recharge rate for the study area was estimated at 8.1 inches per year, based on mass balance calculations from synoptic survey data. Along the western tributary of Sunflower Drain, there was evidence that spills from the East Canal may recharge the groundwater aquifer adjacent to the stream channel. Groundwater movement to the stream channel may be controlled by the topography of the alluvial/bedrock interface or focused along human-made features, such as tile drains and ditches constructed around irrigated fields. On larger scales, the top of bedrock was also important, creating a topographic constriction that caused a zone of groundwater discharge. The groundwater system is complex, and further study could better define the system, possibly through application of a groundwater flow model and more extensive studies using some of the exploratory methods evaluated in this study.

Colorado↗

USGS2019

Optical characterization of two cyanobacteria genera, Aphanizomenon and Microcystis, with hyperspectral microscopy.

Cyanobacterial blooms are a nuisance and a potential hazard in freshwater systems worldwide. Remote sensing has been used to detect cyanobacterial blooms, but few studies have distinguished between genera of cyanobacteria. Because some genera are more likely to be toxic than others, this is a useful distinction.In this study, hyperspectral imaging reflectance microscopy was used to examine cyanobacteria from Upper Klamath Lake, Oregon, USA, at high spatial and spectral resolution to determine if two species found commonly in the lake, Aphanizomenon flos-aquae and Microcystis aeruginosa, can be separated spectrally. Of the analytical methods applied, a spectral shape algorithm applied to the derivative was found to be most successful in classifying these species in microscope scenes. Further work is required to determine if the spectral characterization of cyanobacterial genera can be scaled up to other remote sensing applications.

Oregon↗

USGS2002

The National Vegetation Classification Standard applied to the remote sensing classification of two semiarid environments

The National Vegetation Classification Standard (NVCS) was implemented at two US National Park Service (NPS) sites in Texas, the Padre Island National Seashore (PINS) and the Lake Meredith National Recreation Area (LM-NRA), to provide information for NPS oil and gas management plans. Because NVCS landcover classifications did not exist for these two areas prior to this study, we created landcover classes, through intensive ground and aerial reconnaissance, that characterized the general landscape features and at the same time complied with NVCS guidelines. The created landcover classes were useful for the resource management and were conducive to classification with optical remote sensing systems, such as the Landsat Thematic Mapper (TM). In the LMNRA, topographic elevation data were added to the TM data to reduce confusion between cliff, high plains, and forest classes. Classification accuracies (kappa statistics) of 89.9% (0.89) and 88.2% (0.87) in PINS and LMNRA, respectively, verified that the two NPS landholdings were adequately mapped with TM data. Improved sensor systems with higher spectral and spatial resolutions will ultimately refine the broad classes defined in this classification; however, the landcover classifications created in this study have already provided valuable information for the management of both NPS lands. Habitat information provided by the classifications has aided in the placement of inventory and monitoring plots, has assisted oil and gas operators by providing information on sensitive habitats, and has allowed park managers to better use resources when fighting wildland fires and in protecting visitors and the infrastructure of NPS lands.

Environmental Management↗

USGS2011

OSL dating of a Pleistocene maar: Birket Ram, the Golan heights

Direct dating of maars and their phreatomagmatic deposits is difficult due to the dominance of lithic (host rock) fragments and glassy particles of the juvenile magma. In this paper we demonstrate that optically stimulated luminescence (OSL) dating can be successfully used for age determination of phreatomagmatic deposits. We studied the tuff deposit of Birket Ram, a basanitic maar located at the northern edge of the Golan heights on the western Arabian plate. The maar is underlain by a thick section of Pleistocene basalts, and currently hosts a small lake. It is filled by approximately 90m of lacustrine sediments with radiocarbon ages extrapolated to 108ka at the base. OSL was applied to quartz grains extracted from tuffs and paleosols in order to set the time frame of the phreatomagmatism at the site. A maximum age constraint of 179??13ka was determined for a paleosol that underlies the maar ejecta. Quartz grains from two layers in the tuff section yielded a direct age of 129??6ka for the phreatomagmatic eruption. A younger age of 104??7ka, which was determined for a tuff layer underlying a basaltic flow, was attributed to thermal resetting during the lava emplacement. This was confirmed by an 40Ar/39Ar age of 101??3ka determined on the overlying basalt. The internal consistency of the OSL ages and the agreement with the 40Ar/39Ar age determination as well as with previous estimates demonstrates the potential of OSL for maar dating. ?? 2010 Elsevier B.V.

Journal of Volcanology and Geothermal Research↗

USGS2024

Long-term distributed temperature sensing monitoring for near-wellbore gas migration and gas hydrate formation

Well integrity monitoring has always been a critical component of subsurface oil and gas operations. Distributed fiber-optic sensing is an emerging technology that shows great promise for monitoring processes, both in boreholes and in other settings. In this study, we present a case study of using distributed temperature sensing (DTS) technology to monitor a cemented and plugged well in the Alaska North Slope (ANS). The well was drilled as part of a long-term gas hydrate study, and the downhole DTS data were recorded over a period of approximately 2 years. By applying a temporal gradient and removing instrument instability noise, we reveal subtle (<0.001°C/h) thermal anomalies, which are characterized by brief warming periods followed by longer cooling periods at discrete depths along the borehole. The observed coherent events show an upward trajectory from deeper formations into the overlying permafrost interval, with the thermal anomalies concentrated in relatively coarse-grained sandstone layers. We also observe that the upward migration rate of the DTS anomalies varies with formation lithology and that there is a spatial and temporal correlation between the subsurface events and measured wellhead annular pressures. We interpret that the observed warming events represent the exothermic process of gas hydrate formation that is occurring in association with the upward migration of gas outside the well casing, and this interpretation is confirmed by numerical simulations. These observations demonstrate the ability of suitably processed DTS data to detect subtle processes and highlight the value of DTS technologies for wellbore integrity monitoring.

Alaska↗

USGS2016

Inferring river bathymetry via Image-to-Depth Quantile Transformation (IDQT)

Conventional, regression-based methods of inferring depth from passive optical image data undermine the advantages of remote sensing for characterizing river systems. This study introduces and evaluates a more flexible framework, Image-to-Depth Quantile Transformation (IDQT), that involves linking the frequency distribution of pixel values to that of depth. In addition, a new image processing workflow involving deep water correction and Minimum Noise Fraction (MNF) transformation can reduce a hyperspectral data set to a single variable related to depth and thus suitable for input to IDQT. Applied to a gravel bed river, IDQT avoided negative depth estimates along channel margins and underpredictions of pool depth. Depth retrieval accuracy (R25 0.79) and precision (0.27 m) were comparable to an established band ratio-based method, although a small shallow bias (0.04 m) was observed. Several ways of specifying distributions of pixel values and depths were evaluated but had negligible impact on the resulting depth estimates, implying that IDQT was robust to these implementation details. In essence, IDQT uses frequency distributions of pixel values and depths to achieve an aspatial calibration; the image itself provides information on the spatial distribution of depths. The approach thus reduces sensitivity to misalignment between field and image data sets and allows greater flexibility in the timing of field data collection relative to image acquisition, a significant advantage in dynamic channels. IDQT also creates new possibilities for depth retrieval in the absence of field data if a model could be used to predict the distribution of depths within a reach.

Water Resources Research↗

USGS2003

Hydrothermal diamond-anvil cell: Application to studies of geologic fluids

The hydrothermal diamond-anvil cell (HDAC) was designed to simulate the geologic conditions of crustal processes in the presence of water or other fluids. The HDAC has been used to apply external pressure to both synthetic and natural fluid inclusions in quartz to minimize problems caused by stretching or decrepitation of inclusions during microthermometric analysis. When the HDAC is loaded with a fluid sample, it can be considered as a large synthetic fluid inclusion and therefore, can be used to study the PVTX properties as well as phase relations of the sample fluid. Because the HDAC has a wide measurement pressure-temperature range and also allows in-situ optical observations, it has been used to study critical phenomena of various chemical systems, such as the geologically important hydrous silicate melts. It is possible, when the HDAC is combined with synchrotron X-ray sources, to obtain basic information on speciation and structure of metal including rare-earth elements (REE) complexes in hydrothermal solutions as revealed by X-ray absorption fine structure (XAFS) spectra. Recent modifications of the HDAC minimize the loss of intensity of X-rays due to scattering and absorption by the diamonds. These modifications are especially important for studying elements with absorption edges below 10 keV and therefore particularly valuable for our understanding of transport and deposition of first-row transition elements and REE in hydrothermal environments.

Acta Petrologica Sinica↗

USGS2009

A revised burial dose estimation procedure for optical dating of youngand modern-age sediments

The presence of genuinely zero-age or near-zero-age grains in modern-age and very young samples poses a problem for many existing burial dose estimation procedures used in optical (optically stimulated luminescence, OSL) dating. This difficulty currently necessitates consideration of relatively simplistic and statistically inferior age models. In this study, we investigate the potential for using modified versions of the statistical age models of Galbraith et??al. [Galbraith, R.F., Roberts, R.G., Laslett, G.M., Yoshida, H., Olley, J.M., 1999. Optical dating of single and multiple grains of quartz from Jinmium rock shelter, northern Australia: Part I, experimental design and statistical models. Archaeometry 41, 339-364.] to provide reliable equivalent dose (D e ) estimates for young and modern-age samples that display negative, zero or near-zero D e estimates. For this purpose, we have revised the original versions of the central and minimum age models, which are based on log-transformed D e values, so that they can be applied to un-logged D e estimates and their associated absolute standard errors. The suitability of these 'un-logged' age models is tested using a series of known-age fluvial samples deposited within two arroyo systems from the American Southwest. The un-logged age models provide accurate burial doses and final OSL ages for roughly three-quarters of the total number of samples considered in this study. Sensitivity tests reveal that the un-logged versions of the central and minimum age models are capable of producing accurate burial dose estimates for modern-age and very young (<350??yr) fluvial samples that contain (i) more than 20% of well-bleached grains in their D e distributions, or (ii) smaller sub-populations of well-bleached grains for which the D e values are known with high precision. Our results indicate that the original (log-transformed) versions of the central and minimum age models are still preferable for most routine dating applications, since these age models are better suited to the statistical properties of typical single-grain and multi-grain single-aliquot D e datasets. However, the unique error properties of modern-age samples, combined with the problems of calculating natural logarithms of negative or zero-Gy D e values, mean that the un-logged versions of the central and minimum age models currently offer the most suitable means of deriving accurate burial dose estimates for very young and modern-age samples. ?? 2009 Elsevier Ltd. All rights reserved.

Quaternary Geochronology↗

USGS2000

Fracture process zone in granite

In uniaxial compression tests performed on Aue granite cores (diameter 50 mm, length 100 mm), a steel loading plate was used to induce the formation of a discrete shear fracture. A zone of distributed microcracks surrounds the tip of the propagating fracture. This process zone is imaged by locating acoustic emission events using 12 piezoceramic sensors attached to the samples. Propagation velocity of the process zone is varied by using the rate of acoustic emissions to control the applied axial force. The resulting velocities range from 2 mm/s in displacement-controlled tests to 2 μm/s in tests controlled by acoustic emission rate. Wave velocities and amplitudes are monitored during fault formation. P waves transmitted through the approaching process zone show a drop in amplitude of 26 dB, and ultrasonic velocities are reduced by 10%. The width of the process zone is ∼9 times the grain diameter inferred from acoustic data but is only 2 times the grain size from optical crack inspection. The process zone of fast propagating fractures is wider than for slow ones. The density of microcracks and acoustic emissions increases approaching the main fracture. Shear displacement scales linearly with fracture length. Fault plane solutions from acoustic events show similar orientation of nodal planes on both sides of the shear fracture. The ratio of the process zone width to the fault length in Aue granite ranges from 0.01 to 0.1 inferred from crack data and acoustic emissions, respectively. The fracture surface energy is estimated from microstructure analysis to be ∼2 J. A lower bound estimate for the energy dissipated by acoustic events is 0.1 J.

Journal of Geophysical Research B: Solid Earth↗

USGS2020

Inferring surface flow velocities in sediment-laden Alaskan rivers from optical image sequences acquired from a helicopter

The remote, inaccessible location of many rivers in Alaska creates a compelling need for remote sensing approaches to streamflow monitoring. Motivated by this objective, we evaluated the potential to infer flow velocities from optical image sequences acquired from a helicopter deployed above two large, sediment-laden rivers. Rather than artificial seeding, we used an ensemble correlation particle image velocimetry (PIV) algorithm to track the movement of boil vortices that upwell suspended sediment and produce a visible contrast at the water surface. This study introduced a general, modular workflow for image preparation (stabilization and geo-referencing), preprocessing (filtering and contrast enhancement), analysis (PIV), and postprocessing (scaling PIV output and assessing accuracy via comparison to field measurements). Applying this method to images acquired with a digital mapping camera and an inexpensive video camera highlighted the importance of image enhancement and the need to resample the data to an appropriate, coarser pixel size and a lower frame rate. We also developed a Parameter Optimization for PIV (POP) framework to guide selection of the interrogation area (IA) and frame rate for a particular application. POP results indicated that the performance of the PIV algorithm was highly robust and that relatively large IAs (64–320 pixels) and modest frame rates (0.5–2 Hz) yielded strong agreement ( R 2 > 0 . 9 "> R 2 > 0 . 9 ) between remotely sensed velocities and field measurements. Similarly, analysis of the sensitivity of PIV accuracy to image sequence duration showed that dwell times as short as 16 s would be sufficient at a frame rate of 1 Hz and could be cut in half if the frame rate were doubled. The results of this investigation indicate that helicopter-based remote sensing of velocities in sediment-laden rivers could contribute to noncontact streamgaging programs and enable reach-scale mapping of flow fields.

Alaska↗

USGS2025

Ultraviolet and visible remote sensing of volcanic gases

As magma rises in volcanic systems, volatile species exsolve from the silicate melt and are emitted as gases into the atmosphere. Measuring the magnitude and composition of gas emissions from volcanoes provides insights into processes occurring deep within the Earth and helps constrain the impact of volcanic degassing on atmospheric chemistry. Optical remote sensing techniques allow volcanic gas emissions to be characterized without the need to access hazardous areas near active volcanic vents. This paper reviews the state of the art in ultraviolet and visible volcanic gas remote sensing from the ground, air, and space. Special attention is given to discussing the physics of atmospheric radiative transfer on which these techniques are based. The functionality and limitations of different remote sensing instruments are examined, making clear that the ideal choice of instrumentation will depend on the volcanic system to which it is applied and the sought measurement parameters. Common algorithms for determining trace gas column densities, gas burdens, and volcanic emission rates from measurements of spectral radiance are outlined and compared, showing how some algorithms attempt to model the physics of the measurement while others maximize sensitivity. Several examples demonstrate how remote sensing measurements continue to advance our understanding of volcanic systems and their impact on the atmosphere. Finally, a few promising directions of inquiry are suggested that could lead to improvements in remote sensing instrumentation and analysis techniques. By combining spectroscopic and imaging techniques, improving our understanding of atmospheric radiative transfer, expanding the suite of target gases, and increasing the coverage and frequency of observations, we stand to significantly improve our ability to detect and quantify volcanic gas emissions and gain new insights into important Earth-system processes.

Journal of Volcanology and Geothermal Research↗

USGS2017

User guide for luminescence sampling in archaeological and geological contexts

Luminescence dating provides a direct age estimate of the time of last exposure of quartz or feldspar minerals to light or heat and has been successfully applied to deposits, rock surfaces, and fired materials in a number of archaeological and geological settings. Sampling strategies are diverse and can be customized depending on local circumstances, although all sediment samples need to include a light-safe sample and material for dose-rate determination. The accuracy and precision of luminescence dating results are directly related to the type and quality of the material sampled and sample collection methods in the field. Selection of target material for dating should include considerations of adequacy of resetting of the luminescence signal (optical and thermal bleaching), the ability to characterize the radioactive environment surrounding the sample (dose rate), and the lack of evidence for post-depositional mixing (bioturbation in soils and sediment). Sample strategies for collection of samples from sedimentary settings and fired materials are discussed. This paper should be used as a guide for luminescence sampling and is meant to provide essential background information on how to properly collect samples and on the types of materials suitable for luminescence dating.

Advances in Archaeological Practice: A Journal of ↗

USGS2024

Detecting avalanche path ground cover and vegetation change across multiple scales through time using remote sensing tools

Large-magnitude avalanches often alter vegetation composition, avalanche path dimensions, and subsequent avalanche return periods. Understanding temporal changes in individual avalanche path trimlines, runout zones, and geomorphic characteristics helps forecasters, planners, and engineers estimate potential avalanche destructive size and impact on infrastructure or settlements in the runout zone. Understanding these changes on a large scale also provides information on post-cycle avalanche distribution. Here, we use remote sensing platforms and change detection techniques to examine vegetation change in avalanche paths in Montana and Colorado. In northwest Montana, we implemented a novel approach using lidar, aerial imagery, and a random forest model to classify imagery-observed vegetation within avalanche paths. We calculated spatially explicit avalanche return periods using a physically based spatial interpolation method and characterized the vegetation within those return period zones. In Colorado, we investigated changes in avalanche path vegetation characteristics prior to and after a widespread large-magnitude avalanche cycle. The highest frequency of avalanche return periods was broadly characterized by grassland and shrubland, but topography greatly influences vegetation classes and return periods. Furthermore, statistically significant differences in lidar-derived vegetation canopy height exist between categorical return periods. We used optical sensors from satellite imagery to analyze changes in Normalized Difference Vegetation Index (NDVI) to calculate ground cover change over time. NDVI, a measure of near-infrared and red bands within the imagery, allowed us to distinguish between green vegetation (e.g., trees and shrubs) and non-vegetated ground cover (e.g., dead and downed trees, rocks, and dirt) within avalanche paths. For this study, we calculated changes in NDVI values by comparing imagery from 2018 to imagery from 2019 after a widespread large magnitude avalanche cycle occurred in March 2019 in Colorado, United States. We applied a filtering process to reduce error, classified NDVI change based on the value distribution, and then calculated area change of all areas within each avalanche path. We completed this process for 1633 avalanche paths throughout Colorado. We found that using NDVI difference values pre- and post-avalanche cycle allowed us to identify ground cover change in avalanche paths throughout Colorado. These changes span from a slight expansion of existing avalanche paths to substantial landscape disturbance. For example, a size D5 avalanche caused severe ground cover change in 18% of one single path near Aspen, Colorado. This suggests that large magnitude avalanches can redefine avalanche path dimensions and could impact subsequent avalanche size and frequency. Using NDVI from satellite imagery is a simple way to detect ground cover changes in avalanche paths on a large scale or in remote areas. In general, remote sensing products to detect and examine vegetation and ground cover change in avalanche paths can help inform avalanche distribution and benefit planning efforts.

Montana↗