USGS Science⌕ Search

SEARCH · USGS Science

Results for “Journal of Remote Sensing”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25Linked to original sources
USGS2015

Variations in water temperature and implications for trout populations in the Upper Schoharie Creek and West Kill, New York, USA

Water temperature is a key component of aquatic ecosystems because it plays a pivotal role in determining the suitability of stream and river habitat to most freshwater fish species. Continuous temperature loggers and airborne thermal infrared (TIR) remote sensing were used to assess temporal and spatial temperature patterns on the Upper Schoharie Creek and West Kill in the Catskill Mountains, New York, USA. Specific objectives were to characterize (1) contemporary thermal conditions, (2) temporal and spatial variations in stressful water temperatures, and (3) the availability of thermal refuges. In-stream loggers collected data from October 2010 to October 2012 and showed summer water temperatures exceeded the 1-day and 7-day thermal tolerance limits for trout survival at five of the seven study sites during both summers. Results of the 7 August 2012 TIR indicated there was little thermal refuge at the time of the flight. About 690,170 m 2 of water surface area were mapped on the Upper Schoharie, yet only 0.009% (59 m 2 ) was more than 1.0 °C below the median water surface temperature (BMT) at the thalweg and no areas were more than 2.0 °C BMT. On the West Kill, 79,098 m 2 were mapped and 0.085% (67 m 2 ) and 0.018% (14 m 2 ) were BMT by 1 and 2 °C, respectively. These results indicate that summer temperatures in the majority of the study area are stressful for trout and may adversely affect growth and survival. Validation studies are needed to confirm the expectation that resident trout are in poor condition or absent from the downstream portion of the study area during warm-water periods.

New York↗
USGS2008

Characterization of errors in a coupled snow hydrology-microwave emission model

Traditional approaches to the direct estimation of snow properties from passive microwave remote sensing have been plagued by limitations such as the tendency of estimates to saturate for moderately deep snowpacks and the effects of mixed land cover within remotely sensed pixels. An alternative approach is to assimilate satellite microwave emission observations directly, which requires embedding an accurate microwave emissions model into a hydrologic prediction scheme, as well as quantitative information of model and observation errors. In this study a coupled snow hydrology [Variable Infiltration Capacity (VIC)] and microwave emission [Dense Media Radiative Transfer (DMRT)] model are evaluated using multiscale brightness temperature (TB) measurements from the Cold Land Processes Experiment (CLPX). The ability of VIC to reproduce snowpack properties is shown with the use of snow pit measurements, while TB model predictions are evaluated through comparison with Ground-Based Microwave Radiometer (GBMR), air-craft [Polarimetric Scanning Radiometer (PSR)], and satellite [Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E)] TB measurements. Limitations of the model at the point scale were not as evident when comparing areal estimates. The coupled model was able to reproduce the TB spatial patterns observed by PSR in two of three sites. However, this was mostly due to the presence of relatively dense forest cover. An interesting result occurs when examining the spatial scaling behavior of the higher-resolution errors; the satellite-scale error is well approximated by the mode of the (spatial) histogram of errors at the smaller scale. In addition, TB prediction errors were almost invariant when aggregated to the satellite scale, while forest-cover fractions greater than 30% had a significant effect on TB predictions. ?? 2008 American Meteorological Society.

Journal of Hydrometeorology↗
USGS2011

Hurricane impacts on coastal wetlands: A half-century record of storm-generated features from southern Louisiana

Temporally and spatially repeated patterns of wetland erosion, deformation, and deposition are observed on remotely sensed images and in the field after hurricanes cross the coast of Louisiana. The diagnostic morphological wetland features are products of the coupling of high-velocity wind and storm-surge water and their interaction with the underlying, variably resistant, wetland vegetation and soils. Erosional signatures include construction of orthogonal-elongate ponds and amorphous ponds, pond expansion, plucked marsh, marsh denudation, and shoreline erosion. Post-storm gravity reflux of floodwater draining from the wetlands forms dendritic incisions around the pond margins and locally integrates drainage pathways forming braided channels. Depositional signatures include emplacement of broad zones of organic wrack on topographic highs and inorganic deposits of variable thicknesses and lateral extents in the form of shore-parallel sandy washover terraces and interior-marsh mud blankets. Deformational signatures primarily involve laterally compressed marsh and displaced marsh mats and balls. Prolonged water impoundment and marsh salinization also are common impacts associated with wetland flooding by extreme storms. Many of the wetland features become legacies that record prior storm impacts and locally influence subsequent storm-induced morphological changes. Wetland losses caused by hurricane impacts depend directly on impact duration, which is controlled by the diameter of hurricane-force winds, forward speed of the storm, and wetland distance over which the storm passes. Distinguishing between wetland losses caused by storm impacts and losses associated with long-term delta-plain processes is critical for accurate modeling and prediction of future conversion of land to open water.

Louisiana↗
USGS2010

Hyperspectral analysis of columbia spotted frog habitat

Wildlife managers increasingly are using remotely sensed imagery to improve habitat delineations and sampling strategies. Advances in remote sensing technology, such as hyperspectral imagery, provide more information than previously was available with multispectral sensors. We evaluated accuracy of high-resolution hyperspectral image classifications to identify wetlands and wetland habitat features important for Columbia spotted frogs (Rana luteiventris) and compared the results to multispectral image classification and United States Geological Survey topographic maps. The study area spanned 3 lake basins in the Salmon River Mountains, Idaho, USA. Hyperspectral data were collected with an airborne sensor on 30 June 2002 and on 8 July 2006. A 12-year comprehensive ground survey of the study area for Columbia spotted frog reproduction served as validation for image classifications. Hyperspectral image classification accuracy of wetlands was high, with a producer's accuracy of 96 (44 wetlands) correctly classified with the 2002 data and 89 (41 wetlands) correctly classified with the 2006 data. We applied habitat-based rules to delineate breeding habitat from other wetlands, and successfully predicted 74 (14 wetlands) of known breeding wetlands for the Columbia spotted frog. Emergent sedge microhabitat classification showed promise for directly predicting Columbia spotted frog egg mass locations within a wetland by correctly identifying 72 (23 of 32) of known locations. Our study indicates hyperspectral imagery can be an effective tool for mapping spotted frog breeding habitat in the selected mountain basins. We conclude that this technique has potential for improving site selection for inventory and monitoring programs conducted across similar wetland habitat and can be a useful tool for delineating wildlife habitats. ?? 2010 The Wildlife Society.

Journal of Wildlife Management↗
USGS2015

A comparison of thermal infrared to fiber-optic distributed temperature sensing for evaluation of groundwater discharge to surface water

Groundwater has a predictable thermal signature that can be used to locate discrete zones of discharge to surface water. As climate warms, surface water with strong groundwater influence will provide habitat stability and refuge for thermally stressed aquatic species, and is therefore critical to locate and protect. Alternatively, these discrete seepage locations may serve as potential point sources of contaminants from polluted aquifers. This study compares two increasingly common heat tracing methods to locate discrete groundwater discharge: direct-contact measurements made with fiber-optic distributed temperature sensing (FO-DTS) and remote sensing measurements collected with thermal infrared (TIR) cameras. FO-DTS is used to make high spatial resolution (typically m) thermal measurements through time within the water column using temperature-sensitive cables. The spatialtemporal data can be analyzed with statistical measures to reveal zones of groundwater influence, however, the personnel requirements, time to install, and time to georeference the cables can be burdensome, and the control units need constant calibration. In contrast, TIR data collection, either from handheld, airborne, or satellite platforms, can quickly capture point-in-time evaluations of groundwater seepage zones across large scales. However the remote nature of TIR measurements means they can be adversely influenced by a number of environmental and physical factors, and the measurements are limited to the surface skin temperature of water features. We present case studies from a range of lentic to lotic aquatic systems to identify capabilities and limitations of both technologies and highlight situations in which one or the other might be a better instrument choice for locating groundwater discharge. FO-DTS performs well in all systems across seasons, but data collection was limited spatially by practical considerations of cable installation. TIR is found to consistently locate groundwater seepage zones above and along the streambank, but submerged seepage zones are only well identified in shallow systems (e.g. <0.5 m depth) with moderate flow. Winter data collection, when groundwater is relatively warm and buoyant, increases the water surface expression of discharge zones in shallow systems.

Massachusetts, Michigan, Montana, New York, Pennsy↗
USGS1999

Overview of the Mars Pathfinder Mission: Launch through landing, surface operations, data sets, and science results

Mars Pathfinder successfully landed at Ares Vallis on July 4, 1997, deployed and navigated a small rover about 100 m clockwise around the lander, and collected data from three science instruments and ten technology experiments. The mission operated for three months and returned 2.3 Gbits of data, including over 16,500 lander and 550 rover images, 16 chemical analyses of rocks and soil, and 8.5 million individual temperature, pressure and wind measurements. Path‐finder is the best known location on Mars, having been clearly identified with respect to other features on the surface by correlating five prominent horizon features and two small craters in lander images with those in high‐resolution orbiter images and in inertial space from two‐way ranging and Doppler tracking. Tracking of the lander has fixed the spin pole of Mars, determined the precession rate since Viking 20 years ago, and indicates a polar moment of inertia, which constrains a central metallic core to be between 1300 and ∼2000 km in radius. Dark rocks appear to be high in silica and geochemically similar to anorogenic andesites; lighter rocks are richer in sulfur and lower in silica, consistent with being coated with various amounts of dust. Rover and lander images show rocks with a variety of morphologies, fabrics and textures, suggesting a variety of rock types are present. Rounded pebbles and cobbles on the surface as well as rounded bumps and pits on some rocks indicate these rocks may be conglomerates (although other explanations are also possible), which almost definitely require liquid water to form and a warmer and wetter past. Air‐borne dust is composed of composite silicate particles with a small fraction of a highly magnetic mineral, interpreted to be most likely maghemite; explanations suggest iron was dissolved from crustal materials during an active hydrologic cycle with maghemite freeze dried onto silicate dust grains. Remote sensing data at a scale of a kilometer or greater and an Earth analog correctly predicted a rocky plain safe for landing and roving with a variety of rocks deposited by catstrophic floods, which are relatively dust free. The surface appears to have changed little since it formed billions of years ago, with the exception that eolian activity may have deflated the surface by ∼3–7 cm, sculpted wind tails, collected sand into dunes, and eroded ventifacts (fluted and grooved rocks). Pathfinder found a dusty lower atmosphere, early morning water ice clouds, and morning near‐surface air temperatures that changed abruptly with time and height. Small scale vortices, interpreted to be dust devils, were observed repeatedly in the afternoon by the meteorology instruments and have been imaged.

Journal of Geophysical Research E: Planets↗
USGS2003

Vertical velocity variance in the mixed layer from radar wind profilers

Vertical velocity variance data were derived from remotely sensed mixed layer turbulence measurements at the Atmospheric Boundary Layer Experiments (ABLE) facility in Butler County, Kansas. These measurements and associated data were provided by a collection of instruments that included two 915 MHz wind profilers, two radio acoustic sounding systems, and two eddy correlation devices. The data from these devices were available through the Atmospheric Boundary Layer Experiment (ABLE) database operated by Argonne National Laboratory. A signal processing procedure outlined by Angevine et al. was adapted and further built upon to derive vertical velocity variance, w_pm???2, from 915 MHz wind profiler measurements in the mixed layer. The proposed procedure consisted of the application of a height-dependent signal-to-noise ratio (SNR) filter, removal of outliers plus and minus two standard deviations about the mean on the spectral width squared, and removal of the effects of beam broadening and vertical shearing of horizontal winds. The scatter associated with w_pm???2 was mainly affected by the choice of SNR filter cutoff values. Several different sets of cutoff values were considered, and the optimal one was selected which reduced the overall scatter on w_pm???2 and yet retained a sufficient number of data points to average. A similarity relationship of w_pm???2 versus height was established for the mixed layer on the basis of the available data. A strong link between the SNR and growth/decay phases of turbulence was identified. Thus, the mid to late afternoon hours, when strong surface heating occurred, were observed to produce the highest quality signals.

Journal of Hydrologic Engineering↗
USGS2012

Limitations and potential of satellite imagery to monitor environmental response to coastal flooding

Storm-surge flooding and marsh response throughout the coastal wetlands of Louisiana were mapped using several types of remote sensing data collected before and after Hurricanes Gustav and Ike in 2008. These included synthetic aperture radar (SAR) data obtained from the (1) C-band advance SAR (ASAR) aboard the Environmental Satellite, (2) phased-array type L-band SAR (PALSAR) aboard the Advanced Land Observing Satellite, and (3) optical data obtained from Thematic Mapper (TM) sensor aboard the Land Satellite (Landsat). In estuarine marshes, L-band SAR and C-band ASAR provided accurate flood extent information when depths averaged at least 80 cm, but only L-band SAR provided consistent subcanopy detection when depths averaged 50 cm or less. Low performance of inundation mapping based on C-band ASAR was attributed to an apparent inundation detection limit (>30 cm deep) in tall Spartina alterniflora marshes, a possible canopy collapse of shoreline fresh marsh exposed to repeated storm-surge inundations, wind-roughened water surfaces where water levels reached marsh canopy heights, and relatively high backscatter in the near-range portion of the SAR imagery. A TM-based vegetation index of live biomass indicated that the severity of marsh dieback was linked to differences in dominant species. The severest impacts were not necessarily caused by longer inundation but rather could be caused by repeated exposure of the palustrine marsh to elevated salinity floodwaters. Differential impacts occurred in estuarine marshes. The more brackish marshes on average suffered higher impacts than the more saline marshes, particularly the nearshore coastal marshes occupied by S. alterniflora.

Journal of Coastal Research↗
USGS2025

Assessing causes and consequences of winter surface water dynamics in California’s Central Valley using satellite remote sensing

California's Central Valley is increasingly vulnerable to winter floods. A comprehensive spatial baseline of flood extents is critical for inundation analyses that can enhance future flood predictions, but cloud cover has prevented the regular observation of surface water extents with optical satellite imagery. In this study, we leveraged the daily resolution of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data to create a continuous series of monthly Dynamic Surface Water Extent (DSWEmod) images across the Central Valley from January 2003 to January 2023. We used the timeseries to assess the climatic driving forces of winter (Oct–April) surface water variability at sub-basin and pixel scales. At the sub-basin scale, we evaluated the influences of winter precipitation, occurrence of atmospheric rivers, and antecedent soil moisture on monthly surface water extents and found that the greatest correspondence occurs in mid-winter (Dec–Feb); in contrast, non-precipitation drivers such as water management play a stronger role in autumn and spring. The pixel-level analysis identified the probabilities of precipitation-driven surface water occurrences in the Sacramento basin are highest along rivers, conveyance channels, and floodways, with higher probabilities under wetter antecedent soil moisture conditions. Precipitation-driven surface water occurrences are also common in leveed areas and outside flood boundaries designated by state and federal agencies where exposure of structures to inundation was larger in terms of their value. Finally, areas with more frequent precipitation-driven flooding have poor recharge potential but are commonly within 5 km of areas classified as having good potential. This study demonstrates a novel approach for exploring the utility of MODIS for understanding surface water dynamics in mid-winter, a period characterized by peak precipitation, flood risk, and surface water extent. This information can provide valuable insights for (1) assessing flood risks for infrastructure and populations, (2) identifying areas most suited to strategic water management investments to increase recharge, and (3) analyzing precipitation thresholds that trigger flooding to allow proactive water management strategies to minimize damage and maximize recharge.

California↗
USGS2014

Modeling vegetation heights from high resolution stereo aerial photography: an application for broad-scale rangeland monitoring

Vertical vegetation structure in rangeland ecosystems can be a valuable indicator for assessing rangeland health and monitoring riparian areas, post-fire recovery, available forage for livestock, and wildlife habitat. Federal land management agencies are directed to monitor and manage rangelands at landscapes scales, but traditional field methods for measuring vegetation heights are often too costly and time consuming to apply at these broad scales. Most emerging remote sensing techniques capable of measuring surface and vegetation height (e.g., LiDAR or synthetic aperture radar) are often too expensive, and require specialized sensors. An alternative remote sensing approach that is potentially more practical for managers is to measure vegetation heights from digital stereo aerial photographs. As aerial photography is already commonly used for rangeland monitoring, acquiring it in stereo enables three-dimensional modeling and estimation of vegetation height. The purpose of this study was to test the feasibility and accuracy of estimating shrub heights from high-resolution (HR, 3-cm ground sampling distance) digital stereo-pair aerial images. Overlapping HR imagery was taken in March 2009 near Lake Mead, Nevada and 5-cm resolution digital surface models (DSMs) were created by photogrammetric methods (aerial triangulation, digital image matching) for twenty-six test plots. We compared the heights of individual shrubs and plot averages derived from the DSMs to field measurements. We found strong positive correlations between field and image measurements for several metrics. Individual shrub heights tended to be underestimated in the imagery, however, accuracy was higher for dense, compact shrubs compared with shrubs with thin branches. Plot averages of shrub height from DSMs were also strongly correlated to field measurements but consistently underestimated. Grasses and forbs were generally too small to be detected with the resolution of the DSMs. Estimates of vertical structure will be more accurate in plots having low herbaceous cover and high amounts of dense shrubs. Through the use of statistically derived correction factors or choosing field methods that better correlate with the imagery, vegetation heights from HR DSMs could be a valuable technique for broad-scale rangeland monitoring needs.

California;Nevada↗
USGS1996

Preflight and in-flight calibration plan for ASTER

Preflight and in-flight radiometric calibration plans are described for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) that is a multispectral optical imager of high spatial resolution. It is designed for the remote sensing from orbit of land surfaces and clouds, and is expected to be launched in 1998 on NASA's EOS AM-I spacecraft. ASTER acquires images in three separate spectral regions, the visible and near-infrared (VNIR), the shortwave infrared (SWIR), and the thermal infrared (TIR) with three imaging radiometer subsystems. The absolute radiometric accuracy is required to be better than 4% for VNIR and SWIR radiance measurements and 1 to 3 K, depending on the temperature regions from 200 to 370 K, for TIR temperature measurements. A reference beam is introduced at the entrance pupil of each imaging radiometer to provide the in-flight calibration. Thus, the ASTER instrument includes internal onboard calibration units that comprise incandescent lamps for the VNIR and SWIR and a blackbody radiator for the TIR as reference sources. The calibration reliability of the VNIR and SWIR is enhanced by a dual system of onboard calibration units as well as by high-stability halogen lamps. A ground calibration system of spectral radiances traceable to fixed-point blackbodies is used for the preflight VNIR and SWIR calibration. Because of the possibility of nonuniform contamination effects on the partial-aperture onboard calibration, it is desirable to check their results with respect to other methods. Reflectance- and radiance-based vicarious methods have been developed for this purpose. These, and methods involving in-flight cross-calibration with other sensors are also described.

Journal of Atmospheric and Oceanic Technology↗
USGS2025

The ghost plume phenomenon and its impact on zenith-facing remote sensing measurements of volcanic SO2 emission rates

A large source of error in SO 2 emission rates derived from mobile Differential Optical Absorption Spectroscopy (DOAS) of volcanic gas plumes is the uncertainty in atmospheric light paths between the sun and the instrument, particularly under non-ideal atmospheric conditions, such as the presence of low clouds. DOAS instruments measure the SO 2 column density along the effective light path, so changes to that pathway directly affect the measured SO 2 signal. Due to complex radiative transfer mechanisms when a cloud is between the DOAS viewing position and a volcanic plume, measured plumes can appear spatially offset from their true location, a phenomenon informally referred to as “ghost plumes.” In addition to the appearance of ghost plumes, DOAS measurements recorded in non-ideal conditions have poorly characterized errors and are often discarded, limiting the data available to characterize volcanic degassing. In this study we simulate the radiative transfer associated with zenith-facing mobile DOAS traverses using the McArtim radiative transfer model for scenarios when there is a cloud layer between the instrument and the volcanic plume. In total, 217 permutations of atmospheric optical conditions are considered with varying cloud opacities (AOD = 0, 1, 2, 4, 8, 20), plume opacities (AOD = 0, 1, 2, 4, 8), solar zenith angles (SZA = 1°, 30°, 60°), and cloud thicknesses (200, 400, 800 m). We first develop objective criteria for selecting SO 2 baseline absorption levels and plume spatial extents. The simulated plume traverses are then integrated to obtain the SO 2 cross-sectional burdens which, after multiplication with the wind speed, yield SO 2 emission rates. We find large modification in the shape of the modeled cross-sectional burdens even under translucent (low AOD) cloud conditions in our modeled scenarios. Despite modification of the plume shape, the presence of a low cloud layer is typically not a large source of error in the SO 2 cross-sectional burden or emission rate obtained from zenith-facing DOAS traverses. We find that all measured cross-sectional burdens simulated using an aerosol-free plume in the above conditions and SZA ≤ 30° are within ±25% of the true value.

Journal of Volcanology and Goethermal Research↗
USGS2024

Using remote sensing to identify habitat for wintering Henslow's Sparrows (Centronyx henslowii)

The Henslow's Sparrow ( Centronyx henslowii ) is a grassland bird species that overwinters in the southeastern United States and is a species of conservation concern due to population declines primarily caused by habitat loss. Henslow's Sparrows often overwinter in marginal habitats, such as powerline rights-of-way (ROWs), clear cuts, and field edges that provide some of their desired habitat characteristics, such as low-to-no tree cover and a diverse herbaceous understory. Using remote sensing methods, we evaluated the habitat characteristics of Henslow's Sparrow–occupied ROWs in southeastern Georgia. We calculated 22 satellite imagery metrics from Sentinel 2-L2 10 m resolution imagery, including single-pixel variables (e.g., Enhanced Vegetation Index, EVI) as well as “image texture” metrics that represent spatial heterogeneity. Using Random Forest models, we evaluated whether satellite imagery metrics could be used to discriminate between Henslow's Sparrow used areas (delineated from telemetry data) and surrounding available areas. Satellite imagery metrics were successful in predicting habitat characteristics in the ROWs (as evaluated by out-of-bag error and 3 goodness-of-fit tests), with image texture metrics performing better than single-pixel metrics. Image texture metrics were 9 of the top 10 most important predictors of habitat use in the best performing model that had a 500 m available buffer around use areas (out-of-bag error rate 21.21%). The most important image texture metric, cluster shade, was positively correlated with tree cover; Henslow's Sparrows were more likely to use areas with intermediate levels of cluster shade. From our results, we concluded that image texture metrics derived from 10 m satellite imagery could be used to predict sites that have suitable overwintering habitat for Henslow's Sparrows, but only at coarse resolutions and broader extents (hundreds of meters to kilometers). Therefore, this tool could be used to identify other ROWs (and possibly non-ROWs) with habitat that may support this and other declining grassland species.

Georgia↗
USGS2017

The study of fresh-water lake ice using multiplexed imaging radar

The study of ice in the upper Great Lakes, both from the operational and the scientific points of view, is receiving continued attention. Quantitative and qualitative field work is being conducted to provide the needed background for accurate interpretation of remotely sensed data. The data under discussion in this paper were obtained by a side-looking multiplexed airborne radar (SLAR) supplemented with ground-truth data. Because of its ability to penetrate adverse weather, radar is an especially important instrument for monitoring ice in the upper Great Lakes. It has previously been shown that imaging radars can provide maps of ice cover in these areas. However, questions concerning both the nature of the surfaces reflecting radar energy and the interpretation of the radar imagery continually arise. Our analysis of ice in Whitefish Bay (Lake Superior) indicates that the combination of the ice/water interlace and the ice/air interface is the major contributor to the radar backscatter as seen on the imagery At these frequencies the ice has a very low relative dielectric permittivity (< 3.0) and a low loss tangent Thus, this ice is somewhat transparent to the energy used by the imaging SLAR system. The ice types studied include newly formed black ice, pancake ice, and frozen and consolidated pack and brash ice. Although ice thickness cannot be measured directly from the received signals, it is suspected that by combining the information pertaining to radar backscatter with data on the meteorological and sea-state history of the area, together with some basic ground truth, better estimates of the ice thickness may be provided. In addition, certain ice features (e.g. ridges, ice-foot formation, areas of brash ice) may be identified with reasonable confidence. There is a continued need for additional ground work to verify the validity of imaging radars for these types of interpretations.

Upper Great Lakes↗
USGS2000

Estimation of wave phase speed and nearshore bathymetry from video imagery

A new remote sensing technique based on video image processing has been developed for the estimation of nearshore bathymetry. The shoreward propagation of waves is measured using pixel intensity time series collected at a cross-shore array of locations using remotely operated video cameras. The incident band is identified, and the cross-spectral matrix is calculated for this band. The cross-shore component of wavenumber is found as the gradient in phase of the first complex empirical orthogonal function of this matrix. Water depth is then inferred from linear wave theory's dispersion relationship. Full bathymetry maps may be measured by collecting data in a large array composed of both cross-shore and longshore lines. Data are collected hourly throughout the day, and a stable, daily estimate of bathymetry is calculated from the median of the hourly estimates. The technique was tested using 30 days of hourly data collected at the SandyDuck experiment in Duck, North Carolina, in October 1997. Errors calculated as the difference between estimated depth and ground truth data show a mean bias of −35 cm (rms error = 91 cm). Expressed as a fraction of the true water depth, the mean percent error was 13% (rms error = 34%). Excluding the region of known wave nonlinearities over the bar crest, the accuracy of the technique improved, and the mean (rms) error was −20 cm (75 cm). Additionally, under low-amplitude swells (wave height H ≤ 1 m), the performance of the technique across the entire profile improved to 6% (29%) of the true water depth with a mean (rms) error of −12 cm (71 cm).

North Carolina↗
USGS2023

AIMS for wildlife: Developing an automated interactive monitoring system to integrate real-time movement and environmental data for true adaptive management

To effectively manage species and habitats at multiple scales, population and land managers require rapid information on wildlife use of managed areas and responses to landscape conditions and management actions. GPS tracking studies of wildlife are particularly informative to species ecology, habitat use, and conservation. Combining GPS data with administrative data and a diverse suite of remotely sensed, geo-referenced environmental (e.g., climatic) data, would more comprehensively inform how animals interact with and utilize habitats and ecosystems and our goal was to create a conceptual model for a system that would accomplish this – the ‘Automated Interactive Monitoring System (AIMS) for Wildlife’. Our objective for this study was to develop a Customized Wildlife Report (CWR) - the first AIMS for Wildlife deliverable product. CWRs collate and summarize our 8-year GPS tracking dataset of ∼11 million locations from 1338 individual (16 species) avifauna and make actionable, real-time data on animal movements and trends in a specific area of interest available to managers and stakeholders for rapid application in day-to-day management. The CWR exemplar presented in this paper was developed to address needs identified by habitat managers of Sacramento National Wildlife Refuge and illustrates the highly specific, information offered and how it contributes to assessing the efficacy of conservation actions while allowing for near real-time adaptive management. The report can be easily customized for any of the thousands of wildlife refuges or regional areas of interest in the United States, emphasizing the broad application of an animal movement data stream. Utilizing diverse, extensive telemetry data streams through scientific collaboration can aid managers and conservation stakeholders with short and long-term research and conservation planning and help address a cadre of issues from local-scale habitat management to improving the understanding of landscape level impacts like drought, wildfire, and climate change on wildlife populations.

Journal of Environmental Management↗
USGS2020

Combining ash analyses with remote sensing to identify juvenile magma involvement and fragmentation mechanisms during the 2018/19 small eruption of Peteroa volcano (Southern Andes)

The Planchón Peteroa Volcanic Complex (PPVC) is located on the border of Chile and Argentina, and is one of the most active volcanic systems in the Andes. Holocene activity has included magma-water interaction with an evolving series of crater lakes, mainly sourced from Peteroa volcano. This study examines data from the 2018/19 eruption, together with the volcanic history of the PPVC, to elucidate the complex interplay between magmatic activity and summit water and ice. From February 2016 to mid-2019, three seismic swarms occurred in the PPVC, preceding the explosive eruption from September 2018 to April 2019. The activity originated from a small vent nested within the easternmost crater, the most active portion of the complex (Peteroa). The explosions interacted with a crater lake, producing ash plumes up to 2 km above the crater and building a small tephra cone. To investigate the eruption mechanisms, we performed remote sensing analysis of plume dispersal, thermal anomalies and ground deformation, and characterized the volcanic products, including grain size, componentry, morphology, internal textures, composition and mineralogy. Our results suggest that the precursory seismicity beginning in 2016 was related to the intrusion of a new magma batch that reached the surface during the 2018/19 eruption. The eruption was also preceded by thermal anomalies, geomorphic changes and increased hydrothermal activity at the surface, though without any ground deformation recognized through radar interferometry (InSAR). The eruption initially produced predominantly recycled ash (phreatic activity), then evolved to increasing proportions of juvenile magma (phreatomagmatic) by April 2019. The juvenile clasts had a trachyandesite composition (~59 wt% SiO 2 ), with vesicular and dense scoria containing plagioclase and pyroxene. The ash surfaces show external quenching cracks and step fractures consistent with phreatomagmatic fragmentation within the active crater lake. Textural characteristics also point to a slowly ascending batch of magma that was relatively viscous by the time it interacted with water in the crater lake. Notably, these juvenile particles are distinctive from the pre-2018 products. Ash erupted from 2010/11 did not contain recognizable juvenile material, and is inferred to have been a mainly phreatic eruption. Our findings suggest that the interplay between phreatic and phreatomagmatic eruptions fed by small magma batches intruding at shallow levels characterize much of the eruptive behavior of the PPVC during the last three decades. Multi-parametric assessment is a powerful tool to discriminate between phreatic and phreatomagmatic eruptions.

Southern Andes↗
USGS2012

Use of ASTER and MODIS thermal infrared data to quantify heat flow and hydrothermal change at Yellowstone National Park

The overarching aim of this study was to use satellite thermal infrared (TIR) remote sensing to monitor geothermal activity within the Yellowstone geothermal area to meet the missions of both the U.S. Geological Survey and the Yellowstone National Park Geology Program. Specific goals were to: 1) address the challenges of monitoring the surface thermal characteristics of the > 10,000 spatially and temporally dynamic thermal features in the Park (including hot springs, pools, geysers, fumaroles, and mud pots) that are spread out over ~ 5000 km 2 , by using satellite TIR remote sensing tools (e.g., ASTER and MODIS), 2) to estimate the radiant geothermal heat flux (GHF) for Yellowstone's thermal areas, and 3) to identify normal, background thermal changes so that significant, abnormal changes can be recognized, should they ever occur (e.g., changes related to tectonic, hydrothermal, impending volcanic processes, or human activities, such as nearby geothermal development). ASTER TIR data (90-m pixels) were used to estimate the radiant GHF from all of Yellowstone's thermal features and update maps of thermal areas. MODIS TIR data (1-km pixels) were used to record background thermal radiance variations from March 2000 through December 2010 and establish thermal change detection limits. A lower limit for the radiant GHF estimated from ASTER TIR temperature data was established at ~ 2.0 GW, which is ~ 30–45% of the heat flux estimated through geochemical thermometry. Also, about 5 km 2 of thermal areas was added to the geodatabase of mapped thermal areas. A decade-long time-series of MODIS TIR radiance data was dominated by seasonal cycles. A background subtraction technique was used in an attempt to isolate variations due to geothermal changes. Several statistically significant perturbations were noted in the time-series from Norris Geyser Basin, however many of these did not correspond to documented thermal disturbances. This study provides concrete examples of the strengths and limitations of current satellite TIR monitoring of geothermal areas, highlighting some specific areas that can be improved. This work provides a framework for future satellite-based thermal monitoring at Yellowstone and other volcanic and geothermal systems.

Idaho, Montana, Oregon, Wyoming↗