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At least 127 records · Page 7Linked to original sources

Predicted aquatic exposure effects from a national urban stormwater study

A multi-agency study of 438 organic and 62 inorganic chemicals measured in urban stormwater during 50 total runoff events at 21 sites across the United States demonstrated that stormwater discharges can generate localized, aquatic exposures to extensive contaminant mixtures, including organics suspected to cause adverse aquatic-health effects. The aggregated risks to multiple aquatic trophic levels (fish, invertebrates, plants) of the stormwater mixture exposures, which were documented in the national study, were explored herein by calculating cumulative ratios of organic-contaminant in vitro exposure–activity cutoffs (∑ EAR ) and health-benchmark-weighted cumulative toxicity quotients (∑ TQ ). Both risk assessment approaches indicated substantial (moderate to high) risk for acute adverse effects to aquatic organisms across multiple trophic levels (fish, macroinvertebrates, non-vascular/vascular plants) at or near stormwater discharge points across the United States. The results are interpreted as potential orders of magnitude underestimates of actual aquatic risk in stormwater control wetlands or in the immediate vicinity of such discharges to surface-water receptors, because the 438 organic-compound analytical space assessed in this study is orders of magnitude less than the 350 000 parent compounds estimated to be in current commercial use globally and the incalculable chemical-space of potential metabolites and degradates.

Environmental Science: Water Research and Technolo

Environmentalism and natural aggregate mining

Sustaining a developed economy and expanding a developing one require the use of large volumes of natural aggregate. Almost all human activity (commercial, recreational, or leisure) is transacted in or on facilities constructed from natural aggregate. In our urban and suburban worlds, we are almost totally dependent on supplies of water collected behind dams and transported through aqueducts made from concrete. Natural aggregate is essential to the facilities that produce energy—hydroelectric dams and coal-fired powerplants. Ironically, the utility created for mankind by the use of natural aggregate is rarely compared favorably with the environmental impacts of mining it. Instead, the empty quarries and pits are seen as large negative environmental consequences. At the root of this disassociation is the philosophy of environmentalism, which flavors our perceptions of the excavation, processing, and distribution of natural aggregate. The two end-member ideas in this philosophy are ecocentrism and anthropocentrism. Ecocentrism takes the position that the natural world is a organism whose arteries are the rivers—their flow must not be altered. The soil is another vital organ and must not be covered with concrete and asphalt. The motto of the ecocentrist is “man must live more lightly on the land.” The anthropocentrist wants clean water and air and an uncluttered landscape for human use. Mining is allowed and even encouraged, but dust and noise from quarry and pit operations must be minimized. The large volume of truck traffic is viewed as a real menace to human life and should be regulated and isolated. The environmental problems that the producers of natural aggregate (crushed stone and sand and gravel) face today are mostly difficult social and political concerns associated with the large holes dug in the ground and the large volume of heavy truck traffic associated with quarry and pit operations. These concerns have increased in recent years as society's demand for living space has encroached on the sites of production; in other words, the act of production has engendered condemnation. Many other environmental problems that are associated with dust and noise and blasting from quarry and pit operations have been reduced through the efficient use of technology. Recycling concrete in buildings, bridges, and roads and asphaltic pavements will ultimately reduce the demand for virgin natural aggregate. The impact created by the large holes in the ground required for the mining of natural aggregate can be greatly reduced by planning their reclamation before mining begins.

Natural Resources Research

Occupancy models for citizen-science data

Large‐scale citizen‐science projects, such as atlases of species distribution, are an important source of data for macroecological research, for understanding the effects of climate change and other drivers on biodiversity, and for more applied conservation tasks, such as early‐warning systems for biodiversity loss. However, citizen‐science data are challenging to analyse because the observation process has to be taken into account. Typically, the observation process leads to heterogeneous and non‐random sampling, false absences, false detections, and spatial correlations in the data. Increasingly, occupancy models are being used to analyse atlas data. We advocate a dual approach to strengthen inference from citizen science data for the questions the programme is intended to address: (a) the survey design should be chosen with a particular set of questions and associated analysis strategy in mind and (b) the statistical methods should be tailored not only to those questions but also to the specific characteristics of the data. We review the consequences of particular survey design choices that typically need to be made in atlas‐style citizen‐science projects. These include spatial resolution of the sampling units, allocation of effort in space, and collection of information about the observation process. On the analysis side, we review extensions of the basic occupancy models that are frequently necessary with atlas data, including methods for dealing with heterogeneity, non‐independent detections, false detections, and violation of the closure assumption. New technologies, such as cell‐phone apps and fixed remote detection devices, are revolutionizing citizen‐science projects. There is an opportunity to maximize the usefulness of the resulting datasets if the protocols are rooted in robust statistical designs and data analysis issues are being considered. Our review provides guidelines for designing new projects and an overview of the current methods that can be used to analyse data from such projects.

Methods in Ecology and Evolution

The U.S. Geological Survey Land Remote Sensing Program

In 2002, the U. S. Geological Survey (USGS) launched a program to enhance the acquisition, preservation, and use of remotely sensed data for USGS science programs, as well as for those of cooperators and customers. Remotely sensed data are fundamental tools for studying the Earth's land surface, including coastal and near-shore environments. For many decades, the USGS has been a leader in providing remotely sensed data to the national and international communities. Acting on its historical topographic mapping mission, the USGS has archived and distributed aerial photographs of the United States for more than half a century. Since 1972, the USGS has acquired, processed, archived, and distributed Landsat and other satellite and airborne remotely sensed data products to users worldwide. Today, the USGS operates and manages the Landsats 5 and 7 missions and cooperates with the National Aeronautics and Space Administration (NASA) to define and implement future satellite missions that will continue and expand the collection of moderate-resolution remotely sensed data. In addition to being a provider of remotely sensed data, the USGS is a user of these data and related remote sensing technology. These data are used in natural resource evaluations for energy and minerals, coastal environmental surveys, assessments of natural hazards (earthquakes, volcanoes, and landslides), biological surveys and investigations, water resources status and trends analyses and studies, and geographic and cartographic applications, such as wildfire detection and tracking and as a source of information for The National Map. The program furthers these distinct but related roles by leading the USGS activities in providing remotely sensed data while advancing applications of such data for USGS programs and a wider user community.

Fact Sheet

A probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention

The U.S. Energy Independence and Security Act of 2007 authorized the U.S. Geological Survey (USGS) to conduct a national assessment of the potential volume of hydrocarbons recoverable by injection of carbon dioxide (CO 2 ) into known oil reservoirs with historical production. The implementation of CO 2 enhanced oil recovery (CO 2 -EOR) techniques could increase the U.S. recoverable hydrocarbon resource base. Use of anthropogenic CO 2 in the CO 2 -EOR process could reduce the amount of CO 2 released to the atmosphere by allowing a percentage of the injected CO 2 to remain in reservoir pore space once occupied by produced oil and water or by CO 2 dissolution in oil and water in the reservoir. The USGS has developed a new methodology for the national assessment of technically recoverable oil resources that may be produced by using current CO 2 -EOR technologies. The methodology relies on a proprietary reservoir-level database, the comprehensive resource database (CRD). The CRD incorporates commercially available geologic and engineering data, and USGS-defined play averages or province averages of reservoir data were used to populate incomplete records. Values from the CRD are used to estimate the original oil in place ( OOIP ) for each reservoir. The inputs are reviewed by USGS geologists, particularly when play or province averages have been used. Monte Carlo simulation is used to produce a numerical probability distribution for the OOIP for each reservoir, with the mean defined as the value of the OOIP in the CRD. A reservoir model (CO 2 Prophet, developed for the U.S. Department of Energy by Texaco, Inc.) is used to determine the incremental recovery factors for oil during the CO 2 -EOR process, on an individual reservoir basis. The model is also used to estimate the volume of CO 2 remaining in the reservoir after the CO 2 -EOR process is complete. Empirical decline curve analysis and comparison with data from published papers and reports on CO 2 -EOR projects are utilized to substantiate the simulation results. Numerical distributions of recovery factors are prepared for variations in the reservoir lithology (clastic or carbonate). The distribution of incremental oil is computed by multiplying the appropriate probability distribution of recovery factors by the individual reservoir distribution of the OOIP . A way to estimate the CO 2 remaining in the reservoir after the completion of the CO 2 -EOR process is also included in the methodology. Assessment results will be aggregated to play, petroleum province, regional, and national scales. This assessment methodology has been tested on the Horseshoe Atoll, Upper Pennsylvanian-Wolfcampian play in the Permian Basin Province in Texas; the play consists of 27 reservoirs having at least 2 billion barrels of OOIP that are amenable to the CO 2 -EOR process. The play was selected as a test case because CO 2 -EOR production data and published reports are available for several reservoirs within the play. Preliminary estimates of oil recoverable by implementation of miscible CO 2 -EOR are comparable to those reported in the literature and obtained by reservoir decline curve analysis.

Scientific Investigations Report

White-tailed deer movements and space use on Fire Island: A four-year radio-telemetry study 2015-2016 post-Hurricane Sandy assessment

Hurricane Sandy provided a unique opportunity to better understand the movements of Fire Island’s dense white-tailed deer (Odocoileus virginianus borealis) herds. White-tailed deer inhabit all areas of Fire Island National Seashore and their high densities negatively affect native vegetation in several areas of the island, especially as disturbed areas attempt to recover after a catastrophic storm like Hurricane Sandy. Understanding deer movements and space use helps land managers to prioritize white-tailed deer population size and the health and recovery potential of Fire Island’s natural lands according to their management goals. The results of this study will inform Fire Island staff as they prepare to initiate the tasks set forth by the Seashore’s approved Deer Management Plan. We used radio-collars fitted with Very High Frequency (VHF) signal and Global Positioning System (GPS) technology to monitor movements of white-tailed deer for four years after Hurricane Sandy. The greatest movements of Fire Island’s adult female white-tailed deer occurred in spring each year. Home range and core area sizes varied among study areas and years, but suggested hierarchical dominance among Fire Island’s deer populations. Potentially six distinct populations were delineated through analysis of GPS radio-collar data, though these divisions also reflect the concentrated sampling efforts of deer capture. Nearly all deer monitored shared time between natural and nearby built environments. Since Hurricane Sandy, deer movements in Fire Island’s Wilderness are divided by the storm-induced breach. GPS radio-collars provided a wealth of data for analysis of deer movements and space use, and this report is simply a snapshot of the potential information we intend to gain from this study.

New York

Hydrophone placement yields high variability in detection of Epinephelus striatus calls at a spawning site.

Passive acoustic monitoring is a cost-effective, minimally invasive technology commonly used to study behavior and population dynamics of soniferous fish species. To understand the strengths and limitations of acoustic monitoring for this purpose at fish spawning aggregations (FSA) requires an assessment of the variability in aggregation-associated sounds (AAS) as a function of time, space, and proximity for spawning fishes of interest. Here, we evaluate temporal and spatial trends in the detection of AAS by Nassau Grouper ( Epinephelus striatus ) using an array of six hydrophones deployed across a large Nassau Grouper FSA at Little Cayman, Cayman Islands. We collected continuous data for nine days during a winter spawning season and subsequently used an automatic classifier to extract the embedded Nassau Grouper AAS. Using these data, we analyzed variability in spatiotemporal AAS detection rates across the array with a Bayesian mixed effects model. We found high variability in the detection of AAS across the spawning site, with positive correlations among neighboring hydrophone pairs trending toward negative correlations with distances exceeding 350 m. Indeed, temporal trends in AAS rates at the spawning site were approximately inverted at the two most distant hydrophones (~600 m). Across the hydrophone network, our model predicted strong positive effects of fish proximity, spawning behavior, and crepuscular periods on detected AAS. Our findings suggest hydrophone placement can strongly influence AAS detection rates and even basic temporal patterns in AAS across the spawning season. Given both the vagaries of movement and behavior of aggregating fish at spawning sites and the limits of AAS detection using standard monitoring tools, we suggest spawning site acoustic monitoring programs deploy hydrophone arrays of sufficient size to capture the site-wide trends in AAS rates if possible; this is particularly true if researchers hope to compare/contrast AAS rates between spawning sites or across seasons for the purpose of population assessment.

Ecological Applications

Spatially explicit modeling in ecology: A review

The use of spatially explicit models (SEMs) in ecology has grown enormously in the past two decades. One major advancement has been that fine-scale details of landscapes, and of spatially dependent biological processes, such as dispersal and invasion, can now be simulated with great precision, due to improvements in computer technology. Many areas of modeling have shifted toward a focus on capturing these fine-scale details, to improve mechanistic understanding of ecosystems. However, spatially implicit models (SIMs) have played a dominant role in ecology, and arguments have been made that SIMs, which account for the effects of space without specifying spatial positions, have an advantage of being simpler and more broadly applicable, perhaps contributing more to understanding. We address this debate by comparing SEMs and SIMs in examples from the past few decades of modeling research. We argue that, although SIMs have been the dominant approach in the incorporation of space in theoretical ecology, SEMs have unique advantages for addressing pragmatic questions concerning species populations or communities in specific places, because local conditions, such as spatial heterogeneities, organism behaviors, and other contingencies, produce dynamics and patterns that usually cannot be incorporated into simpler SIMs. SEMs are also able to describe mechanisms at the local scale that can create amplifying positive feedbacks at that scale, creating emergent patterns at larger scales, and therefore are important to basic ecological theory. We review the use of SEMs at the level of populations, interacting populations, food webs, and ecosystems and argue that SEMs are not only essential in pragmatic issues, but must play a role in the understanding of causal relationships on landscapes.

Ecosystems

Estimating animal resource selection from telemetry data using point process models

Analyses of animal resource selection functions (RSF) using data collected from relocations of individuals via remote telemetry devices have become commonplace. Increasing technological advances, however, have produced statistical challenges in analysing such highly autocorrelated data. Weighted distribution methods have been proposed for analysing RSFs with telemetry data. However, they can be computationally challenging due to an intractable normalizing constant and cannot be aggregated (i.e. collapsed) over time to make space-only inference. In this study, we take a conceptually different approach to modelling animal telemetry data for making RSF inference. We consider the telemetry data to be a realization of a space–time point process. Under the point process paradigm, the times of the relocations are also considered to be random rather than fixed. We show the point process models we propose are a generalization of the weighted distribution telemetry models. By generalizing the weighted model, we can access several numerical techniques for evaluating point process likelihoods that make use of common statistical software. Thus, the analysis methods can be readily implemented by animal ecologists. In addition to ease of computation, the point process models can be aggregated over time by marginalizing over the temporal component of the model. This allows a full range of models to be constructed for RSF analysis at the individual movement level up to the study area level. To demonstrate the analysis of telemetry data with the point process approach, we analysed a data set of telemetry locations from northern fur seals (Callorhinus ursinus) in the Pribilof Islands, Alaska. Both a space–time and an aggregated space-only model were fitted. At the individual level, the space–time analysis showed little selection relative to the habitat covariates. However, at the study area level, the space-only model showed strong selection relative to the covariates.

Alaska

Gravity and magnetic surveys of the Skaergaard intrusion, East Greenland

Aeromagnetic and gravity surveys of the Skaergaard intrusion in East Greenland were carried out in July–August 1971 as part of a grant to the University of Oregon Center for Volcanology to refine the models of crystallization and differentiation of the intrusion, specifically to test whether the intrusion is underlain by dense rocks of a reservoir 20 kilometers (km) thick (referred to as a “hidden zone”). The Skaergaard intrusion is a source of platinum group elements that are critical mineral resources for many technologies, and because no new data have been collected these legacy datasets remain a valuable asset. The total-intensity aeromagnetic survey was flown in early July 1971 with a proton precession magnetometer at a constant barometric altitude of 1.5 km (5,000 feet) with a nominal line spacing of 1 km. Two gravimeters were used to acquire 168 stations of which 86 were at known altitudes (mainly sea level) and 82 had altitudes measured by altimetry in late July–August 1971. Finally, a north-south ground vertical-intensity magnetic traverse was completed across the intrusion together with collection of oriented hand specimens. The hand specimens were measured for remnant magnetization and density, along with density measurements of more specimens collected by expedition geologists for other purposes. The intrusion is composed of layered gabbro with extensive crystal fractionation that is dense and strongly reversely polarized. After terrain correction and standard Bouguer gravity reduction, the gravity anomaly dataset was corrected for all rock above sea level using the density measurements of the various zones of the intrusion and the topographic and geologic maps (variable density Bouguer gravity reduction). A large regional gradient in the gravity anomaly data was removed using orthogonal polynomial fitting to the gridded data. The zonal volumes of rock below sea level were calculated from the dipping polygonal layer gravity model of the intrusion below sea level and combined with elliptic cross–section cylinders for the various zones above sea level to approximate the original zonal volumes of the intrusion. The residual gravity anomaly of 18–20 milligals (mGal) was only about half of the expected anomaly if a large hidden zone proposed from petrologic considerations were present, and both two-dimensional and three-dimensional models imply that the exposed series of intrusion zones explain the gravity anomaly by their down-dip extension below sea level together with a small hidden-zone volume. A three-dimensional model of the exposed rocks and their down-dip extension below sea level also can account for the aeromagnetic anomaly with little or no requirement for hidden-zone rock. The middle and upper zone units of the intrusion contain the most magnetite and account for most of the aeromagnetic anomaly.

Skaergaard intrusion

Lunar grid systems, coordinate systems, and map projections for the Artemis missions and lunar surface navigation

Foreward This document contains design specifications of a navigational standard for the Moon, including a Lunar Transverse Mercator system, a Lunar Polar Stereographic system, a Lunar Grid Reference System, and a unique coordinate structure, Artemis Condensed Coordinates, for Artemis mission navigation and lunar surface science. The National Aeronautics and Space Administration (NASA) Artemis campaign seeks to place humans on the Moon for the first time since the Apollo missions. Early Artemis missions are heavily focused on the lunar south pole, which promises to return valuable data on the Moon’s geologic record, amongst other mission objectives. Coordinate systems in use today for the lunar south pole provides crew members on the surface neither an efficient nor intuitive means to communicate their position and orientation. A novel grid coordinate system, the Lunar Grid Reference System, is proposed to address these concerns for use in real-time extravehicular activity operations on the lunar surface. The many stakeholders involved in the Artemis missions will need a common system to communicate position and orientation while astronauts are operating on the lunar surface. To that end, Artemis crew members will need that system to be efficient and intuitive to promote efficient extravehicular activity timelines and reduce confusion. In the context of this document, these characteristics are addressed on the design of lunar coordinate systems: Efficient.—The number of characters required to communicate a location within a desired precision level in both local and global contexts, and how many steps are required for a recipient or sender to interpret a location. Intuitive.—How well the system aligns with human perceptual abilities, and whether the system yields distances that have the same relationship to actual lunar surface distance in all directions from the point where a person is located. Technological systems are currently being investigated to supplement the crew members’ ability to locate and orient themselves and other assets on the lunar surface; however, it is unlikely that those systems will be fully operational for the first few landed missions. Even with future positional aids, crew members will still need an efficient and intuitive means to communicate position and orientation. In addition, if technological systems fail, the crews will require land navigation skills and have maps available, thus providing further motivation for a crew-centric coordinate system. The contents of this U.S. Geological Survey (USGS) document detail a comprehensive framework for standardizing lunar crewed surface navigation within NASA and outlines the protocols, methods, and designs necessary for achieving consistency and interoperability across relevant space mission teams and lunar surface navigators. Key components of this document include designs of map projections, projected coordinate reference systems (Lunar Transverse Mercator and Lunar Polar Stereographic systems), and a grid system (Lunar Grid Reference System and Artemis Condensed Coordinates) for the Moon. The work proposed in this document seeks to accomplish something similar to the National Geospatial-Intelligence Agency (NGA) document SIG 0012 (NGA, 2014a), but for using grid systems for the Moon. This report incorporates initial feedback and input from NASA’s Artemis Geospatial Data Team, NASA’s Flight Operations Directorate, National Geodetic Survey, USGS Astrogeology Science Center, and NGA and is intended to serve as a resource for all involved with the Artemis missions, as well as for engineers designing and operating lunar infrastructure.

Techniques and Methods

Standard Reference Material (SRM 1990) for Single Crystal Diffractometer Alignment

An international project was successfully completed which involved two major undertakings: (1) a round-robin to demonstrate the viability of the selected standard and (2) the certification of the lattice parameters of the SRM 1990, a Standard Reference Material?? for single crystal diffractometer alignment. This SRM is a set of ???3500 units of Cr-doped Al2O3, or ruby spheres [(0 420.011 mole fraction % Cr (expanded uncertainty)]. The round-robin consisted of determination of lattice parameters of a pair of crystals' the ruby sphere as a standard, and a zeolite reference to serve as an unknown. Fifty pairs of crystals were dispatched from Hauptman-Woodward Medical Research Institute to volunteers in x-ray laboratories world-wide. A total of 45 sets of data was received from 32 laboratories. The mean unit cell parameters of the ruby spheres was found to be a=4.7608 A?? ?? 0.0062 A??, and c=12.9979 A?? ?? 0.020 A?? (95 % intervals of the laboratory means). The source of errors of outlier data was identified. The SRM project involved the certification of lattice parameters using four well-aligned single crystal diffractometers at (Bell Laboratories) Lucent Technologies and at NRC of Canada (39 ruby spheres), the quantification of the Cr content using a combined microprobe and SEM/EDS technique, and the evaluation of the mosaicity of the ruby spheres using a double-crystal spectrometry method. A confirmation of the lattice parameters was also conducted using a Guinier-Ha??gg camera. Systematic corrections of thermal expansion and refraction corrections were applied. These rubies_ are rhombohedral, with space group R3c. The certified mean unit cell parameters are a=4.76080 ?? 0.00029 A??, and c=12 99568 A?? ?? 0.00087 A?? (expanded uncertainty). These certified lattice parameters fall well within the results of those obtained from the international round-robin study. The Guinier-Ha??gg transmission measurements on five samples of powdered rubies (a=4.7610 A?? ?? 0.0013 A??, and c=12.9954 A?? ?? 0.0034 A??) agreed well with the values obtained from the single crystal spheres.

Journal of Research of the National Institute of S

Monitoring beach morphology changes using small-format aerial photography and digital softcopy photogrammetry

Current methods of monitoring beach morphology changes commonly involve the establishment of Global Positioning System profiles that are surveyed on a regular basis. Although this method produces precise measurements of coastal topography, it is costly in time and effort and may result in large data gaps between profiles. Much of our understanding of coastal dynamics is thus limited by profile spacing and survey frequency. Softcopy photogrammetry is increasingly being used as an alternative to assess shoreline change and study beach morphodynamics. This method of producing three-dimensional topographic models and orthophotographs from digitized aerial photography can aid in filling in the gaps between established profiles. A limiting factor to this technology is the cost of obtaining high-resolution aerial photography. We have developed an aerial mapping system designed to collect data in an efficient and cost-effective way. We use a small-format aerial photography system that can be mounted on a variety of small aircraft on short notice. After a flight, the photographs are scanned, and softcopy photogrammetry software is used to create both DTMs (Digital Terrain Models) and orthophotographs. The DTMs can be compared with existing profiles for accuracy, and volumetric changes can be computed. The orthophotos are used to make precise measurements of the position and morphology of shoreline features. This aerial mapping system is advantageous over previous methods of beach morphology change monitoring because it allows for rapid response to storm events and provides a cost-effective method of establishing a continual monitoring program in erosion hazard areas.

Environmental Geosciences

Automatic identification and quantification of volcanic hotspots in Alaska using HotLINK: The hotspot learning and identification network

An increase in volcanic thermal emissions can indicate subsurface and surface processes that precede, or coincide with, volcanic eruptions. Space-borne infrared sensors can detect hotspots—defined here as localized volcanic thermal emissions—in near-real-time. However, automatic hotspot detection systems are needed to efficiently analyze the large quantities of data produced. While hotspots have been automatically detected for over 20 years with simple thresholding algorithms, new computer vision technologies, such as convolutional neural networks (CNNs), can enable improved detection capabilities. Here we introduce HotLINK: the Hotspot Learning and Identification Network, a CNN trained to detect hotspots with a dataset of −3,800 satellite-based, Visible Infrared Imaging Radiometer Suite (VIIRS) images from Mount Veniaminof and Mount Cleveland volcanoes, Alaska. We find that our model achieves an accuracy of 96% (F1-score 0.92) when evaluated on −1,700 unseen images from the same volcanoes, and 95% (F1-score 0.67) when evaluated on −3,000 images from six additional Alaska volcanoes (Augustine Volcano, Bogoslof Island, Okmok Caldera, Pavlof Volcano, Redoubt Volcano, Shishaldin Volcano). In comparison with an existing threshold-based hotspot detection algorithm, MIROVA (Coppola et al., Geological Society, London, Special Publications, 2016, 426, 181–205), our model detects 22% more hotspots and produces 12% fewer false positives. Additional testing on −700 labeled Moderate Resolution Imaging Spectroradiometer (MODIS) images from Mount Veniaminof demonstrates that our model is applicable to this sensor’s data as well, achieving an accuracy of 98% (F1-score 0.95). We apply HotLINK to 10 years of VIIRS data and 22 years of MODIS data for the eight aforementioned Alaska volcanoes and calculate the radiative power of detected hotspots. From these time series we find that HotLINK accurately characterizes background and eruptive periods, similar to MIROVA, but also detects more subtle warming signals, potentially related to volcanic unrest. We identify three advantages to our model over its predecessors: 1) the ability to detect more subtle volcanic hotspots and produce fewer false positives, especially in daytime images; 2) probabilistic predictions provide a measure of detection confidence; and 3) its transferability, i.e., the successful application to multiple sensors and multiple volcanoes without the need for threshold tuning, suggesting the potential for global application.

Alaska

The EnMAP spaceborne imaging spectroscopy mission: Initial scientific results two years after launch

Imaging spectroscopy has been a recognized and established remote sensing technology since the 1980s, mainly using airborne and field-based platforms to identify and quantify key bio- and geo-chemical surface and atmospheric compounds, based on characteristic spectral reflectance features in the visible-near infrared (VNIR) and short-wave infrared (SWIR). Spaceborne missions, a leap in technology, were sparse, starting with the CHRIS/PROBA and EO1/Hyperion missions in the early 2000s, and providing spectroscopy data with limited spectral coverage and/or low data quality in the SWIR. Since 2019, several countries and agencies have successfully launched a number of spaceborne imaging spectroscopy systems into orbit or deployed them on the International Space Station (ISS) such as DESIS, PRISMA, HISUI, GF-5, EnMAP and EMIT. Among these recent missions, the German Environmental Mapping and Analysis Program (EnMAP) stands for its long-term development, sophisticated design with on-board calibration, high data quality requirements, and extensive accompanying science program. EnMAP was launched in April 2022 and, following a successful commissioning phase, started its operational activities in November 2022. The EnMAP mission encompasses global coverage from 80° N to 80° S through on-demand data acquisitions. Data are free and open access with 30 m spatial resolution, a high spectral resolution with a spectral sampling distance of 6.5 nm and 10 nm in the VNIR and SWIR regions respectively, and a high signal-to-noise ratio. In this paper, we aim to present the mission's current status, coverage, science capabilities and performance two years after launch. We show the potential of EnMAP for space-based imaging spectroscopy to operate in various environments, including high and low light levels, dense forests, Antarctic glaciers, and arid agricultural areas. EnMAP enables various applications in fields such as agriculture and forestry, soil compositional, raw materials, and methane mapping, as well as water quality assessment, and snow and ice properties. The results show that EnMAP's performance exceeds the mission requirements, and highlights the significant potential for contribution to scientific exploitation in various geo- and biochemical sciences. EnMAP is also expected to serve as a key tool for the development and testing of data processing algorithms for upcoming global operational missions.

Remote Sensing of Environment

Comparison of fluvial suspended-sediment concentrations and particle-size distributions measured with in-stream laser diffraction and in physical samples

Laser-diffraction technology, recently adapted for in-stream measurement of fluvial suspended-sediment concentrations (SSCs) and particle-size distributions (PSDs), was tested with a streamlined (SL), isokinetic version of the Laser In-Situ Scattering and Transmissometry (LISST) for measuring volumetric SSCs and PSDs ranging from 1.8-415 µm in 32 log-spaced size classes. Measured SSCs and PSDs from the LISST-SL were compared to a suite of 22 datasets (262 samples in all) of concurrent suspended-sediment and streamflow measurements using a physical sampler and acoustic Doppler current profiler collected during 2010-12 at 16 U.S. Geological Survey streamflow-gaging stations in Illinois and Washington (basin areas: 38 – 69,264 km 2 ). An unrealistically low computed effective density (mass SSC / volumetric SSC) of 1.24 g/ml (95% confidence interval: 1.05-1.45 g/ml) provided the best-fit value (R 2 = 0.95; RMSE = 143 mg/L) for converting volumetric SSC to mass SSC for over 2 orders of magnitude of SSC (12-2,170 mg/L; covering a substantial range of SSC that can be measured by the LISST-SL) despite being substantially lower than the sediment particle density of 2.67 g/ml (range: 2.56-2.87 g/ml, 23 samples). The PSDs measured by the LISST-SL were in good agreement with those derived from physical samples over the LISST-SL's measureable size range. Technical and operational limitations of the LISST-SL are provided to facilitate the collection of more accurate data in the future. Additionally, the spatial and temporal variability of SSC and PSD measured by the LISST-SL is briefly described to motivate its potential for advancing our understanding of suspended-sediment transport by rivers.

Water Resources Research

Agencies collaborate, develop a cyanobacteria assessment network

Cyanobacteria are a genetically diverse group of photosynthetic microorganisms that occupy a broad range of habitats on land and water all over the world. They release toxins that can cause lung and skin irritation, alter the taste and odor of potable water, and cause human and animal illness. Cyanobacteria blooms occur worldwide, and climate change may increase the frequency, duration, and extent of these bloom events. Rapid detection of potentially harmful blooms is essential to protect humans and animals from exposure. Information about potential for exposure, such as bloom duration, frequency, and extent, is especially critical for developing environmental management decisions during periods of limited resources and funding. The National Research Council (NRC) report Exposure Science in the 21st Century suggested that effectively assessing and mitigating exposures requires techniques for rapid measurement of a stressor, such as an algal bloom, across diverse geographic, temporal, and biologic scales (e.g., various bloom concentrations) and an enhanced infrastructure to address threats [ NRC , 2012]. The report specifically calls for approaches that use diverse information, such as satellite remote sensing, to identify and understand exposures that may pose a threat to ecosystems or human health. A collaborative effort integrates the work of the U.S. Environmental Protection Agency (EPA), NASA, the National Oceanic and Atmospheric Administration (NOAA), and the U.S. Geological Survey (USGS) to provide an approach for using satellite ocean color capabilities in U.S. fresh and brackish water quality management decisions. The overarching goal of this collaborative project is to detect and quantify cyanobacteria blooms using satellite data records in order to support the environmental management and public use of U.S. lakes and reservoirs. Satellite remote sensing tools may enable policy makers and environmental managers to assess the sustainability of watershed ecosystems and the services they provide, now and in the future. Satellite technology allows us to develop early-warning indicators of cyanobacteria blooms at the local scale while maintaining continuous national coverage.

Eos, Earth and Space Science News

Survey of remote sensing applications

Data from the first earth resources technology satellite (ERTS) as well as from NASA and other aircraft, contain much of the information indicative of the distribution of groundwater and the extent of its utilization. Thermal infrared imagery from aircraft is particularly valuable in studying groundwater discharge to the sea and other surface water bodies. Color infrared photography from aircraft and space is also used to locate areas of potential groundwater development. Anomalies in vegetation, soils, moisture, and their pattern of distribution may be indicative of underlying groundwater conditions. Remote sensing may be used directly or indirectly to identify stream reaches for test holes or production wells. Similarly, location of submarine springs increase effectiveness of groundwater exploration in the coastal zone.

Water Well Journal