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At least 91 records · Page 5Linked to original sources
USGS2002

Cooperative investigation of precision and accuracy in chemical analysis of silicate rocks

This is the preliminary report of the first extensive program ever organized to study the analysis of igneous rocks, a study sponsored by the United States Geological Survey, the Massachusetts Institute of Technology, and the Geophysical Laboratory of the Carnegie Institution of Washington. Large samples of two typical igneous rocks, a granite and a diabase, were carefully prepared and divided. Small samples (about 70 grams) of each were sent to 25 rock-analysis laboratories throughout the world; analyses of one or both samples were reported by 34 analysts in these laboratories. The results, which showed rather large discrepancies, are presented in histograms. The great discordance in results reflects the present unsatisfactory state of rock analysis. It is hoped that the ultimate establishment of standard samples and procedures will contribute to the improvement of quality of analyses. The two rock samples have also been thoroughly studied spectrographically and petrographically. Detailed reports of all the studies will be published.

Analytical Chemistry↗
USGS2002

Some aspects of resource uncertainty and their economic consequences in assessment of the 1002 Area of the Arctic National Wildlife Refuge

Exploration ventures in frontier areas have high risks. Before committing to them, firms prepare regional resource assessments to evaluate the potential payoffs. With no historical basis for directly estimating size distribution of undiscovered accumulations, reservoir attribute probability distributions can be assessed subjectively and used to project undiscovered accumulation sizes. Three questions considered here are: (1) what distributions should be used to characterize the subjective assessments of reservoir attributes, (2) how parsimonious can the analyst be when eliciting subjective information from the assessment geologist, and (3) what are consequences of ignoring dependencies among reservoir attributes? The standard or norm used for comparing outcomes is the computed cost function describing costs of finding, developing, and producing undiscovered oil accumulations. These questions are examined in the context of the US Geological Survey's recently published regional assessment of the 1002 Area of the Arctic National Wildlife Refuge, Alaska. We study effects of using the various common distributions to characterize the geologist's subjective distributions representing reservoir attributes. Specific findings show that triangular distributions result in substantial bias in economic forecasts when used to characterize skewed distributions. Moreover, some forms of the lognormal distribution also result in biased economic inferences. Alternatively, we generally determined four fractiles (100, 50, 5, 0) to be sufficient to capture essential economic characteristics of the underlying attribute distributions. Ignoring actual dependencies among reservoir attributes biases the economic evaluation.

Alaska↗
USGS2002

Comparison of two probability distributions used to model sizes of undiscovered oil and gas accumulations: Does the tail wag the assessment?

Undiscovered oil and gas assessments are commonly reported as aggregate estimates of hydrocarbon volumes. Potential commercial value and discovery costs are, however, determined by accumulation size, so engineers, economists, decision makers, and sometimes policy analysts are most interested in projected discovery sizes. The lognormal and Pareto distributions have been used to model exploration target sizes. This note contrasts the outcomes of applying these alternative distributions to the play level assessments of the U.S. Geological Survey's 1995 National Oil and Gas Assessment. Using the same numbers of undiscovered accumulations and the same minimum, medium, and maximum size estimates, substitution of the shifted truncated lognormal distribution for the shifted truncated Pareto distribution reduced assessed undiscovered oil by 16% and gas by 15%. Nearly all of the volume differences resulted because the lognormal had fewer larger fields relative to the Pareto. The lognormal also resulted in a smaller number of small fields relative to the Pareto. For the Permian Basin case study presented here, reserve addition costs were 20% higher with the lognormal size assumption. ?? 2002 International Association for Mathematical Geology.

Mathematical Geology↗
USGS2010

Iceberg calving as a primary source of regional‐scale glacier‐generated seismicity in the St. Elias Mountains, Alaska

Since the installation of the Alaska Regional Seismic Network in the 1970s, data analysts have noted nontectonic seismic events thought to be related to glacier dynamics. While loose associations with the glaciers of the St. Elias Mountains have been made, no detailed study of the source locations has been undertaken. We performed a two-step investigation surrounding these events, beginning with manual locations that guided an automated detection and event sifting routine. Results from the manual investigation highlight characteristics of the seismic waveforms including single-peaked (narrowband) spectra, emergent onsets, lack of distinct phase arrivals, and a predominant cluster of locations near the calving termini of several neighboring tidewater glaciers. Through these locations, comparison with previous work, analyses of waveform characteristics, frequency-magnitude statistics and temporal patterns in seismicity, we suggest calving as a source for the seismicity. Statistical properties and time series analysis of the event catalog suggest a scale-invariant process that has no single or simple forcing. These results support the idea that calving is often a response to short-lived or localized stress perturbations. Our results demonstrate the utility of passive seismic instrumentation to monitor relative changes in the rate and magnitude of iceberg calving at tidewater glaciers that may be volatile or susceptible to ensuing rapid retreat, especially when existing seismic infrastructure can be used.

Alaska↗
USGS2025

Crater detection dependence on resolution, incidence angle, emission angle, and phase angle

Impact crater population detection and measurement is critical to understanding solar system bodies and dynamics. However, the ability to detect all possible craters under different lighting and camera geometries has not been systematically studied except in a few limited cases. This work presents the first systematic study examining crater detection based on resolution, incidence angle, emission angle, and phase angle, by three independent researchers to also test reliability of our conclusions. We found the best incidence angles for crater detection to be ∼74°–82°. We found little dependence on emission angle with geometries as high as ∼60°, while phase angles ∼20°–75° produce reliable crater populations. Resolution requires at least 6 pixels, and it is likely researcher-, geometry-, and terrain-specific. This work reveals potential biases in crater analysts' work and can be used for missions planning encounters so they can achieve the best, most reliable recovery of crater populations.

Geophysical Research Letters↗
USGS2020

A continuously updated, geospatially rectified database of utility-scale wind turbines in the United States

Nearly 60,000 utility-scale wind turbines are installed in the United States as of July, 2019, representing over 97 gigawatts of electric power capacity; US wind turbine installations continue to grow at a rapid pace. Yet, until April 2018, no publicly-available, regularly updated data source existed to describe those turbines and their locations. Under a cooperative research and development agreement, analysts from three organizations collaborated to develop and release the United States Wind Turbine Database (USWTDB) - a publicly available, continuously updated, spatially rectified data source of locations and attributes of utility-scale wind turbines in the United States. Technical specifications and wind facility data, incorporated from five sources, undergo rigorous quality control. The location of each turbine is visually verified using high-resolution aerial imagery. The quarterly-updated data are available in a variety of formats, including an interactive web application, comma-separated values (CSV), shapefile, and application programming interface (API). The data are used widely by academic researchers, engineers and developers from wind energy companies, government agencies, planners, educators, and the general public.

Scientific Data↗
USGS2023

Georectified polygon database of ground-mounted large-scale solar photovoltaic sites in the United States

Over 4,400 large-scale solar photovoltaic (LSPV) facilities operate in the United States as of December 2021, representing more than 60 gigawatts of electric energy capacity. Of these, over 3,900 are ground-mounted LSPV facilities with capacities of 1 MWdc or more. Ground mounted LSPV installations continue increasing, with more than 400 projects appearing online in 2021 alone; however, a comprehensive, publicly available georectified dataset including spatial footprints of these facilities is lacking. Analysts from U.S. Over 4,400 large-scale solar photovoltaic (LSPV) facilities operate in the United States as of December 2021, representing more than 60 gigawatts of electric energy capacity. Of these, over 3,900 are ground-mounted LSPV facilities with capacities of 1 megawatt direct current (MW dc ) or more. Ground-mounted LSPV installations continue increasing, with more than 400 projects appearing online in 2021 alone; however, a comprehensive, publicly available georectified dataset including spatial footprints of these facilities is lacking. The United States Large-Scale Solar Photovoltaic Database (USPVDB) was developed to fill this gap. Using US Energy Information Administration (EIA) data, locations of 3,699 LSPV facilities were verified using high-resolution aerial imagery, polygons were digitized around panel arrays, and attributes were appended. Quality assurance and control were achieved via team peer review and comparison to other US PV datasets. Data are publicly available via an interactive web application and multiple downloadable formats, including: comma-separated value (CSV), application programming interface (API), and GIS shapefile and GeoJSON. Survey and Lawrence Berkeley National Laboratory collaborated to develop the United States Large-Scale Solar Photovoltaic Database (USPVDB). Using Energy Information Administration (EIA) data, locations of LSPV facilities were verified using high-resolution aerial imagery, polygons were digitized around panel arrays, and attributes were appended. Quality assurance and control were achieved via team peer review and comparison to other US PV datasets. Data are publicly available in an interactive web application, and a number of downloadable formats, including: comma-separated value spreadsheet (CSV), application programming interface (API), and GIS shapefile.

Scientific Data↗
USGS1995

Criteria for evaluating state instream-flow programs: Deciding what works

Most states have adopted some form of instream-flow–protection program. These programs are of three types: instream-flow water rights; reservations of water for instream purposes; and conditions on consumptive water rights. No matter which type of protection program is adapted, the same question remains: How can we tell if it works? Several authors have attempted to answer this question. The works of these analysts are reviewed and criteria are suggested to evaluate the success of an instream-flow–protection program. The criteria are public confidence, certainty, proper administration, expense, and outcome in-stream.

Journal of Water Resources Planning and Management↗
USGS2001

User interface for ground-water modeling: Arcview extension

Numerical simulation for ground-water modeling often involves handling large input and output data sets. A geographic information system (GIS) provides an integrated platform to manage, analyze, and display disparate data and can greatly facilitate modeling efforts in data compilation, model calibration, and display of model parameters and results. Furthermore, GIS can be used to generate information for decision making through spatial overlay and processing of model results. Arc View is the most widely used Windows-based GIS software that provides a robust user-friendly interface to facilitate data handling and display. An extension is an add-on program to Arc View that provides additional specialized functions. An Arc View interface for the ground-water flow and transport models MODFLOW and MT3D was built as an extension for facilitating modeling. The extension includes preprocessing of spatially distributed (point, line, and polygon) data for model input and postprocessing of model output. An object database is used for linking user dialogs and model input files. The Arc View interface utilizes the capabilities of the 3D Analyst extension. Models can be automatically calibrated through the Arc View interface by external linking to such programs as PEST. The efficient pre- and postprocessing capabilities and calibration link were demonstrated for ground-water modeling in southwest Kansas.

Journal of Hydrologic Engineering↗
USGS2014

Regression models of discharge and mean velocity associated with near-median streamflow conditions in Texas: utility of the U.S. Geological Survey discharge measurement database

A database containing more than 16,300 discharge values and ancillary hydraulic attributes was assembled from summaries of discharge measurement records for 391 USGS streamflow-gauging stations (streamgauges) in Texas. Each discharge is between the 40th- and 60th-percentile daily mean streamflow as determined by period-of-record, streamgauge-specific, flow-duration curves. Each discharge therefore is assumed to represent a discharge measurement made for near-median streamflow conditions, and such conditions are conceptualized as representative of midrange to baseflow conditions in much of the state. The hydraulic attributes of each discharge measurement included concomitant cross-section flow area, water-surface top width, and reported mean velocity. Two regression equations are presented: (1) an expression for discharge and (2) an expression for mean velocity, both as functions of selected hydraulic attributes and watershed characteristics. Specifically, the discharge equation uses cross-sectional area, water-surface top width, contributing drainage area of the watershed, and mean annual precipitation of the location; the equation has an adjusted R-squared of approximately 0.95 and residual standard error of approximately 0.23 base-10 logarithm (cubic meters per second). The mean velocity equation uses discharge, water-surface top width, contributing drainage area, and mean annual precipitation; the equation has an adjusted R-squared of approximately 0.50 and residual standard error of approximately 0.087 third root (meters per second). Residual plots from both equations indicate that reliable estimates of discharge and mean velocity at ungauged stream sites are possible. Further, the relation between contributing drainage area and main-channel slope (a measure of whole-watershed slope) is depicted to aid analyst judgment of equation applicability for ungauged sites. Example applications and computations are provided and discussed within a real-world, discharge-measurement scenario, and an illustration of the development of a preliminary stage-discharge relation using the discharge equation is given.

Texas↗
USGS2010

Automated masking of cloud and cloud shadow for forest change analysis using Landsat images

Accurate masking of cloud and cloud shadow is a prerequisite for reliable mapping of land surface attributes. Cloud contamination is particularly a problem for land cover change analysis, because unflagged clouds may be mapped as false changes, and the level of such false changes can be comparable to or many times more than that of actual changes, even for images with small percentages of cloud cover. Here we develop an algorithm for automatically flagging clouds and their shadows in Landsat images. This algorithm uses clear view forest pixels as a reference to define cloud boundaries for separating cloud from clear view surfaces in a spectral-temperature space. Shadow locations are predicted according to cloud height estimates and sun illumination geometry, and actual shadow pixels are identified by searching the darkest pixels surrounding the predicted shadow locations. This algorithm produced omission errors of around 1% for the cloud class, although the errors were higher for an image that had very low cloud cover and one acquired in a semiarid environment. While higher values were reported for other error measures, most of the errors were found around the edges of detected clouds and shadows, and many were due to difficulties in flagging thin clouds and the shadow cast by them, both by the developed algorithm and by the image analyst in deriving the reference data. We concluded that this algorithm is especially suitable for forest change analysis, because the commission and omission errors of the derived masks are not likely to significantly bias change analysis results.

International Journal of Remote Sensing↗
USGS1992

Monitoring rangeland dynamics in Senegal with advanced very high resolution radiometer data

Time‐series Normalized Difference Vegetation Index (NDVI) data, computed from Advanced Very High Resolution Radiometer data, are being used by regional and national programs in the African Sahel to monitor seasonal rangeland conditions. The data are often used as indicators of grazing conditions and drought. However, distinguishing rangelands from other vegetation cover types on NDVI images is difficult. A second complication is that rangeland types and their associated productivity vary geographically by soil type. To effectively assess rangeland conditions, seasonal fluctuations (due to climatic cycles) must be isolated from long‐term production characteristics associated with vegetation type and soil differences. Rangeland NDVI dynamics, including qualitative assessments of rangeland production, and the timing and length of the growing season in Senegal were examined by using 7.4‐km global area coverage satellite data. Analyses were based on 10‐day NDVI composite image data from 1982 through 1989. The NDVI image data were stratified by rangeland and soil polygons derived from locally available resource maps. Time‐series NDVI statistics were calculated from the resource polygons that had been interpreted into high, medium, and low production rangelands. Analysts monitoring rangeland conditions can better identify seasonal anomalies such as drought by comparing production potential within homogeneous; resource polygons with the current NDVI data.

Geocarto International↗
USGS2019

Using out-of-sample yield forecast experiments to evaluate which earth observation products best indicate end of season maize yields

In East Africa, accurate grain yield predictions can help save lives and protect livelihoods. Regional grain yield forecasts can inform decisions regarding the availability and prices of key staples, food aid, and large humanitarian responses. Here, we use earth observation (EO) products to develop and evaluate subnational grain yield forecasts for 56 regions located in two severely food insecure countries: Kenya and Somalia. We identify, for a given region and time of year, which, if any, product is the best indicator for end-of-season maize yields. Our analysis seeks to inform a real-world situation in which analysts have access to multiple regularly updated EO data products, but predictive skill corresponding to each may vary across these regions and throughout the season. We find that the most accurate predictions can be made for high-producing areas, but that the relationship between production and forecast accuracy diminishes in areas with yields averaging greater than one metric ton per hectare. However, while forecast accuracy is highest in high production areas, in many of these regions, the forecast accuracy of models using EO products is not better than a set of baseline models that do not use EO products. Overall, we find that rainfall is the best indicator in low-producing regions and that other EO products work best in areas where yields are relatively consistent, but production is still limited by environmental factors.

Environmental Research Letters↗
USGS2026

Bulk location and source mechanisms of repetitive long-period seismicity at Mount St. Helens in July 2005

The 2004–2008 eruption of Mount St. Helens exemplified the practical challenges of processing high seismic event rates and data volumes. This protracted multi-year eruptive sequence was accompanied by a near-continuous occurrence of long-period (LP, 0.5–5 Hz) seismicity, but network-based picks and locations have previously been performed for only a relatively small subset of the overall seismicity, and full-waveform source–mechanism inversions have previously been performed for just two event types during the eruption. We present a new workflow for the bulk detection, cluster picking, 3-D location, and full-waveform source–mechanism inversion of repetitive LP volcanic seismicity recorded by a local broadband seismic network. Our emphasis is on methods that: exploit waveform similarity (multiplets) commonly observed for volcanic LP seismicity swarms; can take into account 3-D topographic and velocity structure heterogeneity typical of volcanoes; can process high event rates with relatively low analyst burden; and do not require a priori catalogue picks or known waveform templates. We develop and illustrate the workflow using data from Mount St. Helens from 2005 June 29 to July 31, a time-window characterized by high-rate LP seismicity, including numerous lower amplitude small LPs, and for which relatively dense seismic network coverage is available. Approximately 40 per cent of seismicity (20 561 events out of 52 141 triggers) during 2005 June 29 to July 31 is repetitive enough to be grouped into 17 multiplets of at least 300 events. We present 3-D locations of the 17 multiplets, representing 20 076 events having picks from at least eight stations, along with full-waveform source mechanism inversions of the 17 separate multiplet stacks. Collectively, our seismic 3-D hypocentre distributions for 2005 June 29 to July 31 are compatible with sources around the margins of the upper conduit section that is associated with plug solidification. All location results indicate compact seismicity clusters, with the 17 multiplets spatially connected and collectively located at shallow depth, approximately ~ 775 m depth beneath the 1980s crater floor and directly beneath, or immediately adjacent to, the extruding dacite spine. The full-waveform source–mechanism inversions for the 17 multiplets generally indicate mechanisms dominated by volumetric components consistent with subhorizontal cracks along with minor contributions from subvertical cracks. The overall picture is that of a stack or plexus of subhorizontal cracks located at shallow depth beneath the extruding dacite spines, consistent with subhorizontal hydrofractures extending from the conduit margins into the surrounding wall rock; minor subvertical crack components of the mechanisms could possibly arise from surfaces parallel to the conduit wall, such as within the damage halo associated with degassing pathways.

Washington↗
USGS2001

Landsat-7 ETM+ radiometric calibration: Two years on-orbit

Landsat-7 has been in orbit for 2 years as of April 15, 2001 and operationally providing calibrated data products for 2 years as of June 28, 2001. A radiometric calibration team consisting of scientists and analysts from the Landsat Project Science Office, the Landsat-7 Image Assessment System and four universities evaluates the calibration based on on-board and ground-look (vicarious) calibration methodologies. The results are assembled and compared semi-annually and the calibration parameter files are adjusted as necessary. To date the combined results for the reflective bands have not shown any change from pre-launch values. The pre-launch values continue to be used for data processing, with the uncertainty estimated at less than 5%. In the thermal band, the vicarious calibration results indicated a 0.31 W/m/sup 2/ sr /spl mu/m bias in the calibration. This bias results in the ETM+ derived temperatures being about 3K high. The calibration parameter file was updated October 1, 2000 to remove this bias, however the U.S. Landsat Product Generation System (LPGS) software required modification that was not incorporated until December 20, 2000. All LPGS data products generated since this date have the correct thermal band calibration, regardless of image acquisition date, with uncertainties at approximately the 1% level.

Conference Paper↗
USGS2025

Spatial close-kin mark-recapture models applied to terrestrial species with continuous natal dispersal

Close-kin mark–recapture (CKMR) methods use information on genetic relatedness among individuals to estimate demographic parameters. An individual's genotype can be considered a ‘recapture’ of each of its parent's genotype, and the frequency of kin-pair matches detected in a population sample can directly inform estimates of abundance. CKMR inference procedures require analysts to define kinship probabilities in functional forms, which inevitably involve simplifying assumptions. Among others, population structure can have a strong influence on how kinship probabilities are formulated. Many terrestrial species are philopatric or face barriers to dispersal, and not accounting for dispersal limitation in kinship probabilities, can create substantial bias if sampling is also spatially structured (e.g. via harvest). We present a spatially explicit formulation of CKMR that corrects for incomplete mixing by incorporating natal dispersal distances and spatial distribution of individuals into the kinship probabilities. We used individual-based simulations to evaluate the accuracy of abundance estimates obtained with one spatially naïve and two spatially explicit CKMR models across six scenarios with distinct spatial patterns of relative abundance and sampling probability. Estimates of abundance obtained with a CKMR model naïve to spatial structure were negatively biased when sampling was spatially biased. Incorporating patterns of natal dispersal in the kinship probabilities helped address this bias, but estimates were not always accurate depending on the model used and the scenario considered. Incorporating natal dispersal into spatially structured CKMR models can address the bias created by population structure and heterogeneous sampling but will often require additional assumptions and auxiliary data (e.g. relative abundance indices). The models shown here were designed for terrestrial species with continuous patterns of natal dispersal and high year-to-year site fidelity but could be extended to other species.

Methods in Ecology and Evolution↗
USGS2025

An analysis of the linked decisions in the confiscation of illegally traded turtles

Over the last few decades, freshwater turtles have become more common in the illegal wildlife trade because of growing global demand. Illegally traded turtles may be intercepted by several different agencies with separate jurisdictions. When turtles are confiscated, uncertainties may make releasing them back to the wild difficult. We used tools from decision analysis to achieve the following three objectives: (1) map elements of the decision process and their relationships in the illegal turtle trade using conceptual models, (2) outline the linked decisions for turtle confiscation and repatriation using decision trees, and (3) evaluate the decision trees for two example scenarios, one with moderate uncertainty and one with high uncertainty. We used the wood turtle ( Glyptemys insculpta ) as a case study, which is a species of conservation concern in part due to illegal wildlife trafficking. We conducted 23 semi-structured interviews of decision makers in law enforcement, biologists, land managers, and zoo staff. Interviews revealed that decisions regarding the disposition of confiscated turtles are complicated by uncertainty in disease status and origin. Decision makers that handle confiscated turtles also recognize that their decisions are often made in sequence and dependent on the outcome of antecedent decisions. In evaluating our decision trees, we found that the optimal decisions for example scenarios were similar and insensitive to uncertainty. Future applications of the decision trees by decision makers would involve a decision analyst to parameterize and interpret the choices and consequences involved in working through these decision trees. Collectively, our work shows how the use of decision trees can help structure and evaluate risky decisions for repatriating confiscated wildlife.

Conservation Science and Practice↗
USGS2003

Nonidentifiability of population size from capture-recapture data with heterogeneous detection probabilities

Heterogeneity in detection probabilities has long been recognized as problematic in mark-recapture studies, and numerous models developed to accommodate its effects. Individual heterogeneity is especially problematic, in that reasonable alternative models may predict essentially identical observations from populations of substantially different sizes. Thus even with very large samples, the analyst will not be able to distinguish among reasonable models of heterogeneity, even though these yield quite distinct inferences about population size. The problem is illustrated with models for closed and open populations.

Biometrics↗