Search USGS⌕ Search

SEARCH · Search USGS

Results for “Data”

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 721 records · Page 40Linked to original sources
USGS1991

Definitions of database files and fields of the Personal Computer-Based Water Data Sources Directory

This report describes the data-base files and fields of the personal computer-based Water Data Sources Directory (WDSD). The personal computer-based WDSD was derived from the U.S. Geological Survey (USGS) mainframe computer version. The mainframe version of the WDSD is a hierarchical data-base design. The personal computer-based WDSD is a relational data- base design. This report describes the data-base files and fields of the relational data-base design in dBASE IV (the use of brand names in this abstract is for identification purposes only and does not constitute endorsement by the U.S. Geological Survey) for the personal computer. The WDSD contains information on (1) the type of organization, (2) the major orientation of water-data activities conducted by each organization, (3) the names, addresses, and telephone numbers of offices within each organization from which water data may be obtained, (4) the types of data held by each organization and the geographic locations within which these data have been collected, (5) alternative sources of an organization's data, (6) the designation of liaison personnel in matters related to water-data acquisition and indexing, (7) the volume of water data indexed for the organization, and (8) information about other types of data and services available from the organization that are pertinent to water-resources activities.

Open-File Report↗
USGS1997

National Geochemical Database: Reformatted data from the National Uranium Resource Evaluation (NURE) Hydrogeochemical and Stream Sediment Reconnaissance (HSSR) program

The National Uranium Resource Evaluation (NURE) Hydrogeochemical and Stream Sediment Reconnaissance (HSSR) program produced a large amount of geochemical data. To fully understand how these data were generated, it is recommended that you read the History of NURE HSSR Program for a summary of the entire program. By the time the NURE program had ended, the HSSR data consisted of 894 separate data files stored with 47 different formats. Many files contained duplication of data found in other files. The University of Oklahoma's Information Systems Programs of the Energy Resources Institute (ISP) was contracted by the Department of Energy to enhance the accessibility and usefulness of the NURE HSSR data. ISP created a single standard-format master file to replace the 894 original files. ISP converted 817 of the 894 original files before its funding apparently ran out. The ISP-reformatted NURE data files have been released by the USGS on CD-ROM (Lower 48 States, Hoffman and Buttleman, 1994; Alaska, Hoffman and Buttleman, 1996). A description of each NURE database field, derived from a draft NURE HSSR data format manual (unpubl. commun., Stan Moll, ISP, Oct 7, 1988), was included in a readme file on each CD-ROM. That original manual was incomplete and assumed that the reformatting process had gone to completion. A lot of vital information was not included. Efforts to correct that manual and the NURE data revealed a large number of problems and missing data. As a result of the frustrating process of cleaning and re-cleaning data from the ISP-reformatted NURE files, a new NURE HSSR data format was developed. This work represents a totally new attempt to reformat the original NURE files into 2 consistent database structures; one for water samples and a second for sediment samples, on a quadrangle by quadrangle basis, from the original NURE files. Although this USGS-reformatted NURE HSSR data format is different than that created by the ISP, many of their ideas were incorporated and expanded in this effort. All of the data from each quadrangle are being examined thoroughly in an attempt to eliminate problems, to combine partial or duplicate records, to convert all coding to a common scheme, and to identify problems even if they can not be solved at this time.

Open-File Report↗
USGS1999

Characteristics of the Alaskan 1-Km Advanced Very High Resolution Radiometer data sets used for analysis of vegetation biophysical properties

In this study, data characteristics for composited, multitemporal Advanced Very High Resolution Radiometer data sets for Alaska were assessed for a 7- year period from 1991 to 1997. This involved consideration of the satellite sensors used, data processing performed, and data set compilation, along with an analysis of acquisition date, solar zenith angle, satellite viewing angle, presence of clouds, and registration accuracy for each year. Each year?s worth of data are available on CD-ROM in byte format. All data sets have an initial start date of April 1, but had varying ending dates (mid-September to late October) because of satellite sensor malfunction or the presence of clouds or snow; no data set extended beyond October 31. Satellite scan angles were summarized in seven categories: data obtained at nadir, data within 30, 40, and 55 degrees of nadir, data greater than 55 degrees off nadir, and proportions of the data representing east or west look angles. Minimum, maximum, and average solar zenith angles were provided for each period. Estimates of cloud cover for each period were based on three tests: reflectance gross cloud test, channel 3 minus channel 4, and channel 4 minus channel 5. Registration accuracy was estimated using a gray-level autocorrelation technique. Results of this investigation indicate that the composited data available on CD-ROM should be useful for a number of different regional assessments of Earth cover properties. However, caution is advised when using these data because (1) loss in precision from the conversion to a byte format, (2) low sun angles and high viewing angles in the September and October data, and (3) registration inaccuracies of 2 to 8 pixels.

Alaska↗
USGS2007

Organic-carbon sequestration in soil/sediment of the Mississippi River deltaic plain — Data; landscape distribution, storage, and inventory; accumulation rates; and recent loss, including a post-Katrina preliminary analysis

Soil/sediment of the Mississippi River deltaic plain (MRDP) in southeastern Louisiana is rich in organic carbon (OC). The MRDP contains about 2 percent of all OC in the surface meter of soil/sediment in the Mississippi River Basin (MRB). Environments within the MRDP differ in soil/sediment organic carbon (SOC) accumulation rate, storage, and inventory. The focus of this study was twofold: (1) develop a database for OC and bulk density for MRDP soil/sediment; and (2) estimate SOC storage, inventory, and accumulation rates for the dominant environments (brackish, intermediate, and fresh marsh; natural levee; distributary; backswamp; and swamp) in the MRDP. Comparative studies were conducted to determine which field and laboratory methods result in the most accurate and reproducible bulk-density values for each marsh environment. Sampling methods included push-core, vibracore, peat borer, and Hargis1 sampler. Bulk-density data for cores taken by the "short push-core method" proved to be more internally consistent than data for samples collected by other methods. Laboratory methods to estimate OC concentration and inorganic-constituent concentration included mass spectrometry, coulometry, and loss-on-ignition. For the sampled MRDP environments, these methods were comparable. SOC storage was calculated for each core with adequate OC and bulk-density data. SOC inventory was calculated using core-specific data from this study and available published and unpublished pedon data linked to SSURGO2 map units. Sample age was estimated using isotopic cesium ( 37 Cs), lead ( 210 Pb), and carbon ( 14 C), elemental Pb, palynomorphs, other stratigraphic markers, and written history. SOC accumulation rates were estimated for each core with adequate age data. Cesium-137 profiles for marsh soil/sediment are the least ambiguous. Levee and distributary 137 Cs profiles show the effects of intermittent allochthonous input and/or sediment resuspension. Cesium-137 and 210 Pb data gave the most consistent and interpretable information for age estimations of soil/sediment deposited during the 1900s. For several cores, isotopic 14 C and 137 Cs data allowed the 1963-64 nuclear weapons testing (NWT) peak-activity datum to be placed within a few-centimeter depth interval. In some cores, a too old 14 C age (when compared to 137 Cs and microstratigraphic-marker data) is the probable result of old carbon bound to clay minerals incorporated into the organic soil/sediment. Elemental Pb coupled with Pb source-function data allowed age estimation for soil/sediment that accumulated during the late 1920s through the 1980s. Exotic pollen (for example, Vigna unguiculata and Alternanthera philoxeroides ) and other microstratigraphic indicators (for example, carbon spherules) allowed age estimations for marsh soil/sediment deposited during the settlement of New Orleans (1717-20) through the early 1900s. For this study, MRDP distributary and swamp environments were each represented by only one core, backswamp environment by two cores, all other environments by three or more cores. MRDP core data for the surface meter soil/sediment indicate that (1) coastal marshes, abandoned distributaries, and swamps have regional SOC-storage values >16 kg m -2 ; (2) swamps and abandoned distributaries have the highest SOC storage values (swamp, 44.8 kg m -2 ; abandoned distributary, 50.9 kg m -2 ); (3) fresh-to-brackish marsh environments have the second highest site-specific SOC-storage values; and (4) site-specific marsh SOC storage values decrease as the salinity of the environment increases (fresh-marsh, 36.2 kg m -2 ; intermediate marsh, 26.2 kg m -2 ; brackish marsh, 21.5 kg m -2 ). This inverse relation between salinity and SOC storage is opposite the regional systematic increase in SOC storage with increasing salinity that is evident when SOC storage is mapped by linking pedon data to SSURGO map units (fresh marsh, 47 kg m -2 ; intermediate marsh, 67 kg m -2 ; brackish marsh, 75 kg m -2 ; and salt marsh, 80 kg m -2 ). MRDP core data for this study also indicate that levees and backswamp have regional SOC-storage values <16 kg m -2 . Group-mean SOC storage for cores from these environments are natural levee (17.0 kg m -2 ) and backswamp (14.1 kg m -2 ). An estimate for the SOC inventory in the surface meter of soil/sediment in the MRDP can be made using the SSURGO mapped portion of the coastal-marsh vegetative-type map (13,236 km 2 , land-only area) published by the Louisiana Department of Wildlife and Fisheries and U.S. Geological Survey (1997). This area has a SOC inventory (surface meter) of 677 Tg (slightly more than 2 percent of the 30,289 Tg SOC inventory for the MRB). The MRDP (6,180 km2, land-only area) has an estimated SOC inventory of 397 Tg. Most of the MRDP is located within the SSURGO mapped coastal marshlands. The entire MRDP, including water, has an area of about 10,800 km 2 . Using the ratio of total MRDP area to SSURGO mapped MRDP area as an adjustment, the MRDP SOC inventory is estimated at 694 Tg. This larger estimate of 694 Tg for the SOC inventory is probably more realistic, because it is reasonable to assume that the marsh sediments overlain by shallow water have comparable SOC storage to that of the adjacent land areas. MRDP core data for this study indicate that there is some variability in long-term SOC mass-accumulation rates for centuries and millennia and that this variability may indicate important geologic changes or changes in land use. However, the consistency of the range in rates of SOC accumulation through time suggests a remarkable degree of marsh sustainability throughout the Holocene, including the recent period of significant marsh modification/channelization for human use. One example of marsh sustainability is its present ability to function as a SOC sink even with Louisiana's large-scale coastal land loss during the last several decades. With coastal-marsh restoration efforts, this sink potential will increase. Looking to the future, a total of 1,101 g m -2 yr -1 SOC is projected to be lost from all of coastal Louisiana (U.S. Army Corps of Engineers, Louisiana Coastal Area (LCA) subprovinces 1-4; not just the MRDP) through coastal erosion from year 2000 to 2050. This translates to a projected SOC-loss rate of about 0.20 percent per year. The recent Hurricanes Katrina and Rita, which devastated the Louisiana coast during late August and late September 2005, transformed about 259 km 2 (100 mi 2 ) of marsh to open water (U.S. Geological Survey, 2005). To the extent that some or all of this land loss is permanent, this result equates to a SOC loss of about 15 Tg. This estimate is based on the year-2000 15,153-km 2 land area for the LCA study area that includes LCA subprovince 4. Using the year-2000 land area, the LCA study area had an estimated SOC inventory of 858 Tg. The estimated 15 Tg SOC loss attributable to Hurricanes Katrina and Rita is 1.7 percent of the year-2000 LCA inventory and 2.3 percent of the year-2000 MRDP inventory. If this SOC loss is included in the projection for the year 2050, then the MRDP would either remain a source with a net SOC loss of 3 Tg or become a weak sink with a net SOC gain of 4 Tg. These estimates are lower bounds for potential SOC flux because they are only for the surface meter of landmass.

Louisiana↗
USGS2005

Sediment-transport investigations of the upper Yellowstone River, Montana, 1999 through 2001: Data collection, analysis, and simulation of sediment transport

The upper Yellowstone River in Montana is an important State and national water resource, providing recreational, agricultural, and commercial benefits. Floods in 1996 and 1997, with recorded peak discharges having recurrence intervals close to 100 years, caused substantial streambank erosion and hill- slope mass wasting. Large quantities of sand-, gravel-, and cobble-sized material entrained by the flood flows became flood-bar deposits, creating a source of sediment available for transport during future floods. The flood damage and resulting sedimentation raised concerns about potential streambank-stabilization projects and how the river and riparian corridor might be managed in the future. The U.S. Geological Survey, in cooperation with the Park Conservation District, the Montana Department of Transportation, and the U.S. Army Corps of Engineers, investigated sediment transport in the upper Yellowstone River near Livingston from 1999 through 2001 as part of a cumulative effects study to provide a scientific basis for future river management decisions. The purpose of this report is to present the results of data collection, analysis, and simulation of sediment transport for the upper Yellowstone River. The study area included a 13.5-mile study reach of the upper Yellowstone River where substantial sediment transport occurred in 1996 and 1997. In this study area, the upper Yellowstone River is a high gradient, coarse-bed stream having a slope of about 0.0028 foot per foot or more than 14 feet per mile. The study area drains about 3,551 square miles, and runoff results primarily from snowmelt during the spring and summer months. As part of sediment-transport investigations, the U.S. Geological Survey surveyed river cross sections, characterized streambed-material particle size using particle counts and sieve analyses, and collected bedload- and suspended-sediment data during three runoff seasons (1999-2001). Data were collected for stream discharges that ranged from 2,220 cubic feet per second (typical of pre- and post-runoff discharge) to 25,100 cubic feet per second (about 125 percent of bankfull discharge). The distribution of streambed-material particle size was determined, and sediment-transport curves for bedload discharge, suspended-sediment discharge, and total-sediment discharge were developed. The threshold values of streamflow and average stream velocity needed for initiation of bedload transport for selected sediment-size classes showed that little to no bedload was transported for an average stream velocity below about 3 feet per second, and the only particle size transported as bedload at that velocity was sand. Over the range of stream discharges sampled and with silt- and finer-sized particles excluded, bedload discharge averaged about 18 percent of the total-sediment discharge, equal to bedload discharge plus suspended-sediment discharge. At the lowest and highest stream discharges sampled, bedload was, respectively, less than about 2 percent and about 30 percent of the total-sediment discharge. Over the range of stream discharges sampled, the sand-sized part of the total suspended-sediment discharge averaged about 48 percent, where the total suspended-sediment discharge included sand-, silt- and finer-sized particles. At the lowest and highest stream discharges sampled, the sand-sized part of the total suspended-sediment discharge was, respectively, less than about 16 percent and about 50 percent of the total suspended-sediment discharge. The sediment-transport curves were compared to curves for selected sites in the western United States having drainage areas ranging from 21 square miles to over 20,000 square miles. Daily sediment loads transported at bankfull discharge were calculated for each site and results were plotted in relation to drainage area. Results based on the 1999-2001 data-collection period indicate that the estimated daily bedload transported at bankfull discharge in the upper Yellowstone River exceeded the envelope line that bounds the upper end of the data for other selected sites in the Northern Rocky Mountains and is similar in magnitude to that for selected sites in Alaska having braided channels and glacial and snowmelt runoff. Similar comparisons for suspended sediment indicate that daily suspended-sediment load at bankfull discharge is relatively high in the upper Yellowstone River, plotting slightly above the envelope line that bounds the upper end of the data for other selected sites in the Northern Rocky Mountains. Sediment data were used to develop individual transport equations for seven size classes of sediment ranging from small cobbles to very fine sand. A step-wise regression procedure relating sediment discharge to important hydraulic variables showed that average stream velocity was the only significant variable at the 95-percent confidence level. Bedload and suspended-sediment data and equations indicate that more sand is transported for a given velocity than any other particle size, and very little sand-size sediment load is transported below an average stream velocity of about 2.5 feet per second. Transport of coarser-sized sediment (limited to bedload) becomes very little for an average velocity less than about 3.5 feet per second. Results for the 1999-2001 data-collection period indicate that sediment transport in the upper Yellowstone River tends to be limited more by the transport capacity of the stream (capacity or transport limited), than to the availability of sediment in the watershed (supply limited). Sediment data collected and analyzed were used to simulate sediment transport in the study reach using the BRIdge Stream Tube model for Alluvial River Simulation, or BRI-STARS computer model. The model was calibrated and verified using selected data from historical runoff periods. Simulated total-sediment loads, on a reach-averaged basis, were in good agreement with the total-sediment loads determined from the transport curve for the 2-year flood hydrograph but were considerably smaller for the total-sediment loads determined from the transport curve for the 50-, 100-, and 500-year flood hydrographs. The differences probably were largely due to the inability of the model to simulate streambank erosion, hillslope mass-wasting, and other channel-widening processes, which had supplied substantial quantities of sediment to the channel during the 1996 and 1997 floods, and probably continued to contribute to the sediment load in the subsequent years (1999-2001) when the data were collected. Furthermore, the transport curve was applied beyond the measured data for the highest discharges, and may thus be unreliable. Also, the transport curve derived from only limited data may not apply over the full duration of the hydrograph and sediment might be transported over only a portion of the hydrograph, especially for rivers like the upper Yellowstone where snowmelt runoff predominates. The true sediment discharge is, therefore, unknown and might be closer to the simulated values than to the values calculated from the transport curve.

Montana↗
USGS2020

Quality of pesticide data for groundwater analyzed for the National Water-Quality Assessment Project, 2013–18

The National Water-Quality Assessment (NAWQA) Project of the U.S. Geological Survey (USGS) submitted nearly 1,900 samples collected from groundwater sites across the United States in 2013–18 for analysis of 225 pesticide compounds (pesticides and pesticide degradates, hereafter referred to as “pesticides”) by USGS National Water Quality Laboratory schedule 2437 (S2437). For the associated NAWQA study of pesticide occurrence and concentration in groundwater, and for other studies using pesticide results determined by S2437, it is necessary to assess the ability of reported results to meet data-quality requirements that will allow study objectives to be achieved. This assessment of the quality of S2437 results reported in 2013–18 examined data from field and laboratory quality-control samples, along with third-party performance assessment samples, to estimate bias and variability and to identify their potential sources, with an emphasis on implications for the interpretation of pesticide data for groundwater. Results indicate that measurements produced by the S2437 method for most pesticides have bias and variability that would be considered acceptable for many interpretative studies, which could therefore use the results without qualification or censoring. However, the reported data for a subset of pesticides have the potential for unacceptable contamination bias, high or low recovery bias, or high variability as a consequence of method performance and (or) nonlaboratory factors that could preclude their use for certain common objectives or could necessitate adjustment or qualification to meet those objectives. Based on data for laboratory blanks, censoring of some detections for a subset of pesticides reported by the laboratory in environmental samples might be necessary or desirable to avoid an unacceptably high likelihood of a false-positive result caused by laboratory contamination. The 90-percent upper confidence limit for the 95th percentile of laboratory blank concentration equals or exceeds the minimum reported groundwater concentration in at least 1 water year for 28 pesticides. During at least 1 water year, this upper confidence limit exceeds the maximum laboratory detection limit for 17 pesticides and exceeds the maximum laboratory reporting limit for 3 pesticides (ametryn, atrazine, and diazinon). The level of contamination indicated by this upper confidence limit should not substantially affect the suitability of reported environmental concentrations for any compound for comparison with corresponding human-health benchmarks. Despite being subjected to the same laboratory processes as laboratory blanks, field blanks indicated little evidence of contamination bias. This observation could largely be the consequence of data-reporting practices, which utilize detections in laboratory blanks to censor results in associated field samples (including blanks and environmental samples) when relative concentrations indicate that a result could have a substantial contribution from laboratory contamination. Laboratory censoring appears likely to reduce the risk of false-positive results in environmental samples below the level that laboratory blank results alone would imply. Whereas data available for third-party blind blank samples analyzed in 2018 indicate that only propoxur had any false-positive results, data for pesticides that were not spiked into blind spike samples analyzed in 2013–18 indicate that the false-positive rates for 31 pesticides exceeded 1 percent when considering only detections reported at concentrations greater than the maximum detection limit. Although about half of these pesticides lack substantial supporting evidence of contamination bias based on laboratory blank or field blank detections, indicating that spiking issues or degradation of parent compounds within the spiked samples might be a contributing factor to some false-positive results, these results indicate the need to closely examine detections reported for some pesticides in environmental samples analyzed during a similar period for possible contributions from contamination bias. Data for blind spike samples that were spiked at concentrations above the maximum reporting limit indicate that false-negative rates for eight pesticides exceed 10 percent; substantial low bias could affect results reported for these pesticides in environmental samples analyzed during a similar period. Data for laboratory reagent spikes, which measure recovery of pesticides in blank water, show little evidence for unacceptable recovery bias for S2437 pesticides. However, field matrix spikes, which measure recovery of pesticides in environmental matrices, indicate that degradation and (or) matrix effects could result in moderate to substantial low bias for groundwater results for several pesticides. Low bias could cause some reported concentrations to be categorized as being below a benchmark when the actual concentration in groundwater is greater than the benchmark. Occurrence and concentrations in groundwater could be substantially underrepresented for six pesticides with benchmarks (1H-1,2,4-triazole, asulam, bifenthrin, cis-permethrin, fenbutatin oxide, and naled) that have median recoveries between zero and 50 percent in field matrix spikes. Two compounds (didealkylatrazine and 2-hydroxy-6-ethylamino-4-amino-s-triazine) have median recoveries near or greater than 150 percent in field matrix spikes, indicating a substantial high bias. Plots of data for all spike types show clear changes in the typical recovery with time for some pesticides, which would require further examination for evaluation of temporal trends in environmental concentrations. Data for laboratory reagent spikes indicate that nearly all S2437 pesticides have acceptable variability resulting from random measurement error. Only two compounds (fenbutatin oxide and naled) have F-pseudosigma values greater than 30 percent for recovery, which implies the potential for relatively high variability in reported concentrations and could affect comparison of concentrations to benchmarks and determination of whether concentrations for samples collected at separate locations or times are truly different with a specified level of confidence. Data for third-party blind spike samples show relatively high variability for a greater number of pesticides, although these results likely reflect the influence of degradation and (or) differences in the magnitude and variability of concentrations used for blind spikes relative to laboratory reagent spikes. Detailed analysis of variability using field replicate data is possible for only 12 pesticides on S2437; low variability in analyte detection and concentration is indicated for most of these pesticides in groundwater.

Scientific Investigations Report↗
USGS1996

Evaluation of the Surface-Water Quantity, Surface-Water Quality, and Rainfall Data-Collection Programs in Hawaii, 1994

This report documents the results of an evaluation of the surface-water quantity, surface-water quality, and rainfall data-collection programs in Hawaii. Fourteen specific issues and related goals were identified for the surface-water quantity program and a geographic information systems (GIS) data base was developed summarizing information for all surface-water stream gages that have been operated in Hawaii by the U.S. Geological Survey. Changes in status, which for some gages includes discontinuing operation, need to be considered at 42 sites where data are currently collected. The current surface-water quantity data base was determined to be adequate to address only two of the 14 specific issues and related goals. Alternatives were identified to address the areas where future issues and goals could not be adequately addressed. Options include new and expanded data collection, use of regional regression analyses, hydrologic and hydraulic modeling, and analysis and publication of existing data. A total of 47 streams were identified where additional stream-gaging stations are needed. Evaluation of the surface-water quality program was limited to a description of the U.S. Geological Survey's historical and existing programs and available analyses of data. Limitations of the program are described which primarily included lack of data regarding suspended sediment, land-use effects, quality of stream discharge to oceans, background water quality and nonpoint sources of contamination. Evaluation of the rainfall data program indicated that identified future goals could be discussed as either regional, systems related, current needs, forecasting, water quality, or trend analysis related. To address these goals, data from about 2,000 rain gages, 528 of which are active, are available. Data were found to only partially meet identified goals. Alternatives discussed to address the limitations include the need for more recording gages, primarily in areas of high rainfall. Another area of concern was the potential that many plantations will close and the effect these closings would have on continued operation of the important long-term gages they operate. Evaluation of data-collection programs in Hawaii needs to be an ongoing process. Equally important, data being collected need to be summarized and made available through data bases and published reports.

Water-Resources Investigations Report↗
USGS2001

A comparison of U.S. geological survey seamless elevation models with shuttle radar topography mission data

Elevation models produced from Shuttle Radar Topography Mission (SRTM) data will be the most comprehensive, consistently processed, highest resolution topographic dataset ever produced for the Earth's land surface. Many applications that currently use elevation data will benefit from the increased availability of data with higher accuracy, quality, and resolution, especially in poorly mapped areas of the globe. SRTM data will be produced as seamless data, thereby avoiding many of the problems inherent in existing multi-source topographic databases. Serving as precursors to SRTM datasets, the U.S. Geological Survey (USGS) has produced and is distributing seamless elevation datasets that facilitate scientific use of elevation data over large areas. GTOPO30 is a global elevation model with a 30 arc-second resolution (approximately 1-kilometer). The National Elevation Dataset (NED) covers the United States at a resolution of 1 arc-second (approximately 30-meters). Due to their seamless format and broad area coverage, both GTOPO30 and NED represent an advance in the usability of elevation data, but each still includes artifacts from the highly variable source data used to produce them. The consistent source data and processing approach for SRTM data will result in elevation products that will be a significant addition to the current availability of seamless datasets, specifically for many areas outside the U.S. One application that demonstrates some advantages that may be realized with SRTM data is delineation of land surface drainage features (watersheds and stream channels). Seamless distribution of elevation data in which a user interactively specifies the area of interest and order parameters via a map server is already being successfully demonstrated with existing USGS datasets. Such an approach for distributing SRTM data is ideal for a dataset that undoubtedly will be of very high interest to the spatial data user community.

Conference Paper↗
USGS1978

EROS Data Center Landsat digital enhancement techniques and imagery availability

The US Geological Survey's EROS Data Center (EDC) is experimenting with the production of digitally enhanced Landsat imagery. Advanced digital image processing techniques are used to perform geometric and radiometric corrections and to perform contrast and edge enhancements. The enhanced image product is produced from digitally preprocessed Landsat computer compatible tapes (CCTs) on a laser beam film recording system. Landsat CCT data have several geometric distortions which are corrected when NASA produces the standard film products. When producing film images from CCT's, geometric correction of the data is required. The EDC Digital Image Enhancement System (EDIES) compensates for geometric distortions introduced by Earth's rotation, variable line length, non-uniform mirror scan velocity, and detector misregistration. Radiometric anomalies such as bad data lines and striping are common to many Landsat film products and are also in the CCT data. Bad data lines or line segments with more than 150 contiguous bad pixels are corrected by inserting data from the previous line in place of the bad data. Striping, caused by variations in detector gain and offset, is removed with a destriping algorithm applied after digitally enhancing the data. Image enhancement is performed by applying a linear contrast stretch and an edge enhancement algorithm. The linear contrast enhancement algorithm is designed to expand digitally the full range of useful data recorded on the CCT over the range of 256 digital counts. This minimizes the effect of atmospheric scattering and saturates the relative brightness of highly reflecting features such as clouds or snow. It is the intent that no meaningful terrain data are eliminated by the digital processing. The edge enhancement algorithm is designed to enhance boundaries between terrain features that exhibit subtle differences in brightness values along edges of features. After the digital data have been processed, data for each Landsat band are recorded on black-and-white film with a laser beam film recorder (LBR). The LBR corrects for aspect ratio distortions as the digital data are recorded on the recording film over a preselected density range. Positive transparencies of MSS bands 4, 5, and 7 produced by the LBR are used to make color composite transparencies. Color film positives are made photographically from first generation black-and-white products generated on the LBR.

Canadian Journal of Remote Sensing↗
USGS1995

Profiles of gamma-ray and magnetic data for aerial surveys over parts of the Western United States from longitude 108 to 126 degrees W. and from latitude 34 to 49 degrees N.

This CD-ROM contains images generated from geophysical data, software for displaying and analyzing the images and software for displaying and examining profile data from aerial surveys flown as part of the National Uranium Resource Evaluation (NURE) Program of the U.S. Department of Energy. The images included are of gamma-ray data (uranium, thorium, and potassium channels), Bouguer gravity data, isostatic residual gravity data, aeromagnetic anomalies, topography, and topography with bathymetry. This publication contains image data for the conterminous United States and profile data for the conterminous United States within the area longitude 108 to 126 degrees W. and latitude 34 to 49 degrees N. The profile data include apparent surface concentrations of potassium, uranium, and thorium, the residual magnetic field, and the height above the ground. The images on this CD-ROM include graytone and color images of each data set, color shaded-relief images of the potential-field and topographic data, and color composite images of the gamma-ray data. The image display and analysis software can register images with geographic and geologic overlays. The profile display software permits the user to view the profiles as well as obtain data listings and export ASCII versions of data for selected flight lines.

Data Series↗
USGS2011

Spatially pooled depth-dependent reservoir storage, elevation, and water-quality data for selected reservoirs in Texas, January 1965-January 2010

The U.S. Geological Survey (USGS), in cooperation with Texas Tech University, constructed a dataset of selected reservoir storage (daily and instantaneous values), reservoir elevation (daily and instantaneous values), and water-quality data from 59 reservoirs throughout Texas. The period of record for the data is as large as January 1965-January 2010. Data were acquired from existing databases, spreadsheets, delimited text files, and hard-copy reports. The goal was to obtain as much data as possible; therefore, no data acquisition restrictions specifying a particular time window were used. Primary data sources include the USGS National Water Information System, the Texas Commission on Environmental Quality Surface Water-Quality Management Information System, and the Texas Water Development Board monthly Texas Water Condition Reports. Additional water-quality data for six reservoirs were obtained from USGS Texas Annual Water Data Reports. Data were combined from the multiple sources to create as complete a set of properties and constituents as the disparate databases allowed. By devising a unique per-reservoir short name to represent all sites on a reservoir regardless of their source, all sampling sites at a reservoir were spatially pooled by reservoir and temporally combined by date. Reservoir selection was based on various criteria including the availability of water-quality properties and constituents that might affect the trophic status of the reservoir and could also be important for understanding possible effects of climate change in the future. Other considerations in the selection of reservoirs included the general reservoir-specific period of record, the availability of concurrent reservoir storage or elevation data to match with water-quality data, and the availability of sample depth measurements. Additional separate selection criteria included historic information pertaining to blooms of golden algae. Physical properties and constituents were water temperature, reservoir storage, reservoir elevation, specific conductance, dissolved oxygen, pH, unfiltered salinity, unfiltered total nitrogen, filtered total nitrogen, unfiltered nitrate plus nitrite, unfiltered phosphorus, filtered phosphorus, unfiltered carbon, carbon in suspended sediment, total hardness, unfiltered noncarbonate hardness, filtered noncarbonate hardness, unfiltered calcium, filtered calcium, unfiltered magnesium, filtered magnesium, unfiltered sodium, filtered sodium, unfiltered potassium, filtered potassium, filtered chloride, filtered sulfate, unfiltered fluoride, and filtered fluoride. When possible, USGS and Texas Commission on Environmental Quality water-quality properties and constituents were matched using the database parameter codes for individual physical properties and constituents, descriptions of each physical property or constituent, and their reporting units. This report presents a collection of delimited text files of source-aggregated, spatially pooled, depth-dependent, instantaneous water-quality data as well as instantaneous, daily, and monthly storage and elevation reservoir data.

Texas↗
USGS2006

Water resources data, Puerto Rico and the U.S. Virgin Islands, water year 2004

The Caribbean Water Science Center of the U.S. Geological Survey (USGS), in cooperation with local and Federal agencies obtains a large amount of data pertaining to the water resources of the Commonwealth of Puerto Rico and the Territory of the U.S. Virgin Islands each water year. These data, accumulated during many water years, constitute a valuable data base for developing an improved understanding of the water resources of the area. To make these data readily available to interested parties outside the U.S. Geological Survey, the data are published annually in this report series entitled 'Water Resources Data for Puerto Rico and the U.S. Virgin Islands.' This report includes records on both surface and ground water. Specifically, it contains: (1) discharge records for 89 streamflow-gaging stations, daily sediment records for 13 sediment stations, stage records for 18 reservoirs, and (2) water-quality records for 20 streamflow-gaging stations, and for 38 ungaged stream sites, 13 lake sites, 2 lagoons, and 1 bay, and (3) water-level records for 72 observation wells. Water-resources data for Puerto Rico for calendar years 1958-67 were released in a series of reports entitled 'Water Records of Puerto Rico.' Water-resources data for the U.S. Virgin Islands for the calendar years 1962-69 were released in a report entitled 'Water Records of U.S. Virgin Islands.' Included were records of streamflow, ground-water levels, and water-quality data for both surface and ground water. Beginning with the 1968 calendar year, surface-water records for Puerto Rico were released separately on an annual basis. Ground-water level records and water-quality data for surface and ground water were released in companion reports covering periods of several years. Data for the 1973-74 reports were published under separate covers. Water-resources data reports for 1975 to 2003 water years consist of one volume each and contain data for streamflow, water quality, and ground water.

Water Data Report↗
USGS2020

An open source database for the synthesis of soil radiocarbon data: ISRaD version 1.0

Radiocarbon is a critical constraint on our estimates of the timescales of soil carbon cycling that can aid in identifying mechanisms of carbon stabilization and destabilization and improve the forecast of soil carbon response to management or environmental change. Despite the wealth of soil radiocarbon data that have been reported over the past 75 years, the ability to apply these data to global-scale questions is limited by our capacity to synthesize and compare measurements generated using a variety of methods. Here, we present the International Soil Radiocarbon Database (ISRaD; http://soilradiocarbon.org , last access: 16 December 2019), an open-source archive of soil data that include reported measurements from bulk soils, distinct soil carbon pools isolated in the laboratory by a variety of soil fractionation methods, samples of soil gas or water collected interstitially from within an intact soil profile, CO 2 gas isolated from laboratory soil incubations, and fluxes collected in situ from a soil profile. The core of ISRaD is a relational database structured around individual datasets (entries) and organized hierarchically to report soil radiocarbon data, measured at different physical and temporal scales as well as other soil or environmental properties that may also be measured and may assist with interpretation and context. Anyone may contribute their own data to the database by entering it into the ISRaD template and subjecting it to quality assurance protocols. ISRaD can be accessed through (1) a web-based interface, (2) an R package (ISRaD), or (3) direct access to code and data through the GitHub repository, which hosts both code and data. The design of ISRaD allows for participants to become directly involved in the management, design, and application of ISRaD data. The synthesized dataset is available in two forms: the original data as reported by the authors of the datasets and an enhanced dataset that includes ancillary geospatial data calculated within the ISRaD framework. ISRaD also provides data management tools in the ISRaD-R package that provide a starting point for data analysis; as an open-source project, the broader soil community is invited and encouraged to add data, tools, and ideas for improvement. As a whole, ISRaD provides resources to aid our evaluation of soil dynamics across a range of spatial and temporal scales. The ISRaD v1.0 dataset is archived and freely available at https://doi.org/10.5281/zenodo.2613911 (Lawrence et al., 2019).

Earth System Science Data↗
USGS2016

A strategy for recovering continuous behavioral telemetry data from Pacific walruses

Tracking animal behavior and movement with telemetry sensors can offer substantial insights required for conservation. Yet, the value of data collected by animal-borne telemetry systems is limited by bandwidth constraints. To understand the response of Pacific walruses ( Odobenus rosmarus divergens ) to rapid changes in sea ice availability, we required continuous geospatial chronologies of foraging behavior. Satellite telemetry offered the only practical means to systematically collect such data; however, data transmission constraints of satellite data-collection systems limited the data volume that could be acquired. Although algorithms exist for reducing sensor data volumes for efficient transmission, none could meet our requirements. Consequently, we developed an algorithm for classifying hourly foraging behavior status aboard a tag with limited processing power. We found a 98% correspondence of our algorithm's classification with a test classification based on time–depth data recovered and characterized through multivariate analysis in a separate study. We then applied our algorithm within a telemetry system that relied on remotely deployed satellite tags. Data collected by these tags from Pacific walruses across their range during 2007–2015 demonstrated the consistency of foraging behavior collected by this strategy with data collected by data logging tags; and demonstrated the ability to collect geospatial behavioral chronologies with minimal missing data where recovery of data logging tags is precluded. Our strategy for developing a telemetry system may be applicable to any study requiring intelligent algorithms to continuously monitor behavior, and then compress those data into meaningful information that can be efficiently transmitted.

Wildlife Society Bulletin↗
USGS2024

From field station to forecast: Managing data at the Alaska Volcano Observatory

The Alaska Volcano Observatory (AVO) uses multidisciplinary data to monitor and study dozens of active and potentially active volcanoes. Here, we provide an overview of internally and externally generated data types, tools and resources used in their management, and challenges faced. Data sources include the following: (1) a multiparameter (seismic, infrasound, GNSS, web cameras) ground-based monitoring network that spans 3000 km and transmits data in real time; (2) a variety of satellite-borne sensors that provide information about surface change and volcanic emissions; (3) geologic and gas field campaigns; and (4) other external data products that provide situation awareness. Each data type requires distinct acquisition, processing, storage, visualization, and archiving approaches. AVO uses a variety of externally and internally developed tools to handle individual data types as well as multidisciplinary volcanological data. A primary tool is the Geologic Database of Information on Volcanoes in Alaska (GeoDIVA), which stores detailed, searchable information on more than 140 volcanoes and over 1000 eruptions and unrest events, including images, eruption descriptions, and geologic station and sample data, metadata, and analyses. It interacts with other internal tools that store monitoring reports and other operational records. Additional data management resources used by AVO assist with alarms and alerts, state-of-health monitoring, and multiparameter visualization. Requirements for 24/7 accessibility, the ever-expanding portfolio of data, and transitioning new tools from development to operations are all challenges faced by AVO and other volcano observatories. AVO strives to meet FAIR data practices and ensure that data are available to national and international community efforts using external repositories as well as those hosted by AVO and its parent institutions.

Alaska↗
USGS2021

Synthesizing and analyzing long-term monitoring data: A greater sage-grouse case study

Long-term monitoring of natural resources is imperative for increasing the understanding of ecosystem processes, services, and how to manage those ecosystems to maintain or improve function. Challenges with using these data may occur because methods of monitoring changed over time, multiple organizations collect and manage data differently, and monetary resources fluctuate, affecting many aspects of data. Because many species respond to changes in habitat conditions and predator-prey relationships across different spatial scales that span management boundaries, greater efforts for collaborating are essential. We demonstrate the challenges and methods for standardizing greater sage-grouse ( Centrocercus urophasianus ) long-term monitoring data across the species range in the western United States to inform population modeling needs identified by the Western Association of Fish and Wildlife Agencies. We used automated and repeatable methods of standardizing data via custom open-source software ( grsg_lekdb ) to improve the scientific integrity of future sage-grouse population assessments within and among states. Data standardization included reconciling uses of different terminology and expunging unusable data, resulting in the removal of 26% of data records due to database insertion errors and modifications to >1 million values to correct formatting and typing errors. Our approaches maximized the inclusion of usable data and identified data that could inform detection probabilities, population trends, and monitoring guidelines. Using sage-grouse databases as an example, we identified the importance of data management and how quality assurance and quality control measures can improve the usefulness of these data for future research needs. Our methods of using informatics and concluding recommendations can support similar endeavors of flora and fauna monitoring programs, whether those efforts are to use existing data or support new monitoring programs.

Ecological Informatics↗
USGS1999

Managing data from multiple disciplines, scales, and sites to support synthesis and modeling

The synthesis and modeling of ecological processes at multiple spatial and temporal scales involves bringing together and sharing data from numerous sources. This article describes a data and information system model that facilitates assembling, managing, and sharing diverse data from multiple disciplines, scales, and sites to support integrated ecological studies. Cross-site scientific-domain working groups coordinate the development of data associated with their particular scientific working group, including decisions about data requirements, data to be compiled, data formats, derived data products, and schedules across the sites. The Web-based data and information system consists of nodes for each working group plus a central node that provides data access, project information, data query, and other functionality. The approach incorporates scientists and computer experts in the working groups and provides incentives for individuals to submit documented data to the data and information system.

Remote Sensing of Environment↗
USGS1987

Design of a spatial data structure using the relational normal forms

In previous work, a relational data structure aimed at the exchange of spatial data between systems was developed. As this data structure was relational it was of first normal form, but compliance with the higher normal forms was not investigated. Recently, a new procedural method for composing fully normalized data structures from the basic data fields has been developed by H. C. Smith, as an alternative to the process of non-loss decomposition which is difficult to understand. Smith's method has been applied to data fields required to store points, lines and polygons in a chain-node spatial data model. When geographic domain, coverage layer and map are also considered, the procedure naturally leads to a catalogue model, needed for the exchange of spatial data. Although the method produces a fully normalized data structure, it is not as easy to identify which normal forms are responsible for the ultimate arrangement of the data fields into relations, but the benefits of these criteria for data base development also apply to spatial data structures and related ancillary data.

International Journal of Geographical Information ↗