AndreaBozzo/ceres-open-data-index huggingface dataset:
u571af.m77t: MGD77T data file for Geophysical data from field activity 71005 (U-5-71-AF) in Continental Margin Liberia from 10/30/1971 to 11/20/1971

Single-beam bathymetry, gravity, and magnetic data along with transit satellite navigation data was collected as part of field activity 71005 (U-5-71-AF) in Continental Margin Liberia from 10/30/1971 to 11/20/1971, http://walrus.wr.usgs.gov/infobank/u/u571af/html/u-5-71-af.meta.html
These data are reformatted from space-delimited ASCII text files located in the Coastal and Marine Geology Program (CMGP) InfoBank field activity catalog at http://walrus.wr.usgs.gov/infobank/u/u571af/html/u-5-71-af.bath.html http://walrus.wr.usgs.gov/infobank/u/u571af/html/u-5-71-af.grav.html http://walrus.wr.usgs.gov/infobank/u/u571af/html/u-5-71-af.mag.html into MGD77T format provided by the NOAA's National Geophysical Data Center(NGDC). The MGD77T format includes a header (documentation) file (.h77t) and a data file (.m77t). More information regarding this format can be found in the publication listed in the Cross_reference section of this metadata file.

Tags: africa, bathymetry, bathymetry-and-elevation, bathymetry-measurement, continental-margin-liberia, distributions, geoscientificinformation, gravimeter-measurement, gravimetry, liberia, magnetic-anomalies, magnetic-field-observations, magnetometer-measurement, marine-geology, marine-geophysics, marine-gravity-field, marine-magnetic-field, oceans, seafloor-topography, single-beam-echo-sounder, usgs-60a7b30c-4a28-4a2a-8421-2fb87f4fde1b, water-depth
Organization: Department of the Interior
Data for Continental-Scale Dispersal of Antimicrobial Resistant Bacteria by Alaska Landfill-Foraging Gulls

This data set includes information on collections of fecal samples from wild gulls (Larus spp.) at seven locations in Alaska, USA. Samples were screened for Escherichia coli (E. coli) and tested for resistance to multiple antibiotics.

Tags: adak, alaska, anchorage, animals-vertebrates, antibiotics, antimicrobial-agents, aquatic-birds, bacteria-archaea, bethel, biota, birds, cold-bay, disease-vectors, dna, dna-sequencing, drug-resistance-microbial, e-coli, ecological-dynamics, environment, evolutionary-adaptation, genetics, genomics, glaucous-gull, glaucous-winged-gull, health, health-and-disease, herring-gull, migratory-birds, nome, soldotna, species-population-interactions, usgs-asc338, utqiagvik, waders-gulls-auks-and-allies
Organization: Department of the Interior
Genetic Data from Barrow's Goldeneye and Common Goldeneye

This data set describes nuclear microsatellite genotypes derived from eight autosomal loci (Aph02, Aph11, Aalµ1, Sfiµ4, Smo4, Smo7, Smo12, and Sfiµ8) and accession numbers for double digest restriction-site associated DNA (ddRAD) sequences.

Tags: alaska, alleles, animals-vertebrates, barrows-goldeneye, biota, birds, british-columbia, bucephala-clangula, bucephala-islandica, canada, coastal-ecosystems, common-goldeneye, denmark, dna, environment, estuarine-habitat, gene-flow, genetic-markers, genetics, genotype, microsatellite-repeats, migratory-birds, ontario, polymerase-chain-reaction, population-genetics, terrestrial-ecosystems, usgs-asc339, waterfowl, wildlife, yukon-territory
Organization: Department of the Interior
National Park Service (ver. 10.0, January 2025)

The National Park Service (NPS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. The MTBS Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image of burn severity classes for all NPS-requested burn severity fires, occurring in CONUS. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires which were not discernable from available imagery.

Tags: ak, alaska, burn-severity, burned-area, continental-u-s, conus, differenced-normalized-burn-ratio, fire-location, fire-occurrence, hawaii, hi, imagerybasemapsearthcover, landsat, location, normalized-burn-ratio, nps, pr, prescribed-fire, puerto-rico, sentinel, united-states, us, usgs-62b1b9b7d34e74f0d80f132a, wildfire, wildland-fire
Organization: Department of the Interior
SPARROW model inputs and simulated streamflow, nutrient and suspended-sediment loads in streams of the Northeastern United States, 2012 Base Year

The U.S. Geological Survey's (USGS) SPAtially Referenced Regression On Watershed attributes (SPARROW) model was used to aid in the interpretation of monitoring data and simulate streamflow and water-quality conditions in streams across the Northeast Region of the United States. SPARROW is a hybrid empirical/process-based mass balance model that can be used to estimate the major sources and environmental factors that affect the long-term supply, transport, and fate of contaminants in streams. The spatially explicit model structure is defined by a river reach network coupled with contributing catchments. The model is calibrated by statistically relating watershed sources and transport-related properties to monitoring-based water-quality load estimates. This USGS data release includes input and output files associated with 2012 SPARROW simulations of streamflow, total nitrogen, total phosphorus and suspended-sediment load in streams of the Northeast region. Model construction, calibration and results are described in Ator (2019, https://doi.org/10.3133/sir20195118).

Tags: connecticut, delaware, district-of-columbia, maine, maryland, massachusetts, new-hampshire, new-jersey, new-york, nutrient-loads, pennsylvania, rhode-island, spatial-analysis, spatially-referenced-regression-on-watershed-attributes-sparrow, statistical-analysis, streamflow, surface-water-quality, suspended-sediment-loads, usgs-5d4192aee4b01d82ce8da477, vermont, virginia, west-virginia
Organization: Department of the Interior
Coastwide Reference Monitoring System (CRMS) 2005, 2008, 2012, 2016, 2018, and 2021 Site 4455 land-water matrix

Wetland restoration efforts conducted by the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in Louisiana rely on monitoring to determine the efficacy of these projects. The Coastwide Reference Monitoring System (CRMS) was developed to assist in a multiple-reference approach that uses aspects of hydrogeomorphic functional assessments and probabilistic sampling for monitoring. The CRMS program includes a suite of approximately 390 sites that encompass the range of hydrological and ecological conditions for each stratum. As part of CRMS, land and water classifications are created from Digital Orthophoto Quarter Quadrangles (DOQQs) approximately every three years at all CRMS sites. This dataset consists of a matrix of six land-water products (2005, 2008, 2012, 2016, 2018, and 2021).  The resulting matrix has 64 possible classes defined by the combination of land and water categories on those six dates.

Tags: alteration-of-wetland-habitats, cartography, coastal, coastal-louisiana, crms, doqq, emergent-wetland, forested-wetland, geographic-information-system, imagerybasemapsearthcover, land-water, louisiana, mapping, marsh, protection, restoration, scrub-shrub-wetland, state-of-louisiana, usgs-654150b2d34ee4b6e05bceca, wetland, wetland-ecosystems, wetland-restoration
Organization: Department of the Interior
Carbonatite whole-rock and calcite geochemistry from the Bear Lodge alkaline complex, Wyoming and Mountain Pass mine, California

Whole-rock and calcite geochemical data are reported for twelve carbonatite samples collected from the Bear Lodge alkaline complex, Wyoming and from the Mountain Pass mine, California. Calcite geochemical data was collected using electron microprobe and laser ablation inductively coupled plasma-mass spectrometry (LA-ICP-MS) analyses. Reported whole-rock data was measured by inductively coupled plasma-optical emission spectrometry (ICP-OES), inductively coupled plasma-mass spectrometry (ICP-MS), ion selective electrode-fluoride (ISE-F), and wavelength dispersive X-ray fluorescence (WDXRF). Geochemical data are presented in downloadable .csv files. Spatial data of sample collection sites are provided as polygons in a downloadable .shp file.

Tags: bear-lodge-mountains, black-hills, california, carbonatite, crook-county, geochemistry, geology-geophysics-and-geochemistry-science-center, gggsc, icp-ms, icp-oes, inductively-coupled-plasma-mass-spectrometry, inductively-coupled-plasma-optical-emission-spectrometry, ion-selective-electrode-fluoride, ise-f, la-icp-ms, laser-ablation-inductively-coupled-plasma-mass-spectrometry, microprobe, mineral-resources-program, mountain-pass-mine, mrp, rare-earth-elements, ree, san-bernardino-county, united-states-geological-survey, usgs, usgs-5cae1adae4b0c3b00654b2ff, wavelength-dispersive-x-ray-fluorescence, wdxrf, wyoming
Organization: Department of the Interior
Bathymetric survey of the Green River near Jensen, Utah, March 26-29, 2018

A topographic and bathymetric survey was collected along a reach of the Green River downstream of Dinosaur National Monument. The surveyed reach extends approximately 16 kilometers upstream and 6 kilometers downstream of the U.S. Route 40 bridge near Jensen, Utah. The topographic and bathymetric data include survey point data for 382 cross sections over 22 kilometers and are provided as a text file of easting, northing and elevation, in meters. The cross-section location data were collected using real-time kinematic Global Navigation Satellite Systems (GNSS) by USGS personnel from March 26, 2018, through March 29, 2018 using a combination of sound navigation and ranging (SONAR) and wading techniques.

Tags: dinosaur-national-monument, green-river, hydraulic-modeling, jensen, topographic-survey, usgs-5ace3660e4b0e2c2dd18462d, utah
Organization: Department of the Interior
5-Meter Sample Resolution Interferometric Swath Bathymetric Data Collected in 2011 from the Chandeleur Islands, Louisiana (U.S. Geological Survey Field Activity Number 11BIM01)

As part of the Barrier Island Evolution Research Project, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center conducted nearshore geophysical surveys off the northern Chandeleur Islands, Louisiana, in June of 2011. The overall objectives of the study are to better understand barrier-island geomorphic evolution, particularly storm-related depositional and erosional processes that shape the islands over annual to interannual timescales (1-5 years). Collection of geophysical data will allow us to identify relationships between the geologic history of the island and its present day morphology and sediment distribution. This mapping effort was the first in a series of three planned surveys in this area. High resolution geophysical data collected in each of three consecutive years along this rapidly changing barrier-island system will provide a unique time-series dataset that will significantly further the analyses and geomorphological interpretations of this and other coastal systems, improving our understanding of coastal response and evolution over short time scales (1-5 years).
This report serves as an archive of processed interferometric swath and single-beam bathymetry data that were collected during two cruises (USGS Field Activity Numbers 11BIM01 and 11BIM02) along the northern portion of the Chandeleur Islands, Breton National Wildlife Refuge, Louisiana, in June of 2011. Geographic information system data products include a 50 m-cell-size interpolated bathymetry grid surface, trackline maps, and point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata.

Tags: 11bim01, barrier-island-evolution-research-project, barrier-island-mapping, bathymetry, chandeleur-islands, chandeleur-sound, cmgp, coastal-and-marine-geology-program, elevation, geophysical, geoscientificinformation, gulf-of-mexico, hydrography, imagerybasemapsearthcover, interferometry, louisiana, marine-geology, oceans, sea, spcmsc, st-petersburg-coastal-and-marine-science-center, swath, swathplus-m, systems-engineering-and-assessment, u-s-geological-survey, usgs, usgs-c9780e25-9eb3-4367-8c06-6cee8ea4a1ce
Organization: Department of the Interior
Digital elevation models (DEMs) of the Elwha River delta, Washington, July 2015

This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in July 2015. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity to examine the response of a delta system to changes in sediment supply. The U.S. Geological Survey developed an integrated research program aimed at understanding the ecosystem responses following dam removal that included regular monitoring of coastal and nearshore bathymetry and topography. As part of this monitoring program, the USGS conducted a bathymetric and topographic survey in the Strait of Juan de Fuca on the Elwha River delta, Washington (USGS Field Activity Number 2015-648-FA). Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite systems (GNSS). Topography data were collected on foot with GNSS receivers mounted on backpacks. DEM surfaces were produced from all available elevation data using linear interpolation.

Tags: bathymetry, bathymetry-and-elevation, bathymetry-measurement, digital-elevation-models, echo-sounders, elevation, global-positioning-system-gps-observations, gps-global-positioning-system, gps-measurement, single-beam-echo-sounder, topographic-mapping, topography, usgs-5807e811e4b0841e59e3a543, water-depth
Organization: Department of the Interior
Marine Arctic polygon distribution of Inconnu (Stenodus leucichthys) (Güldenstadt, 1772)

Region(s) of distribution of Inconnu (Stenodus leucichthys) (Güldenstadt, 1772) in the Arctic as digitized for U.S. Geological Survey Scientific Investigations Report 2016-5038. For details on the project and purpose, see the report at https://doi.org/10.3133/sir20165038. Complete metadata for the collection of species datasets is in the metadata document "Dataset_for_Alaska_Marine_Fish_Ecology_Catalog.xml" at https://doi.org/10.5066/F7M61HD7. Source(s) for this digitized data layer are listed in the metadata Process Steps section. Note that the original source may show an extended area; some datasets were limited to the published map boundary. Distributions of marine fishes are shown in adjacent Arctic seas where reliable data are available. The data were clipped to show only the marine distribution areas although some species also may have an inland presence.

Tags: alaska, arctic, beaufort-sea, bering-sea, bering-strait, biogeography, chukchi-beaufort-lease-area, chukchi-sea, distributions, ecology, fish, guldenstadt-1772, inconnu, marine, marine-fishery-resources, northeast-russia, northwest-canada, northwest-territories, nunavut, stenodus-leucichthys, u-s-exclusive-economic-zone, usgs-58812e60e4b00a062356ffde, yukon
Organization: Department of the Interior
ST3_Final_DEM_metadata: Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs without restoration alternative for storminess bins (ST1-ST4) and sea level rise scenarios (SL1-SL3).

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

Tags: alabama, alongshore-transport, barrier-island, bathymetry, biota, coastal, coastal-processes, dauphin-island, decadal, dem, digital-elevation-models, elevation, geomorphology, gulf-of-mexico, marine-geology, morphologic-change, north-america, ocean-waves, oceans, sea-level-change, sediment-transport, spcmsc, st-petersburg-coastal-and-marine-science-center, tides-oceanic, topography, u-s-geological-survey, united-states, usgs, usgs-72e859ab-0a78-470f-9562-5b97a9720911
Organization: Department of the Interior
Stream-stage Dataset at Peck Canyon near Nogales, Arizona, geographic NAD83 (Water Years 2016–2017)

This dataset contains stream-stage data for Peck Canyon near Rio Rico, Arizona (PC1).  The pressure transducer was housed in a crest-stage pipe mounted to the bridge pier of West Frontage Road. The data were recorded using non-vented Solinst Levelogger for the period of October 7, 2015 to December 31, 2016. The data were logged continuously at a 15-minute interval and manually downloaded. Data were corrected with the atmospheric pressure collected from a Solinst Barologger located at SC14 and checked for erroneous data.

Tags: dna, e-coli, escherichia-coli, stage, tumacacori-national-historical-park, upper-santa-cruz-river, usgs-592efbade4b0e9bd0ea79387, water, water-quality
Organization: Department of the Interior
Land Cover Estimates for the Kenai Peninsula Lowlands, 1973, 2002, and 2017

These raster images represent continuous surfaces of estimated land cover types for the western Kenai Peninsula circa 1973, circa 2002, and circa 2017. The estimated land cover types (Needleleaf Forest, Mixed Forest, Broadleaf Forest, Herbaceous, Wetland, Alpine, Barren, Shrub, Water) were derived from a random forest classifier executed in R (version 3.5.0). Predictor variables from training data included known landcover types deduced from high resolution aerial imagery, summer and winter spectral indices obtained from historical Landsat scenes, and topographic parameters derived from a digital elevation model. For each era (c. 1973, c. 2002, and c. 2017) 3,600 training points (400 points for each land cover type) were randomly distributed within training areas and training areas were opportunistically distributed to capture the regional and geomorphic extent of each land cover type to the extent possible given availability of aerial imagery. Each training point was assigned feature list values from the Landsat mosaics and digital elevation model while land cover was manually interpreted using high-resolution areal imagery. Model output includes predicted landcover types and was rasterized for each era to illustrate the classification of landcover.

Tags: alaska, biota, environment, forest-ecosystems, kenai-peninsula, land-use-and-land-cover, multispectral-imaging, reforestation, remote-sensing, spatial-analysis, usgs-asc320, vegetation-index
Organization: Department of the Interior
Land Cover Series Estimates for the Kenai Peninsula Lowlands; 1973, 2002, and 2017

These raster images represent continuous surfaces of estimated land cover types for the western Kenai Peninsula circa 1973, circa 2002, and circa 2017. This raster image represents the coded series of estimated land cover types for each pixel over the three distinct time periods. The estimated land cover types (Needleleaf Forest, Mixed Forest, Broadleaf Forest, Herbaceous, Wetland, Alpine, Barren, Shrub, Water) were originally derived from a random forest classifier executed in R (version 3.5.0). Predictor variables from training data included known landcover types deduced from high resolution aerial imagery, summer and winter spectral indices obtained from historical Landsat scenes, and topographic parameters derived from a digital elevation model. For each era (c. 1973, c. 2002, and c. 2017) 3,600 training points (400 points for each land cover type) were randomly distributed within training areas and training areas were opportunistically distributed to capture the regional and geomorphic extent of each land cover type to the extent possible given availability of aerial imagery. Each training point was assigned feature list values from the Landsat mosaics and digital elevation model while land cover was manually interpreted using high-resolution areal imagery. Model output included predicted landcover type and a corresponding probability score and were rasterized for each era – one raster image featuring land cover types and one raster image featuring land cover type probability. This raster image characterizes a coded series that represents the unique combinations (or series) of vegetation types that pixels experienced over time. Each cell's series value corresponds to a series of numbers (#_#_#) where the first number is the vegetation code from 1973, the middle number is the vegetation code from 2002 and the last number is the vegetation code from 2017. Raster values (1-687) can be translated into series using the vegetation_code_series_table.csv. Series numbers can be translated into vegetation types using the vegetation_class_table.csv. The code series raster image allows for the graphical depiction of certain landcover change types such as deforestation (e.g. Forest_Forest_Shrub) and has 30 meter resolution. 

Tags: alaska, desktop-geographic-information-systems, environment, forest-ecosystems, image-collections, kenai-peninsula, land-use-and-land-cover, multispectral-imaging, reforestation, remote-sensing, spatial-analysis, usgs-asc321, vegetation-index
Organization: Department of the Interior
Probability of Land Cover Classification Estimates for the Kenai Peninsula Lowlands; 1973, 2002, and 2017

The raster image represents a continuous surface of estimated land cover type probabilities for the western Kenai Peninsula circa 1973, circa 2002, and circa 2017. The estimated land cover types (Needleleaf Forest, Mixed Forest, Broadleaf Forest, Herbaceous, Wetland, Alpine, Barren, Shrub, Water) were derived from a random forest classifier executed in R (version 3.5.0). Predictor variables from training data included known landcover types deduced from high resolution aerial imagery, summer and winter spectral indices obtained from historical Landsat scenes, and topographic parameters derived from a digital elevation model. For each era (c. 1973, c. 2002, and c. 2017) 3,600 training points (400 points for each land cover type) were randomly distributed within training areas and training areas were opportunistically distributed to capture the regional and geomorphic extent of each land cover type to the extent possible given availability of aerial imagery. Each training point was assigned feature list values from the Landsat mosaics and a digital elevation model while land cover was manually interpreted using high-resolution areal imagery. Model output included predicted landcover type and a corresponding probability score and were rasterized for each era with the raster image featuring land cover type probability. For the 1973 era, these raster images are at a 60 meter resolution. For the 2002 and 2017 era, raster image resolution is 30 meters.

Tags: alaska, desktop-geographic-information-systems, environment, forest-ecosystems, image-collections, kenai-peninsula, land-use-and-land-cover, multispectral-imaging, reforestation, remote-sensing, spatial-analysis, usgs-asc322, vegetation-index
Organization: Department of the Interior