AndreaBozzo/ceres-open-data-index huggingface dataset:
USGS T-3 Original Thermal Gradient, Thermal Conductivity, and Heat Flow Data from T-3 Ice Island, 1963-73

The T-3 (Fletcher's) Ice Island in the Arctic Ocean was the site of a scientific research station re-established by the Naval Arctic Research Laboratory starting in 1962. Starting in 1963, the USGS acquired marine heat flow data and coincident sediment cores at sites in Canada Basin, Nautilus Basin, Mendeleev Ridge, and Alpha Ridge as the ice island drifted in the Amerasian Basin. At least 584 heat flow penetrations were attempted, and data were reported at 356 of these. This dataset is the digital version of the original data table from Lachenbruch and others (2019; see cross-reference), retaining the original non-SI units for thermal conductivity and heat flow.

Tags: alpha-ridge, amerasian-basin, arctic, arctic-ocean, canada-basin, chukchi-plateau, cmhrp, coastal-and-marine-hazards-and-resources-program, field-monitoring-stations, fletchers-ice-island, geoscientificinformation, heat-flow-earth, lamont-doherty-earth-observatory, lamont-geological-observatory, location, marine-geology, marine-heat-flow, mendeleev-ridge, nautilus-basin, navigation, navigational-data, oceans, t-3-ice-island, u-s-geological-survey, usgs, usgs-5d10eb5be4b0941bde550217, whcmsc, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
USGS T-3 enhanced thermal data from T-3 Ice Island, 1963-73

The T-3 (Fletcher's) Ice Island in the Arctic Ocean was the site of a scientific research station re-established by the Naval Arctic Research Laboratory starting in 1962. Starting in 1963, the USGS acquired marine heat flow data and coincident sediment cores at sites in Canada Basin, Nautilus Basin, Mendeleev Ridge, and Alpha Ridge as the ice island drifted in the Amerasian Basin. At least 584 heat flow penetrations were attempted, and data were reported at 356 of these. This dataset is the enhanced version of the original data table from Lachenbruch and others (2019; see cross-reference), incorporating additional information such as the probable dates of measurement, physiographic province and surficial geology at each station, and the length of recovered cores.  In addition, this dataset converts the original units to SI units and the positions to decimal degrees.

Tags: alpha-ridge, amerasian-basin, arctic, arctic-ocean, canada-basin, chukchi-plateau, cmhrp, coastal-and-marine-hazards-and-resources-program, field-monitoring-stations, fletchers-ice-island, geoscientificinformation, heat-flow-earth, lamont-doherty-earth-observatory, lamont-geological-observatory, location, marine-geology, marine-heat-flow, mendeleev-ridge, nautilus-basin, navigation, navigational-data, oceans, t-3-ice-island, u-s-geological-survey, usgs, usgs-5d10eb42e4b0941bde550210, whcmsc, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
T-3 Ice Island One Hour Navigation: May 14, 1962 to September 15, 1974

The T-3 (Fletcher's) Ice Island in the Arctic Ocean was the site of a scientific research station re-established by the Naval Arctic Research Laboratory starting in 1962. Lamont Geological Observatory (LGO; now Lamont-Doherty Earth Observatory) and the U.S. Geological Survey, along with other organizations, ran research laboratories on the island during the 1960s and early 1970s as the island drifted in the Amerasian Basin. LGO compiled navigational data, measured gravity and magnetic data, and conducted seismic surveys to image the seafloor. This data release provides the edited LGO-compiled 1 hour navigational data for T-3 from May 1962 until September 1974, along with gravity and magnetic data and calculated anomalies on the same hourly intervals.

Tags: alpha-ridge, amerasian-basin, arctic, arctic-ocean, canada-basin, chukchi-plateau, cmhrp, coastal-and-marine-hazards-and-resources-program, field-monitoring-stations, fletchers-ice-island, geoscientificinformation, gravity-anomaly, lamont-doherty-earth-observatory, lamont-geological-observatory, location, magnetic-anomaly, marine-geology, marine-heat-flow, mendeleev-ridge, nautilus-basin, navigation, navigational-data, oceans, t-3-ice-island, u-s-geological-survey, usgs, usgs-5d10eb1ae4b0941bde550208, whcmsc, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
Range-wide habitat suitability maps for at-risk species in the longleaf system

The data contained in child items of this page were developed to support the Species Status Assessments conducted by the U.S. Fish &amp; Wildlife Service and conservation planning for State, Federal, and non-government researchers, managers, landowners, and other partners for five focal herpetofauna species: gopher tortoise (Gopherus polyphemus), southern hognose snake (Heterodon simus), Florida pine snake (Pituophis melanoleucus mugitus), gopher frog (Lithobates capito), and striped newt (Notophthalmus perstriatus). These data were developed by the USGS Cooperative Fish &amp; Wildlife Research Unit at the University of Georgia in collaboration with other partners.
The three child items contain the following data: (1) responses of species experts, elicited from online surveys and in-person workshops, reflecting environmental, ecological, climatic, anthropogenic, or other attributes influential to each of the five focal species' status in the Southeast; (2) a spatial geodatabase of polygon feature layers representing habitat suitability classes (low, moderate, and high suitability) for each species, as estimated from range-wide habitat suitability models; and (3) a spatial geodatabase of rasters produced from the same habitat suitability models whose values range from 0 (least suitable habitat for the species) to 100 (most suitable). Collectively, the habitat suitability polygons and rasters extend across the range of these species in the Southeast US, including areas in Louisiana, Mississippi, Alabama, Florida, Georgia, South Carolina, and North Carolina.
A full discussion of the compilation methodology and sources used to develop the habitat suitability data is available in the accompanying publication: Crawford, B.A., J.C. Maerz, &amp; C.T. Moore. 2020. Expert-informed habitat suitability analysis for at-risk species assessment and conservation planning. Journal of Fish and Wildlife Management. in review.

Tags: alabama, at-risk-species, biota, coastal-plain, florida, georgia, habitat-suitability, longleaf-pine-system, louisiana, mississippi, north-carolina, south-carolina, southeast-us, usgs-5d0d2d45e4b0941bde52a20d
Organization: Department of the Interior
Land cover map including wetlands and invasive Phragmites circa 2017 for SE Michigan and NW Ohio

The first basin-wide map of large stands of invasive Phragmites australis (common reed) in the coastal zone was created through a collaboration between the U.S. Geological Survey and Michigan Tech Research Institute (Bourgeau-Chavez et al 2013). This data set represents a revised version of that map and was created using multi-temporal PALSAR data and Landsat images from 2016-2017. In addition to Phragmites distribution, the data sets shows several land cover types including urban, agriculture, forest, shrub, emergent wetland, forested wetland, and some based on the dominant plant species (e.g., Schoenoplectus, Typha). The classified map was validated using over 400 field visits.This map covers the coastal regions of Michgan along the southern portion Lake Huron including Saginaw Bay, Lake St. Clair, Lake Erie, and northeastern Ohio.

Tags: imagerybasemapsearthcover, invasive-species, lake-huron, land-use-and-land-cover, michigan, ohio, usgs-5d0ce92ce4b0941bde51dd61, wetlands
Organization: Department of the Interior
Land cover map including wetlands and invasive Phragmites circa 2017 for Central Lake Erie

The first basin-wide map of large stands of invasive Phragmites australis (common reed) in the coastal zone was created through a collaboration between the U.S. Geological Survey and Michigan Tech Research Institute (Bourgeau-Chavez et al 2013). This data set represents a revised version of that map and was created using multi-temporal PALSAR data and Landsat images from 2016-2017. In addition to Phragmites distribution, the data sets shows several land cover types including urban, agriculture, forest, shrub, emergent wetland, forested wetland, and some based on the dominant plant species (e.g., Schoenoplectus, Typha). The classified map was validated using over 400 field visits.This map covers the Southern portion of central Lake Erie.

Tags: imagerybasemapsearthcover, invasive-species, lake-erie, land-use-and-land-cover, ohio, usgs-5d0ce8ebe4b0941bde51da6f, wetlands
Organization: Department of the Interior
Sediment Concentration and Velocity Data to Assess Trapping by Submerged Vegetation

The acoustic Doppler current meter (ADCP) used in this study outputs binary data files containing measurement scheme, location, time, velocity, backscatter, boat heading, depth, and other parameters. These data are provided here in the manufacturer's "classic ASCII" format, as described in READMEforADCP.txt file associated with this data release.
We also collected water samples for suspended-sediment concentration, with co-located ADCP backscatter data. These data are provided in a separate file indicating date, time, and location of these observations.
Data were collected at three locations in Sacramento-San Joaquin River Delta in California: Lindsey Slough; Mokelumne River; and Old River.

Tags: aquatic-vegetation, central-valley, invasive-species, sacramento-san-joaquin-delta, sediment-transport, surface-water, usgs-5d0c1550e4b0941bde4fca84
Organization: Department of the Interior
Annual peak-flow data and PeakFQ output files for selected streamflow gaging stations operated by the U.S. Geological Survey in the New England region that were used to estimate regional skewness of annual peak flows

"NewEngland_pkflows.txt" contains annual peak-flow data for 186 selected streamflow gaging stations (streamgages) operated by the U.S. Geological Survey (USGS) in the New England region (Maine, Connecticut, Massachusetts, Rhode Island, New York, New Hampshire, and Vermont).  Only streamgages in the region that were also in the USGS "GAGES II" database (https://water.usgs.gov/GIS/metadata/usgswrd/XML/gagesII_Sept2011.xml) were considered for use in the study.  The annual peak-flow data were obtained from the USGS National Water Information System (NWIS) database (https://nwis.waterdata.usgs.gov/usa/nwis/peak) and contain annual peak flows ending in water year 2011.  The annual peak flows were used in version 7.0 of USGS software PeakFQ (https://water.usgs.gov/software/PeakFQ/; Veilleux and others, 2014; Flynn and others, 2006) to conduct flood-frequency analyses using the Expected Moments Algorithm (EMA; England and others, 2018).  Data contained in the PeakFQ output (.PRT) files (also included in this data release) were then used to estimate regional skewness of the annual peak flows using Bayesian Weighted Least Squares / Bayesian Generalized Least Squares (B-WLS / B-GLS) regression (Veilleux and others, 2019).

Tags: bayesian-regression, bulletin-17b, connecticut, ema, expected-moments-algorithm, flood-frequency, great-lakes-region-2-digit-hydrologic-unit-code-04, maine, massachusetts, mid-atlantic-region-2-digit-hydrologic-unit-code-02, new-england-region-2-digit-hydrologic-unit-code-01, new-hampshire, new-york, peakfq, regional-skew, rhode-island, usgs-5d0be0d1e4b0941bde4fc889, vermont
Organization: Department of the Interior
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2013–2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.

Tags: atlantic-ocean, barrier-island, cmgp, coastal-and-marine-geology-program, coastal-habitat, coastal-processes, environment, erosion, gateway-national-recreation-area, geographic-information-systems, geomorphology, geospatial-analysis, geospatial-datasets, gis, hazards, image-analysis, long-island, mean-high-water, mhw, new-york, north-america, ny, oceans, rockaway-peninsula, scientific-interpretation, sea-level-change, st-petersburg-coastal-and-marine-science-center, study-areas, u-s-geological-survey, united-states, usa, usgs, usgs-5d0bc97de4b0941bde4fc670, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rockaway Peninsula, NY, 2013–2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.

Tags: atlantic-ocean, barrier-island, bayesian-network, cmgp, coastal-and-marine-geology-program, coastal-erosion, coastal-habitat, coastal-hazards, coastal-processes, environment, erosion, gateway-national-recreation-area, geographic-information-systems, geomorphology, geoscientificinformation, geospatial-analysis, geospatial-datasets, gis, hazards, land-use-and-land-cover, long-island, mean-high-water, mhw, new-york, north-america, ny, probability, rockaway-peninsula, sea-level-change, sea-level-rise, shoreline-change, st-petersburg-coastal-and-marine-science-center, transect-sampling, u-s-geological-survey, united-states, usa, usgs, usgs-5d0bc979e4b0941bde4fc66c, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
ElevMHW: Elevation adjusted to local mean high water: Rockaway Peninsula, NY, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.

Tags: atlantic-ocean, barrier-island, cmgp, coastal-and-marine-geology-program, coastal-habitat, digital-elevation-models, elevation, gateway-national-recreation-area, geographic-information-systems, geomorphology, geospatial-analysis, geospatial-datasets, gis, lidar, long-island, mean-high-water, mhw, new-york, north-america, ny, oceans, rockaway-peninsula, st-petersburg-coastal-and-marine-science-center, topography, u-s-geological-survey, united-states, usa, usgs, usgs-5d0bc978e4b0941bde4fc66a, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
DisOcean: Distance to the ocean: Rockaway Peninsula, NY, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.

Tags: atlantic-ocean, barrier-island, cmgp, coastal-and-marine-geology-program, coastal-habitat, environment, gateway-national-recreation-area, geographic-information-systems, geomorphology, geospatial-analysis, geospatial-datasets, gis, long-island, mean-high-water, mhw, new-york, north-america, ny, oceans, rockaway-peninsula, st-petersburg-coastal-and-marine-science-center, u-s-geological-survey, united-states, usa, usgs, usgs-5d0bc976e4b0941bde4fc668, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Rockaway Peninsula, NY, 2013–2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.

Tags: atlantic-ocean, barrier-island, bayesian-network, biota, charadrius-melodus, cmgp, coastal-and-marine-geology-program, coastal-habitat, ecology, environment, foraging-ecology, gateway-national-recreation-area, geographic-information-systems, geography, geomorphology, geospatial-analysis, geospatial-datasets, gis, long-island, mean-high-water, mhw, new-york, north-america, ny, piping-plovers, rockaway-peninsula, st-petersburg-coastal-and-marine-science-center, u-s-geological-survey, united-states, usa, usgs, usgs-5d0bc974e4b0941bde4fc666, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior