AndreaBozzo/ceres-open-data-index huggingface dataset:
LEAN-Corrected Collier County DEM for wetlands

Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation model (DEM) for wetlands throughout Collier county using a modification of  the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (15,223 points), NAIP-derived Normalized Difference Vegetation Index (2010), a 10 m lidar DEM from 2007, and a 10 m canopy surface model were used to generate a model of predicted bias across marsh, mangrove, and cypress habitats. The predicted bias was then subtracted from the original lidar DEM, masked by wetlands areas using polygons from the National Wetland Inventory dataset, and merged with the original lidar DEM. Only the area covered by the 2007 lidar was corrected; a piece of the inland area not covered by lidar was interpolated with the GPS survey data and merged with the corrected DEM. Lidar from 2017, which covers a narrow coastal strip, was also incorporated by first masking out the wetland areas and then mosaiking with the final DEM.  Across all GPS points, mean initial lidar error was 34.3 cm (SD=28.2) and root-mean squared error (RMSE) was 44.5 cm. After correction with LEAN, mean error was 0 (SD=18.9) and RMSE was 18.9 cm, a 57.3 percent improvement in accuracy. 
References: Buffington, K.J., Dugger, B.D., Thorne, K.M. and Takekawa, J.Y., 2016. Statistical correction of lidar-derived digital elevation models with multispectral airborne imagery in tidal marshes. Remote Sensing of Environment, 186, pp.616-625.

Tags: cypress, digital-elevation-models, elevation, estuary, lidar, mangroves, marsh, usgs-5d8a4c14e4b0c4f70d0ae668, wetlands
Organization: Department of the Interior
Tracking Data for Blue-winged Teal (Anas discors)

This data release includes 2 child items with tracking data for Blue-winged Teal, a duck species that breeds throughout much of North America and whose wintering range includes neotropical areas of the Caribbean and Central and South America, thus providing a migratory link between the continents of North and South America.
      Child Item 1: "Argos Satellite Tracking Data for Blue-winged Teal (Anas discors) - Processed Data" -- Quality-controlled data collected from Argos satellite transmitters.
      Child Item 2: "Argos Satellite Tracking Data for Blue-winged Teal (Anas discors) - Raw Data" -- All raw data collected from Argos satellite transmitters, provided for completeness of the archive. The quality-controlled, "Argos Processed Data" (Child Item 1) are better suited for most analytical purposes.

Tags: alberta, anas-discors, animal-tracking, animals-vertebrates, argos, bahamas, beaumont, biota, birds, blue-winged-teal, breeding-area, breeding-sites, brooks, canada, central-flyway, cuba, distribution, ducks-geese-swans, ecological-dynamics, environment, field-methods, field-sampling, galveston-bay, gulf-of-mexico, livonia, louisiana, mexico, migration, migration-organisms, migration-pathway, migratory-birds, migratory-strategies, ornithology, overwintering, platform-transmitter-terminal, port-barre, ptt, saskatchewan, satellite-transmitter, seasonal-distribution, seasonal-movement, species-life-history, species-migration, telemetry, texas, tracking-equipment, usgs-5d8a48e7e4b0c4f70d0ae636, vanscoy, wildlife, wintering-area
Organization: Department of the Interior
Process-guided deep learning water temperature predictions: 4c All lakes historical training data

Observed water temperatures from 1980-2018 were compiled for 68 lakes in Minnesota and Wisconsin (USA). These data were used as training data for process-guided deep learning models and deep learning models, and calibration data for process-based models. The data are formatted as a single csv (comma separated values) file with attributes corresponding to the unique combination of lake identifier, time, and depth. Data came from a variety of sources, including the Water Quality Portal, the North Temperate Lakes Long-Term Ecological Research Project, and digitized temperature records from the MN Department of Natural Resources.

Tags: biota, climate-change, deep-learning, environment, hybrid-modeling, inlandwaters, machine-learning, minnesota, mn, modeling, reservoirs, temperate-lakes, temperature, thermal-profiles, united-states, us, usgs-5d8a47bce4b0c4f70d0ae61f, water, wi, wisconsin
Organization: Department of the Interior
Principal facts of gravity data collected in and around the eastern Adirondack highlands, northern New York

Gravity data were collected in 2016 and 2017 to assist in mapping subsurface geology in and around the eastern Adirondack highlands, northern New York, which host numerous iron-oxide apatite deposits. Many of these deposits contain rare-earth elements, which are considered a critical mineral resource.  This data release provides principal facts for 189 new gravity stations that were acquired to fill in gaps in the existing public gravity data coverage.

Tags: addison-county, adirondack-highlands, bouguer-anomaly, critical-mineral-resources, essex-county, free-air-anomaly, geology-geophysics-and-geochemistry-science-center, geoscientificinformation, gggsc, gravimeter-measurement, gravitational-field-earth, iron-oxide-apatite-deposits, isostatic-anomaly, mineral-deposits, mineral-resources-program, mrp, new-york, rare-earth-elements, u-s-geological-survey, usgs, usgs-5d8a451be4b0c4f70d0ae606, vermont
Organization: Department of the Interior
Northeast region: Supporting information for attribution of trends and change points

This metadata file describes a comma separated values (csv) file of data used to support attribution of trends and change points in annual peak streamflows observed at gages in the Northeast region. The file includes USGS gage identification and location information, developed land cover and basin storage data, correlation results between annual peak magnitudes and precipitation and Palmer Drought Severity Index (PDSI), and trend and change point results for precipitation and PDSI.

Tags: datasets, flooding, peak-flow, trends, usgs-5d8a2f4be4b0c4f70d0ae557
Organization: Department of the Interior
Organic and metal contaminants in fish tissue collected from the Buffalo River Area of Concern, 2017

Fish tissue from 159 samples collected at four locations in the Buffalo River Area of Concern in 2017 were analyzed for a wide range of analytes including Polychlorinated Biphenyls (PCBs), pesticides, polycyclic aromatic hydrocarbons, organochlorine and other persistent organic compounds, metals, lipid and moisture.  Over 230 analytes were analyzed in the tissue samples, including 160 PCB congeners.  The data set includes a variety of laboratory quality assurance data including sample replicates, laboratory blank data, laboratory spike data, matrix spike recoveries, and replicate matrix spike recoveries.

Tags: contamination-and-pollution, ecotoxicology, environmental-quality, erie, fish-tissue, new-york, organochlorine-pesticides, pahs, polychlorinated-biphenyls-pcbs, sediment-pollution, usgs-5d8a0c2ee4b0c4f70d0ae4f9, water-quality
Organization: Department of the Interior
Process-guided deep learning water temperature predictions: 3 Model inputs (meteorological inputs and ice flags)

This dataset includes model inputs (specifically, weather and flags for predicted ice-cover) and is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD).

Tags: 007, 012, climate-change, deep-learning, environment, hybrid-modeling, inlandwaters, machine-learning, minnesota, mn, modeling, reservoirs, temperate-lakes, temperature, thermal-profiles, united-states, us, usgs-5d89d90ce4b0c4f70d0ae4df, water, wi, wisconsin
Organization: Department of the Interior
Tillage Practices in the Conterminous United States, 1989-2004--Datasets Aggregated by Watershed; tillage_lu92e

This dataset is an aggregation of county-level tillage practices to the 8-digit hydrologic unit watershed. 
The original county-level data were collected by the Conservation Technology Information Center (CTIC) 
and is a proprietary dataset. The CTIC collects tillage data by conducting surveys about tillage systems 
for all counties in the United States. Watershed aggregations were done by overlying the 8-digit HUC 
polygons with a raster of county boundaries and a raster of the 1992 enhanced National Land Cover 
Data for land use 61, 62, 82, 83, and 84 (cultivated land) to derive a county/land-use area weighting factor. 
The weighting factor was then applied to the county-level tillage data for the counties within each 8-digit 
HUC and summed to yield the total acreage of each tillage type within each 8-digit HUC watershed. 
Tillage systems include three types of conservation tillage (no-till, ridge-till, and mulch-till), reduced tillage, 
and intensive tillage. Total planted acreage for each tillage practice for each crop grown is reported to the 
CTIC.The dataset includes total planted acreage by tillage type for selected crops (corn, cotton, grain 
sorghum, soybeans, fallow, forage, newly established permanent pasture, spring and fall seeded small 
grains, and "other" crops) for 1989-2004. The CTIC did not collect data nationwide for 1999, 2001, and 
2003. In addition, data were not collected for all counties every year. Missing data are coded with -9999. 
The companion WBDHUC8 geospatial dataset is available online: 
https://water.usgs.gov/lookup/getspatial?wbdhuc8.xml .

Tags: agricultural-land, conterminous-u-s, crop-residue-management, inland-waters, inlandwaters, planted-acreage, tillage-practice, usgs-5d89a46c-42ef-40c1-9aca-5804502ef1d3
Organization: Department of the Interior
DRAINMOD simulations for two agricultural drainage sites in western Fillmore County, southeastern Minnesota

DRAINMOD, a field-scale, process-based, distributed model (Skaggs, 1980; https://www.bae.ncsu.edu/agricultural-water-management/DRAINMOD/), was used to simulate subsurface drainage flow and field water-surface elevations. DRAINMOD simulations are often used to optimize drainage patterns for agricultural fields with subsurface drainage. For this study, the model results were also used to simulate deep seepage rates. Deep seepage is the amount of water that moves past the agricultural drains. These deep seepage rates were then used as a surrogate for potential groundwater recharge rates. A total of nine different scenarios were run, each sceanrio corresponding to a different location on one of three different field sites (two drained sites, one undrained site). All of the different scenarios and model results are discussed in the associated Scientific Investigations Report, https://doi.org/10.5033/sir20205006.

Tags: deep-seepage, drainmod, environment, groundwater, inlandwaters, usgs-5d893455e4b0c4f70d0ae166
Organization: Department of the Interior
Potential groundwater recharge estimates based on a groundwater rise analysis technique for two agricultural sites in southeastern Minnesota, 2016-2018

A water table fluctuation model simulated potential recharge rates from 2016 to 2018 for two agricultural sites in southeastern Minnesota. The model calculated potential recharge rates through the analysis of groundwater rises. A total of 42 piezometers were analyzed for this study using the water table fluctuation model. This methodology of calculating potential recharge rates was used as an independent method from two other methods: a soil-water-balance model (https://doi.org/10.5066/P90N4AWG), and DRAINMOD (https://doi.org/10.5066/P987N30U).

Tags: environment, groundwater, rise-model, usgs-5d88f17de4b0c4f70d0ab3e5, water-table-fluctuation
Organization: Department of the Interior
USGS National and Global Oil and Gas Assessment Project - Appalachian Basin Province, Point Pleasant Formation and Utica Shale Assessment Unit Boundaries and Assessment Input Data Forms

This data release contains the boundaries of assessment units and input data for the assessment of undiscovered gas hydrate resources on the north slope of Alaska.  The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources.  The Assessment Unit is defined within the context of the higher-level Total Petroleum System.  The Assessment Unit is shown herein as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type.  The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies.  The only exceptions to this are Assessment Units that border the Federal-State water boundary.  In these cases, the Federal-State water boundary forms part of the Assessment Unit boundary.  Methodology of assessments are documented in USGS Data Series 547 for continuous assessments (https://pubs.usgs.gov/ds/547) and USGS DDS69-D, Chapter 21 for conventional assessments (https://pubs.usgs.gov/dds/dds-069/dds-069-d/REPORTS/69_D_CH_21.pdf).  See supplemental information for a detailed list of files included this data release.

Tags: assessment-unit, continuous-assessment-unit, energy-resources, geology, geoscientificinformation, logana-shale-gas, logana-shale-oil, national-assessment-of-oil-and-gas, natural-gas, natural-gas-resources, noga2000, oil, oil-resources, oilgas, petroleum, point-pleasant-utica-foldbelt-gas, point-pleasant-utica-shale-gas, point-pleasant-utica-shale-oil, resource-assessment, state-of-kentucky, state-of-maryland, state-of-new-york, state-of-ohio, state-of-pennsylvania, state-of-virginia, state-of-west-virginia, unconventional-assessment-unit, united-states-of-america, usgs-5d87dd9fe4b0c4f70d0aaf62
Organization: Department of the Interior
Digital map of water-level changes in the High Plains aquifer in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming, predevelopment (about 1950) to 2013

The High Plains aquifer extends from south of 32 degrees to almost 44 degrees north latitude 
and from 96 degrees 30 minutes to 104 degrees west longitude. The aquifer underlies about 
175,000 square miles in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, 
South Dakota, Texas, and Wyoming. This dataset consists of a raster of water-level changes 
for the High Plains aquifer, predevelopment (about 1950) to 2013. This digital dataset was 
created using water-level measurements from 3,349 wells measured in both the predevelopment 
period (about 1950) and in 2013 and using other published information on water-level change 
in areas with few water-level measurements. The map was reviewed for consistency with the 
relevant data at a scale of 1:1,000,000.

Tags: aquifers, colorado, geoscientificinformation, great-plains, ground-water, groundwater, high-plains, high-plains-aquifer, inlandwaters, kansas, nebraska, new-mexico, ogallala-aquifer, oklahoma, south-dakota, texas, usgs-5d86cba9-65d1-4767-a6d1-87825fb8ad2d, water-level-change, wyoming
Organization: Department of the Interior
Annual California Sea Otter Census: 2019 Extra Limit Observations Shapefile

The GIS shapefile Extra limit counts of southern sea otters 2019 is a point layer representing the locations of sea otter sightings that fall outside the officially recognized range of the southern sea otter (Enhydra lutris nereis) in mainland California. These data were collected during the spring 2019 range-wide census. The USGS range-wide sea otter census has been undertaken each year since 1982, using consistent methodology involving both ground-based and aerial-based counts. The spring census provides the primary basis for gauging population trends by State and Federal management agencies. Sea otter distribution in California (the mainland range) is considered to comprise a band of potential habitat stretching along the coast of California, and bounded to the north and south by range limits defined by combining independent otters within a moving window of 10-kilometer stretches of coastline (as measured along the 10-meter bathymetric contour; 20 contiguous ATOS intervals each) and taking the northern and southern ATOS values, respectively, of the northernmost and southernmost stretches in which at least five otters were counted for at least 2 consecutive spring surveys during the last 3 years. However, a few individual sea otters (almost always males) can frequently be found outside this officially recognized range, and these extra-limital animals are also counted during the census.

Tags: aerial-counts, biogeography, biota, california, central-california-coastal, distribution, environment, mammals, ocean, range, sea-otter-census, sea-otters, shore-counts, southern-california-coastal, usgs-5d854224e4b0c4f70d086f1e
Organization: Department of the Interior
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 100-year storm in San Francisco County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. 
The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully.  Data are complete for the information presented.
      

Tags: beaches, central-california, central-california-coast, climate-change, climatologymeteorologyatmosphere, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-erosion, earth-sciences, effects-of-climate-change, erosion, extreme-weather, floods, hazards-planning, mathematical-modeling, ocean-waves, ocean-winds, oceans, pacific-coastal-and-marine-science-center, pcmsc, physical-habitats-and-geomorphology, san-francisco-county, sea-level-change, sea-level-rise, state-of-california, storm-surge, storms, u-s-geological-survey, usgs, usgs-5d84fe11e4b0c4f70d083e6b, water-depth, waves, wind
Organization: Department of the Interior
Process-guided deep learning water temperature predictions: 4 Training data

This dataset includes compiled water temperature data from a variety of sources, including the Water Quality Portal (Read et al. 2017), the North Temperate Lakes Long-TERM Ecological Research Program (https://lter.limnology.wisc.edu/), the Minnesota department of Natural Resources, and the Global Lake Ecological Observatory Network (gleon.org). This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD).

Tags: 007, 012, climate-change, deep-learning, environment, hybrid-modeling, inlandwaters, machine-learning, minnesota, mn, modeling, reservoirs, temperate-lakes, temperature, thermal-profiles, united-states, us, usgs-5d8a42e3e4b0c4f70d0ae5fd, water, wi, wisconsin
Organization: Department of the Interior
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 100-year storm in San Francisco County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. 
The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully.  Data are complete for the information presented.
      

Tags: beaches, central-california, central-california-coast, climate-change, climatologymeteorologyatmosphere, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-erosion, earth-sciences, effects-of-climate-change, erosion, extreme-weather, floods, hazards-planning, mathematical-modeling, ocean-waves, ocean-winds, oceans, pacific-coastal-and-marine-science-center, pcmsc, physical-habitats-and-geomorphology, san-francisco-county, sea-level-change, sea-level-rise, state-of-california, storm-surge, storms, u-s-geological-survey, usgs, usgs-5d84fbdbe4b0c4f70d083d8c, water-depth, waves, wind
Organization: Department of the Interior
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 20-year storm in San Francisco County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. 
The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully.  Data are complete for the information presented.
      

Tags: beaches, central-california, central-california-coast, climate-change, climatologymeteorologyatmosphere, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-erosion, earth-sciences, effects-of-climate-change, erosion, extreme-weather, floods, hazards-planning, mathematical-modeling, ocean-waves, ocean-winds, oceans, pacific-coastal-and-marine-science-center, pcmsc, physical-habitats-and-geomorphology, san-francisco-county, sea-level-change, sea-level-rise, state-of-california, storm-surge, storms, u-s-geological-survey, usgs, usgs-5d84fb83e4b0c4f70d083d80, water-depth, waves, wind
Organization: Department of the Interior