AndreaBozzo/ceres-open-data-index huggingface dataset:
National Land Cover Database (NLCD) All Land Cover Science Products

As part of the next generation NLCD 2016 mapping process, the NLCD research team developed a suite of intermediate products that were used to generate the final NLCD Land Cover products. Some of those products also have value as independent products and are provided here. Please read the product descriptions to understand what the product represents.
Questions about the NLCD 2016 land cover product can be directed to the NLCD 2016 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.

Tags: biota, digital-spatial-data, gis, image-processing, imagerybasemapsearthcover, land-cover, land-use-land-cover-theme, n-l-c-d, national-geospatial-data-asset, ngda, nlcd, u-s, u-s-geological-survey-usgs, united-states, us, usgs-5da9ff5de4b09fd3b0c9cc05
Organization: Department of the Interior
Data Release for the 2007 Alaska Seismic Hazard Model

Gridded seismic hazard curve data, gridded ground motion data, and mapped gridded ground motion values are available for the 2007 Alaska Seismic Hazard Model. Time-independent probabilistic seismic hazard data and maps of Alaska and the Aleutians for peak ground acceleration (PGA) and 0.1, 0.2, 0.3, 0.5, 1.0 and 2.0 second spectral acceleration at probability levels of 2 percent in 50 years (annual probability of 0.000404), 5 percent in 50 years (annual probability of 0.001026), and 10 percent in 50 years (annual probability of 0.0021) assuming firm rock soil conditions at 760 m/s are available. Development of the 2007 Alaska Seismic Hazard Model is documented in the USGS Open-File Report 2007-1043 (https://pubs.usgs.gov/of/2007/1043/).  
This dataset is considered a legacy dataset. The original dataset was uploaded to the USGS website at the time of publication of the seismic hazard model (2007) but was later moved over the the USGS ScienceBase Catalog (2019). The original dataset was assumed to be complete and accurate, but may contain inconsistencies when compared to more recent, actively maintained datasets.

Tags: alaska, earthquake-hazards-program, ehp, geologic-hazards-science-center, ghsc, ground-motion, hazard-curve, hazard-map, national-seismic-hazard-model, national-seismic-hazard-model-project, nehrp-site-classes, nshm, nshmp, spectral-period, u-s-seismic-hazard-maps, usgs, usgs-5da9f42ee4b09fd3b0c9cbd4
Organization: Department of the Interior
Evapotranspiration within Blue Cypress Marsh, Vero Beach, Florida, 2015 to 2018

The dataset consists of a table in Excel format of daily evapotranspiration (ET) from 12/1/2015 to 6/13/2018 at ET station within the Blue Cypress Marsh Conservation Area near Vero Beach, Florida. Evapotranspiration was estimated using eddy-covariance methods.  Data processing followed methods outlined by Shoemaker and others (2011).  Ancillary data includes net radiation, latent heat, sensible heat, relative humidity, air temperature, water depth above land surface or depth to water below land surface (-), and Bowen's ratio.  The site location is 27°41'46",  -80°42'43".  Released data include mean daily latent heat (LE, in watts per square meter), available energy (Ae, in watts per square meter), and sensible heat (H, in watts per square meter), minimum and maximum daily relative humidity and air temperature (RH_max, RH_min in percent; AT_max, AT_min in degrees Celsius), water distance above (+) and below (-) land surface (WD, in meters), evapotranspiration (ET, in millimeters), and Bowen's ratio (BR, unit-less).

Tags: blue-cypress-marsh-conservation-area, eddy-covariance-method, evapotranspiration, florida, net-radiation, usa, usgs-5da9bbf3e4b09fd3b0c9ca87, weather, wetlands
Organization: Department of the Interior
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Cobb Island, VA, 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, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-habitat, coastal-processes, cobb-island, delmarva-peninsula, environment, erosion, geographic-information-systems, geomorphology, geospatial-analysis, geospatial-datasets, gis, hazards, image-analysis, mean-high-water, mhw, north-america, oceans, scientific-interpretation, sea-level-change, st-petersburg-coastal-and-marine-science-center, study-areas, u-s-geological-survey, united-states, usa, usgs, usgs-5daa37aee4b09fd3b0c9ceb7, va, virginia, virginia-coast-reserve, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fisherman Island, VA, 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, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-hazards, delmarva-peninsula, fisherman-island, fisherman-island-national-wildlife-refuge, geographic-information-systems, geomorphology, geoscientificinformation, geospatial-analysis, geospatial-datasets, gis, mean-high-water, mhw, north-america, oceans, st-petersburg-coastal-and-marine-science-center, transect-sampling, u-s-geological-survey, united-states, usa, usgs, usgs-5daa37b3e4b09fd3b0c9cebb, va, virginia, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Fisherman Island, VA, 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, delmarva-peninsula, ecology, environment, fisherman-island, fisherman-island-national-wildlife-refuge, foraging-ecology, geographic-information-systems, geography, geomorphology, geospatial-analysis, geospatial-datasets, gis, mean-high-water, mhw, north-america, piping-plovers, st-petersburg-coastal-and-marine-science-center, u-s-geological-survey, united-states, usa, usgs, usgs-5daa37b4e4b09fd3b0c9cebe, va, virginia, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
DisOcean: Distance to the ocean: Fisherman Island, VA, 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, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-habitat, delmarva-peninsula, environment, fisherman-island, fisherman-island-national-wildlife-refuge, geographic-information-systems, geomorphology, geospatial-analysis, geospatial-datasets, gis, mean-high-water, mhw, north-america, oceans, st-petersburg-coastal-and-marine-science-center, u-s-geological-survey, united-states, usa, usgs, usgs-5daa37b6e4b09fd3b0c9cec0, va, virginia, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
ElevMHW: Elevation adjusted to local mean high water: Fisherman Island, VA, 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, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-habitat, delmarva-peninsula, digital-elevation-models, elevation, fisherman-island, fisherman-island-national-wildlife-refuge, geographic-information-systems, geomorphology, geospatial-analysis, geospatial-datasets, gis, lidar, mean-high-water, mhw, north-america, oceans, st-petersburg-coastal-and-marine-science-center, topography, u-s-geological-survey, united-states, usa, usgs, usgs-5daa37b8e4b09fd3b0c9cec2, va, virginia, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Assateague Island, MD &amp; VA, 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: assateague-island, assateague-island-national-seashore, atlantic-ocean, barrier-island, chincoteague-national-wildlife-refuge, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-processes, delmarva-peninsula, geomorphology, geospatial-analysis, geospatial-datasets, maryland, md, north-america, oceans, st-petersburg-coastal-and-marine-science-center, study-areas, u-s-geological-survey, united-states, usa, usgs, usgs-5daa378ce4b09fd3b0c9ce91, va, virginia, 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: Fisherman Island, VA, 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, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-erosion, coastal-habitat, coastal-hazards, coastal-processes, delmarva-peninsula, environment, erosion, fisherman-island, fisherman-island-national-wildlife-refuge, geographic-information-systems, geomorphology, geoscientificinformation, geospatial-analysis, geospatial-datasets, gis, hazards, land-use-and-land-cover, mean-high-water, mhw, north-america, probability, 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-5daa37b9e4b09fd3b0c9cec4, va, virginia, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fisherman Island, VA, 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, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-processes, delmarva-peninsula, fisherman-island, fisherman-island-national-wildlife-refuge, geomorphology, geospatial-analysis, geospatial-datasets, north-america, oceans, st-petersburg-coastal-and-marine-science-center, study-areas, u-s-geological-survey, united-states, usa, usgs, usgs-5daa37bbe4b09fd3b0c9cec6, va, virginia, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Metompkin Island, VA, 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, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-hazards, delmarva-peninsula, geographic-information-systems, geomorphology, geoscientificinformation, geospatial-analysis, geospatial-datasets, gis, mean-high-water, metompkin-island, mhw, north-america, oceans, st-petersburg-coastal-and-marine-science-center, transect-sampling, u-s-geological-survey, united-states, usa, usgs, usgs-5daa37c2e4b09fd3b0c9cecc, va, virginia, virginia-coast-reserve, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior