AndreaBozzo/ceres-open-data-index huggingface dataset:
Data tables and raster for iron fouling associated with drainage from roadway sites constructed with rock-fill in New Hampshire, USA

This data release contains files that are associated with the publication "Understanding and predicting iron fouling associated with drainage from roadway sites constructed with rock-fill in New Hampshire, USA".  Each zipped file contains a data table or raster file and an associated metadata file.  IronFoulingCutFillData.zip contains a .csv file and .xml metadata file related to the roadcut and rock-fill locations used to develop a statistical model to predict the probability of iron fouling at roadway sites constructed with rock-fill in New Hampshire.  Water_Quality_Measurements.zip contains a .csv file and .xml metadata file for water quality field measurements made at drainage areas from a subset of the rock-fill locations in the IronFoulingCutFillData files.  The NHIronFoulingProb.zip file contains a geotiff raster of the predicted probability of iron fouling occurring at any location within New Hampshire where rock-fill from that location is used and contacts drainage.  This is the output from the statistical model prediction.  NHIronFoulingProb.zip also contains an .xml metadata file.

Tags: imagerybasemapsearthcover, inlandwaters, transportation, usgs-5db9cb49e4b06957974eb5f9
Organization: Department of the Interior
ElevMHW: Elevation adjusted to local mean high water: Cape Hatteras, NC, 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, cape-hatteras, cape-hatteras-national-seashore, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-habitat, digital-elevation-models, elevation, geographic-information-systems, geomorphology, geospatial-analysis, geospatial-datasets, gis, lidar, mean-high-water, mhw, nc, north-america, north-carolina, oceans, ocracoke-island, st-petersburg-coastal-and-marine-science-center, topography, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3763e4b09fd3b0c9ce67, 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: Rhode Island National Wildlife Refuge, RI, 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, geographic-information-systems, geomorphology, geoscientificinformation, geospatial-analysis, geospatial-datasets, gis, mean-high-water, mhw, north-america, oceans, rhode-island, rhode-island-national-wildlife-refuge-complex, ri, st-petersburg-coastal-and-marine-science-center, transect-sampling, trustom-pond, u-s-geological-survey, united-states, usa, usgs, usgs-5daa376de4b09fd3b0c9ce71, 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: Rhode Island National Wildlife Refuge, RI, 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, geographic-information-systems, geography, geomorphology, geospatial-analysis, geospatial-datasets, gis, mean-high-water, mhw, north-america, piping-plovers, rhode-island, rhode-island-national-wildlife-refuge-complex, ri, st-petersburg-coastal-and-marine-science-center, trustom-pond, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3770e4b09fd3b0c9ce76, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
DisOcean: Distance to the ocean: Rhode Island National Wildlife Refuge, RI, 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, environment, geographic-information-systems, geomorphology, geospatial-analysis, geospatial-datasets, gis, mean-high-water, mhw, north-america, oceans, rhode-island, rhode-island-national-wildlife-refuge-complex, ri, st-petersburg-coastal-and-marine-science-center, trustom-pond, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3772e4b09fd3b0c9ce78, 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: Parker River, MA, 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, cape-ann, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-hazards, geographic-information-systems, geomorphology, geoscientificinformation, geospatial-analysis, geospatial-datasets, gis, ma, massachusetts, mean-high-water, mhw, north-america, oceans, parker-river, parker-river-national-wildlife-refuge, st-petersburg-coastal-and-marine-science-center, transect-sampling, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3737e4b09fd3b0c9ce38, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
ElevMHW: Elevation adjusted to local mean high water: Rhode Island National Wildlife Refuge, RI, 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, digital-elevation-models, elevation, geographic-information-systems, geomorphology, geospatial-analysis, geospatial-datasets, gis, lidar, mean-high-water, mhw, north-america, oceans, rhode-island, rhode-island-national-wildlife-refuge-complex, ri, st-petersburg-coastal-and-marine-science-center, topography, trustom-pond, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3774e4b09fd3b0c9ce7a, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Rhode Island National Wildlife Refuge, RI, 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, geomorphology, geospatial-analysis, geospatial-datasets, north-america, oceans, rhode-island, rhode-island-national-wildlife-refuge-complex, ri, st-petersburg-coastal-and-marine-science-center, study-areas, trustom-pond, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3779e4b09fd3b0c9ce7e, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Rhode Island National Wildlife Refuge, RI, 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, environment, erosion, geographic-information-systems, geomorphology, geospatial-analysis, geospatial-datasets, gis, hazards, image-analysis, mean-high-water, mhw, north-america, oceans, rhode-island, rhode-island-national-wildlife-refuge-complex, ri, scientific-interpretation, sea-level-change, st-petersburg-coastal-and-marine-science-center, study-areas, trustom-pond, u-s-geological-survey, united-states, usa, usgs, usgs-5daa377ce4b09fd3b0c9ce80, 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: 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-hazards, delmarva-peninsula, geographic-information-systems, geomorphology, geoscientificinformation, geospatial-analysis, geospatial-datasets, gis, maryland, md, 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-5daa377fe4b09fd3b0c9ce84, va, virginia, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
Development: Development delineation: 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-armoring, coastal-habitat, coastal-hazards, delmarva-peninsula, environment, geographic-information-systems, geospatial-datasets, gis, human-development, land-use-and-land-cover, maryland, md, north-america, st-petersburg-coastal-and-marine-science-center, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3781e4b09fd3b0c9ce87, va, virginia, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior