AndreaBozzo/ceres-open-data-index huggingface dataset:
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cape Lookout, 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-lookout, cape-lookout-national-seashore, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-processes, geomorphology, geospatial-analysis, geospatial-datasets, nc, north-america, north-carolina, north-core-islands, oceans, shackleford-banks, south-core-islands, st-petersburg-coastal-and-marine-science-center, study-areas, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3754e4b09fd3b0c9ce58, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
DisOcean: Distance to the ocean: 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-habitat, environment, geographic-information-systems, geomorphology, 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, u-s-geological-survey, united-states, usa, usgs, usgs-5daa373be4b09fd3b0c9ce3f, 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: Cape Lookout, 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-lookout, cape-lookout-national-seashore, 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, nc, north-america, north-carolina, north-core-islands, oceans, scientific-interpretation, sea-level-change, shackleford-banks, south-core-islands, st-petersburg-coastal-and-marine-science-center, study-areas, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3756e4b09fd3b0c9ce5a, 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: 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-hazards, geographic-information-systems, geomorphology, geoscientificinformation, geospatial-analysis, geospatial-datasets, gis, mean-high-water, mhw, nc, north-america, north-carolina, oceans, ocracoke-island, st-petersburg-coastal-and-marine-science-center, transect-sampling, u-s-geological-survey, united-states, usa, usgs, usgs-5daa375be4b09fd3b0c9ce5e, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
Development: Development delineation: 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-armoring, coastal-habitat, coastal-hazards, environment, geographic-information-systems, geospatial-datasets, gis, human-development, land-use-and-land-cover, nc, north-america, north-carolina, ocracoke-island, st-petersburg-coastal-and-marine-science-center, u-s-geological-survey, united-states, usa, usgs, usgs-5daa375ce4b09fd3b0c9ce61, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
Seismic Reflection, EdgeTech SB-424 Chirp shot points collected in the vicinity of Buffalo Reef, Michigan, within Lake Superior during USGS field activity 2018-043-FA, (CSV text and Esri point shapefile, GCS WGS 84)

In September 2018, the USGS Woods Hole Coastal and Marine Science Center (WHCMSC), in collaboration with the US Army Corps of Engineers (USACE), conducted high-resolution geophysical mapping and sediment sampling to determine the distribution of historical mine tailings on the floor of Lake Superior.  Large amounts of waste material from copper mining, locally known as “stamp sands”, were dumped into the lake in the early 20th century, with wide-reaching consequences that have continued into the present day.  Mapping was focused offshore of the town of Gay on the Keweenaw Peninsula of Michigan, where ongoing erosion and re-deposition of the stamp sands has buried miles of native, white-sand beaches and is steadily encroaching south onto Buffalo Reef, a large area of cobble/boulder substrate that supports productive fisheries in the lake.
The objectives of this cooperative mapping project are to develop a framework for scientific research and provide baseline information required for management of resources within the coastal zone of northern Michigan.  High resolution bathymetry and backscatter data reveal the irregular topography of the shallow, cobble-covered Buffalo Reef, and the relatively smooth, finer-grained sediment that covers adjacent, deeper parts of the lake floor.  Previous research used numerous sediment samples to determine the general distribution of mine tailings on the lake floor in this area, but little information existed on the extent and thickness of the surficial deposits.  The main priority of this project is to image the near-surface stratigraphy, specifically the surficial sand and mud that threaten to cover the reef, with seismic-reflection profiling systems.  In addition to continuous coverage of bathymetric and backscatter data, this report includes a dense grid of closely spaced seismic profiles and an isopach map of sediment thickness, which will guide efforts to mitigate the impacts on Buffalo Reef from contamination by the shifting stamp sands.

Tags: buffalo-reef, chirp, cmhrp, coastal-and-marine-hazards-and-resources-program, department-of-the-interior, doi, edgetech, field-activity-number-2018-043-fa, geology, geophysics, geoscientificinformation, geospatial-datasets, houghton-county, inlandwaters, keweenaw-county, lacustrine-geology, lake-floor, lake-superior, lakefloor, location, navigational-data, r-v-rafael, sb-424, seismic-navigation, seismic-profile, seismic-reflection, seismic-reflection-methods, shapefile, shot-point-navigation, state-of-michigan, traverse-bay, u-s-geological-survey, united-states-of-america, usgs, usgs-5ddeb161e4b04a30051b9e15, whcmsc, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
ElevMHW: Elevation adjusted to local mean high water: 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-habitat, delmarva-peninsula, digital-elevation-models, elevation, geographic-information-systems, geomorphology, geospatial-analysis, geospatial-datasets, gis, lidar, maryland, md, mean-high-water, mhw, north-america, oceans, st-petersburg-coastal-and-marine-science-center, topography, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3786e4b09fd3b0c9ce8d, 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: 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, bayesian-network, biota, cape-hatteras, cape-hatteras-national-seashore, 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, nc, north-america, north-carolina, ocracoke-island, piping-plovers, st-petersburg-coastal-and-marine-science-center, u-s-geological-survey, united-states, usa, usgs, usgs-5daa375fe4b09fd3b0c9ce63, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
DisOcean: Distance to the ocean: 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, environment, geographic-information-systems, geomorphology, geospatial-analysis, geospatial-datasets, gis, mean-high-water, mhw, nc, north-america, north-carolina, oceans, ocracoke-island, st-petersburg-coastal-and-marine-science-center, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3761e4b09fd3b0c9ce65, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
Data Release for the 2016 One-Year Seismic Hazard Forecast for the Central and Eastern United States from Induced and Natural Earthquakes

Seismicity catalogs, gridded seismic hazard curve data, gridded ground motion data, and mapped gridded ground motion values are available for the 2016 One-Year Seismic Hazard Forecast for the Central and Eastern U.S. from Induced and Natural Earthquakes. Probabilistic seismic hazard data and maps of the conterminous U.S. for peak ground acceleration (PGA) and 0.2 and 1.0 second spectral acceleration at a probability level of 1 percent in 1 year (annual probability of 0.0101), assuming firm rock soil conditions at 760 m/s, are available. Hazard was calculated on a 0.05 degree by 0.05 degree grid, defined by a bounding box encompassing the central and eastern U.S. (-115 to -65 degrees longitude west, 24.6 to 50 degrees latitude north). Note, hazard in the western U.S. (-125 to -115 longitude west) is taken from gridded hazard curve results of the 2014 National Seismic Hazard Model for the Conterminous U.S. (https://doi.org/10.5066/P9P77LGZ). Development of the 2016 One-Year Seismic Hazard Forecast for the Central and Eastern U.S. from Induced and Natural Earthquakes is documented in the USGS Open-File Report 2016-1035 (https://doi.org/10.3133/ofr20161035).  
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 (2016) 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: central-and-eastern-u-s, earthquake-hazards-program, ehp, geologic-hazards-science-center, ghsc, ground-motion, hazard-curve, hazard-map, induced-seismicity, national-seismic-hazard-model, national-seismic-hazard-model-project, nehrp-site-classes, nshm, nshmp, spectral-period, u-s-seismic-hazard-maps, usgs, usgs-5db9e72ae4b06957974eb692
Organization: Department of the Interior
Development: Development delineation: 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-armoring, coastal-habitat, coastal-hazards, environment, geographic-information-systems, geospatial-datasets, gis, human-development, land-use-and-land-cover, ma, massachusetts, north-america, parker-river, parker-river-national-wildlife-refuge, st-petersburg-coastal-and-marine-science-center, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3738e4b09fd3b0c9ce3b, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior