AndreaBozzo/ceres-open-data-index huggingface dataset:
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: 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, bayesian-network, cape-ann, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-erosion, coastal-habitat, coastal-hazards, coastal-processes, environment, erosion, geographic-information-systems, geomorphology, geoscientificinformation, geospatial-analysis, geospatial-datasets, gis, hazards, land-use-and-land-cover, ma, massachusetts, mean-high-water, mhw, north-america, parker-river, parker-river-national-wildlife-refuge, 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-5daa3741e4b09fd3b0c9ce43, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: 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-processes, geomorphology, geospatial-analysis, geospatial-datasets, ma, massachusetts, north-america, oceans, parker-river, parker-river-national-wildlife-refuge, st-petersburg-coastal-and-marine-science-center, study-areas, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3743e4b09fd3b0c9ce45, 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: 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, coastal-processes, environment, erosion, geographic-information-systems, geomorphology, geospatial-analysis, geospatial-datasets, gis, hazards, image-analysis, ma, massachusetts, mean-high-water, mhw, north-america, oceans, parker-river, parker-river-national-wildlife-refuge, scientific-interpretation, sea-level-change, st-petersburg-coastal-and-marine-science-center, study-areas, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3745e4b09fd3b0c9ce47, 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: 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, bayesian-network, biota, cape-ann, charadrius-melodus, cmgp, coastal-and-marine-geology-program, coastal-habitat, ecology, environment, foraging-ecology, geographic-information-systems, geography, geomorphology, geospatial-analysis, geospatial-datasets, gis, ma, massachusetts, mean-high-water, mhw, north-america, parker-river, parker-river-national-wildlife-refuge, piping-plovers, st-petersburg-coastal-and-marine-science-center, u-s-geological-survey, united-states, usa, usgs, usgs-5daa373ae4b09fd3b0c9ce3d, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
Airborne geophysical survey: North Arizona - New Mexico East, New Mexico Survey Part 2 of 2

Aeromagnetic data were collected along flight lines by instruments in an
aircraft that recorded magnetic-field values and locations.  This dataset
presents latitude, longitude, altitude, and magnetic-field values.

Tags: aeromagnetic-data, aeromagnetic-surveying, airborne-surveys, arizona, az, f08007-archuleta, f08021-conejos, f08067-la-plata, f35031-mckinley, f35039-rio-arriba, f35043-sandoval, f35045-san-juan, field-monitoring-stations, geophysical-surveys, geophysics, geospatial-datasets, magnetic, magnetic-field-earth, magnetic-surveys, new-mexico, nm, north-arizona-new-mexico-east, residual-magnetic-field, total-field, united-states, usgs-5df2fd35-e3a9-4564-b57b-4580e080ec11
Organization: Department of the Interior
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: 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-hazards, geographic-information-systems, geomorphology, geoscientificinformation, geospatial-analysis, geospatial-datasets, gis, mean-high-water, mhw, nc, north-america, north-carolina, north-core-islands, oceans, shackleford-banks, south-core-islands, st-petersburg-coastal-and-marine-science-center, transect-sampling, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3749e4b09fd3b0c9ce4b, 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 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, bayesian-network, biota, cape-lookout, cape-lookout-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, north-core-islands, piping-plovers, shackleford-banks, south-core-islands, st-petersburg-coastal-and-marine-science-center, u-s-geological-survey, united-states, usa, usgs, usgs-5daa374ce4b09fd3b0c9ce50, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
Western Pond Turtle (Emys [Actinemys] marmorata) observations at Point Reyes National Seashore and Golden Gate National Recreation Area

These data represent incidental observations of western pond turtles (Emys [Actinemys] marmorata) collected by the U.S. Geological Survey, Western Ecological Research Center, at Point Reyes National Seashore and Golden Gate National Recreation Area between 1993 and 2014. These data do not have associated survey effort, and are intended to represent incidental observations, rather than a random, systematic, or exhaustive survey for western pond turtles. The data include turtle location, observation date, and observer information.

Tags: biota, california-north, golden-gate-national-recreation-area, point-reyes-national-seashore, point-reyes-ne, reptiles, usgs-5db9efa4e4b06957974eb6b9, western-pond-turtle
Organization: Department of the Interior
DisOcean: Distance to the ocean: 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, environment, geographic-information-systems, geomorphology, geospatial-analysis, geospatial-datasets, gis, mean-high-water, mhw, nc, north-america, north-carolina, north-core-islands, oceans, shackleford-banks, south-core-islands, st-petersburg-coastal-and-marine-science-center, u-s-geological-survey, united-states, usa, usgs, usgs-5daa374ee4b09fd3b0c9ce52, 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: Monomoy Island, 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-cod, 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, monomoy-island, monomoy-national-wildlife-refuge, north-america, oceans, st-petersburg-coastal-and-marine-science-center, transect-sampling, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3729e4b09fd3b0c9ce27, 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: 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, bayesian-network, cape-lookout, cape-lookout-national-seashore, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-erosion, coastal-habitat, coastal-hazards, coastal-processes, environment, erosion, geographic-information-systems, geomorphology, geoscientificinformation, geospatial-analysis, geospatial-datasets, gis, hazards, land-use-and-land-cover, mean-high-water, mhw, nc, north-america, north-carolina, north-core-islands, probability, sea-level-change, sea-level-rise, shackleford-banks, shoreline-change, south-core-islands, st-petersburg-coastal-and-marine-science-center, transect-sampling, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3752e4b09fd3b0c9ce56, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
Trap records used to analyze trends in mammalian predator control trapping events intended to protect ground-nesting, endangered birds at Haleakalā National Park, Hawai'i (2000 - 2014)

Predation and habitat degradation by non-native species are principal terrestrial threats to the federally endangered Hawaiian Petrel (ʻuaʻu, Pterodroma sandwichensis) and Hawaiian Goose (nēnē, Branta sandvicensis) within Haleakalā National Park (HALE), Maui, Hawaiʻi. Since 1981, HALE has maintained a network of live-traps to control invasive mammalian predators and protect these endangered birds. To continue evaluations of trapping efficiency in HALE, we analyzed 2000 - 2014 trap events. Trap events were divided up into six event types classified into three event categories: no event, other event [bait lost, or trap triggered], or predator event [rat, cat, or mongoose caught]. Event type analysis was divided up for temporal and spatial analysis. Temporal variables included month, year, ‘Ua’u Season (off-season, pre-laying, incubation, or nestling), and Trapline (15 different traplines throughout HALE). Temporal variables were also compared to climate variables (Longman et al. 2015) and moon phase. Spatial variables included the number of ‘Ua’u burrows around the trap, the distance to roads, trails, fences and other structures, elevation, slope, and vegetation class and cover (derived from HALE unpublished data and LANDFIRE [Landfire, 2010]).
References:
Landfire, 2010, Existing Vegetation Type Layer, Existing Vegetation Cover Layer, Elevation Layer, Slope Layer, LANDFIRE 1.3.0, U.S. Department of the Interior, Geological Survey. Accessed 24 October 2016 at http://landfire.cr.usgs.gov/viewer/.
Longman, R. J., T. W. Giambelluca, M. A. Nullet and L. L. Loope. 2015. Climatology of Haleakalā.

Tags: biota, birds, capturing-animals, carnivores, endangered-species, hawaii, invasive-species, maui, omnivores, predator, predator-control, seabird, usgs-5dddbb28e4b04a30051ac2c8
Organization: Department of the Interior