AndreaBozzo/ceres-open-data-index huggingface dataset:
Aeromagnetic data, grid data, and magnetization boundaries of a survey flown in the Burney region, northeastern California

This data release contains data from flightlines collected during an aeromagnetic survey of the Burney region of northeastern California.  These data were gridded and magnetization boundaries were calculated using the maximum horizontal gradient method on the gridded data.

Tags: burney, fall-river-mills, geoscientificinformation, lake-almanor, magnetic-anomaly, magnetic-field-earth, magnetic-horizontal-gradient, magnetometer-measurement, susanville, usgs-5dadf0aee4b09fd3b0c9d8f3
Organization: Department of the Interior
National Land Cover Database (NLCD) 2016 Land Cover Science Product

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four
National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011.
These products provide spatially explicit and reliable information on the Nation’s land cover and land cover
change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s
land resources, the USGS has designed a new generation of NLCD products named NLCD 2016. The NLCD 2016
design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land
cover and land cover change database from 2001 to 2016 at 2–3-year intervals. Comprehensive research was
conducted and resulted in developed strategies for NLCD 2016: a streamlined process for assembling and preprocessing
Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development
and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land
cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for
generating land cover and change products; a continuous fields biophysical parameters modeling method; and
an automated scripted operational system for the NLCD 2016 production. The performance of the developed
strategies and methods were tested in twenty World Reference System-2 path/row throughout the conterminous
U.S. An overall agreement ranging from 71% to 97% between land cover classification and reference data was
achieved for all tested area and all years. Results from this study confirm the robustness of this comprehensive
and highly automated procedure for NLCD 2016 operational mapping.
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-5dadee41e4b09fd3b0c9d8ed
Organization: Department of the Interior
Optimum electrofishing waveforms and parameters to induce immobilization of juvenile Grass Carp: Data

Grass Carp (Ctenopharyngodon idella) are a non-native species to North America that were first introduced for vegetation control in the 1960s.  However, wild-reproducing Grass Carp can negatively impact aquatic habitats and aquatic communities by consuming substantial amounts of aquatic vegetation and increasing turbidity.  Numerous fisheries techniques have been used in an attempt to control or eradicate Grass Carp, including electrofishing.  However, electrofishing efficiency for Grass Carp has been variable, and optimum electrofishing waveforms and parameters for inducing a capture-prone response have not been determined.  The objective of this study was to determine the optimum electrofishing waveforms and parameters to induce a capture-prone response at various water temperatures and conductivities in juvenile Grass Carp in a controlled, laboratory setting.  Results suggested that rectangular pulse waveforms with 60 to 100 Hz frequencies were most effective for immobilization of juvenile Grass Carp.  All duty cycles tested (20 – 48%) at these frequencies were effective; although at 60 Hz and 80 Hz frequencies, 24% and 30% duty cycles, respectively, may be more effective.  Water temperature was positively related to voltage gradient immobilization thresholds whereas ambient water conductivity and fish size were inversely related to voltage gradient immobilization thresholds.  This study provides important information to those seeking to control, eradicate, or detect Grass Carp using electrofishing and provides a framework for future studies focusing on adult Grass Carp.
The dataset includes: Electrofishing exposure trial data from each trial type

Tags: biota, control, electrofishing, grass-carp, invasive-species, usgs-5dab4ce3e4b09fd3b0c9d257
Organization: Department of the Interior
Upper Mississippi River-Pool 4 Time Lag Investigation of Physical Conditions and Submersed Macrophyte Prevalence: Data

The Long-Term Resource Monitoring element (LTRM) of the Upper Mississippi River Restoration program (UMRR) has conducted aquatic vegetation and water quality surveys in several navigation pools since the mid 1990’s. Over a 20-year period (1998-2017), the off-channel (i.e. backwater) areas in upper Pool 4 remained chronically turbid and supported a limited submersed macrophyte community with high between-year variability in the proportion of sites where submersed plants were observed. Water surface elevation and discharge rates also fluctuated substantially within- and between-years in the upper pool. Pearson correlation analysis indicated that between-year change in the proportion of sites where submersed macrophytes are observed is correlated to the number of high summer discharge days 1 year prior (r = -0.48); the number of low summer discharge days during the current year (r =0.46) and one year prior (r = 0.62); minimum discharge (r = 0.52) and the duration that depth at vegetation sample sites was within the estimated photic zone (i.e. a metric that reflects a combination of water clarity and water surface elevation) during the current summer (r = 0.63). Conditions more than one year prior and during the other seasons (winter, spring, fall) exhibited little correlation to subsequent fluctuations in the prevalence of submersed macrophytes.

Tags: backwater, biota, discharge, macrophyte, mississippi-river, photic-zone, pool-4, submersed-aquatic-vegetation, upper-mississippi-river, upper-pool-4, usgs-5dab3da5e4b09fd3b0c9d21f
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: Coast Guard Beach, MA, 2013-2014

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-cod, cape-cod-national-seashore, cmhrp, coast-guard-beach, 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, 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-5daa3721e4b09fd3b0c9ce1f, 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: Wreck 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, 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-5daa3816e4b09fd3b0c9cf2e, va, virginia, woods-hole-coastal-and-marine-science-center, wreck-island, wreck-island-natural-area-preserve
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: Parramore 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, foraging-ecology, geographic-information-systems, geography, geomorphology, geospatial-analysis, geospatial-datasets, gis, mean-high-water, mhw, north-america, parramore-island, piping-plovers, st-petersburg-coastal-and-marine-science-center, u-s-geological-survey, united-states, usa, usgs, usgs-5daa37e0e4b09fd3b0c9cef1, va, virginia, virginia-coast-reserve, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Wreck 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, 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-5daa3814e4b09fd3b0c9cf2c, va, virginia, woods-hole-coastal-and-marine-science-center, wreck-island, wreck-island-natural-area-preserve
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: Wreck 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, 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-5daa3812e4b09fd3b0c9cf2a, va, virginia, woods-hole-coastal-and-marine-science-center, wreck-island, wreck-island-natural-area-preserve
Organization: Department of the Interior
DisOcean: Distance to the ocean: Wreck 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, 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-5daa380ee4b09fd3b0c9cf26, va, virginia, woods-hole-coastal-and-marine-science-center, wreck-island, wreck-island-natural-area-preserve
Organization: Department of the Interior
ElevMHW: Elevation adjusted to local mean high water: Coast Guard Beach, 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, cape-cod-national-seashore, cmhrp, coast-guard-beach, coastal-and-marine-hazards-and-resources-program, coastal-habitat, digital-elevation-models, elevation, geographic-information-systems, geomorphology, geospatial-analysis, geospatial-datasets, gis, lidar, ma, massachusetts, mean-high-water, mhw, north-america, oceans, st-petersburg-coastal-and-marine-science-center, topography, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3720e4b09fd3b0c9ce1d, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior