Skip to main content
Advanced Search

Filters: Types: Downloadable (X) > partyWithName: U.S. Geological Survey - ScienceBase (X) > partyWithName: Woods Hole Coastal and Marine Science Center (X) > Types: OGC WFS Layer (X)

330 results (14ms)   

View Results as: JSON ATOM CSV
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, OGC WFS Layer, OGC WMS Layer, Raster, Shapefile; Tags: Atlantic Ocean, Barrier Island, Bayesian Network, CMHRP, Coastal Erosion, All tags...
thumbnail
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This data release includes one new mean high water (MHW) shoreline extracted from lidar data collected in 2017 for the entire coastal region of North Carolina which is divided into four subregions: northern North Carolina...
thumbnail
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion.These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This data release includes one new mean high water (MHW) shoreline extracted from lidar data collected in 2017 for the entire coastal region of North Carolina which is divided into four subregions: northern North Carolina...
thumbnail
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This data release includes one new mean high water (MHW) shoreline extracted from lidar data collected in 2017 for the entire coastal region of North Carolina which is divided into four subregions: northern North Carolina...
thumbnail
In 2012, Hurricane Sandy struck the Northeastern US causing devastation among coastal ecosystems. Post-hurricane marsh restoration efforts have included sediment deposition, planting of vegetation, and restoring tidal hydrology. The work presented here is part of a larger project funded by the National Fish and Wildlife Foundation (NFWF) to monitor the post-restoration ecological resilience of coastal ecosystems in the wake of Hurricane Sandy. The U.S. Geological Survey Woods Hole Coastal and Marine Science Center made in-situ observations during 2018-2019 and 2022-2023 at two sites: Thompsons Beach, NJ and Stone Harbor, NJ. Marsh creek hydrodynamics and water quality including currents, waves, water levels, water...
thumbnail
The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the USGS Digital Shoreline Analysis System (DSAS), version 5.1 software to calculate rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers understand which areas of the coast are vulnerable to change. This data release, and other associated...
thumbnail
Note: The 2021 data release "Geospatial characterization of salt marshes for Massachusetts" is a more recent and comprehensive MA salt marsh dataset. (https://doi.org/10.5066/P97E086F) The salt marsh complex of Plum Island Estuary and Parker River (PIEPR) was delineated to smaller, conceptual marsh units by geoprocessing of surface elevation data. Flow accumulation based on the relative elevation of each location was used to determine the ridge lines that separate each marsh unit while the surface slope was used to automatically assign each unit a drainage point, where water is expected to drain through. Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. Geological Survey has been...
thumbnail
The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-2009 color aerial orthoimagery and 2007 topographic lidar datasets obtained...
thumbnail
The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photograph or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the Digital Shoreline Analysis System software (v5.1) to compute their rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers understand which areas of the coast are vulnerable to change. This data release, and other associated products, represent...
thumbnail
The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using 2008-2009 color aerial orthoimagery and 2007 topographic lidar datasets obtained from NOAA's Ocean Service, Coastal...
thumbnail
The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-2009 color aerial orthoimagery and 2007 topographic lidar datasets obtained...
thumbnail
The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the Digital Shoreline Analysis System software to compute their rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers understand which areas of the coast are vulnerable to change. This data release, and other associated products, represent...
thumbnail
These data are a part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. The work was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate species that inhabit the region. The Sanctuary's research vessel, R/V Auk, visited a total of 233 locations on Stellwagen Bank during six separate surveys from May 2016 to April 2019. During these surveys a customized...
thumbnail
Note: The 2022 data release "Geospatial Characterization of Salt Marshes in Chesapeake Bay" incorporates the Blackwater region salt marsh dataset. (https://doi.org/10.5066/P997EJYB) This data release contains coastal wetland synthesis products for the geographic region of Blackwater, Chesapeake Bay, Maryland. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and others, are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands with the intent...
thumbnail
During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion along the southeast US coastline and implications for vulnerability to future storms. Shoreline positions were compiled prior to and following Hurricane Irma along the sandy shorelines of the Gulf of Mexico and Atlantic...
thumbnail
In spring and summer 2017, the U.S. Geological Survey’s Gas Hydrates Project conducted two cruises aboard the research vessel Hugh R. Sharp to explore the geology, chemistry, ecology, physics, and oceanography of sea-floor methane seeps and water column gas plumes on the northern U.S. Atlantic margin between the Baltimore and Keller Canyons. Split-beam and multibeam echo sounders and a chirp subbottom profiler were deployed during the cruises to map water column backscatter, sea-floor bathymetry and backscatter, and subsurface stratigraphy associated with known and undiscovered sea-floor methane seeps. The first cruise, known as the Interagency Mission for Methane Research on Seafloor Seeps and designated as field...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: 7160, Accomac Canyon, Atlantic Margin, Atlantic Ocean, CMHRP, All tags...


map background search result map search result map Conceptual marsh units for Plum Island Estuary and Parker River salt marsh complex, Massachusetts DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Edwin B. Forsythe NWR, NJ, 2014 Development: Development delineation: Coast Guard Beach, MA, 2013-2014 Development: Development delineation: Cape Hatteras, NC, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Parramore Island, VA, 2014 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 Multibeam echo sounder - navigation tracklines for Reson 7160 data collected during USGS field activities 2017-001-FA and 2017-002-FA Conceptual marsh units of Blackwater salt marsh complex, Chesapeake Bay, Maryland Historical Shorelines for Puerto Rico from 1901 to 1987 Baseline for the coastal region around Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1 Long-term and short-term shoreline change rates for the region of Martha's Vineyard, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 Baseline for the coastal region north of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1 2016 USACE Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis Shoreline change rates for the coast of Puerto Rico's main island calculated using the Digital Shoreline Analysis System version 5.1 (ver. 2.0, March 2023) Intersects for the Florida west coast (FLwc) coastal region generated to calculate short-term shoreline change rates using the Digital Shoreline Analysis System version 5 Station and data summary for data collected by the U.S. Geological Survey on Stellwagen Bank during six surveys aboard the R/V Auk, May 2016 to April 2019 Grain-size analysis data from sediment samples in support of oceanographic and water-quality measurements at Thompsons Beach and Stone Harbor, New Jersey, collected in September 2018 and March 2022 Long and short-term shoreline change rate transects for the western North Carolina coastal region (NCwest), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 Long and short-term shoreline change rate transects for the central North Carolina coastal region (NCcentral), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 Baseline for the North Carolina coastal region from the Virginia border to Cape Hatteras (NCnorth) Development: Development delineation: Coast Guard Beach, MA, 2013-2014 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 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Parramore Island, VA, 2014 Baseline for the coastal region around Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1 Conceptual marsh units for Plum Island Estuary and Parker River salt marsh complex, Massachusetts Grain-size analysis data from sediment samples in support of oceanographic and water-quality measurements at Thompsons Beach and Stone Harbor, New Jersey, collected in September 2018 and March 2022 Long and short-term shoreline change rate transects for the western North Carolina coastal region (NCwest), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Edwin B. Forsythe NWR, NJ, 2014 Long-term and short-term shoreline change rates for the region of Martha's Vineyard, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 Station and data summary for data collected by the U.S. Geological Survey on Stellwagen Bank during six surveys aboard the R/V Auk, May 2016 to April 2019 Conceptual marsh units of Blackwater salt marsh complex, Chesapeake Bay, Maryland Baseline for the coastal region north of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1 2016 USACE Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis Development: Development delineation: Cape Hatteras, NC, 2014 Baseline for the North Carolina coastal region from the Virginia border to Cape Hatteras (NCnorth) Long and short-term shoreline change rate transects for the central North Carolina coastal region (NCcentral), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 Shoreline change rates for the coast of Puerto Rico's main island calculated using the Digital Shoreline Analysis System version 5.1 (ver. 2.0, March 2023) Historical Shorelines for Puerto Rico from 1901 to 1987 Multibeam echo sounder - navigation tracklines for Reson 7160 data collected during USGS field activities 2017-001-FA and 2017-002-FA Intersects for the Florida west coast (FLwc) coastal region generated to calculate short-term shoreline change rates using the Digital Shoreline Analysis System version 5