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The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time 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 an expansion...
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The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time 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 an expansion...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for developing approaches that balance the needs of humans and native species. Given the magnitude of the threat posed by sea-level rise, and the urgency to better understand it, there is an increasing need to forecast sea-level rise effects on barrier islands. To address this problem, scientists in the U.S. Geological Survey (USGS) Coastal and Marine Geology program are developing Bayesian networks as a tool to evaluate and to forecast the effects of sea-level rise on shoreline change, barrier island geomorphology, and habitat availability for species such as the piping plover (Charadrius melodus)...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Assateague Island, Assateague Island, Assateague Island National Seashore, Assateague Island National Seashore, Atlantic Ocean, All tags...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for developing approaches that balance the needs of humans and native species. Given the magnitude of the threat posed by sea-level rise, and the urgency to better understand it, there is an increasing need to forecast sea-level rise effects on barrier islands. To address this problem, scientists in the U.S. Geological Survey (USGS) Coastal and Marine Geology program are developing Bayesian networks as a tool to evaluate and to forecast the effects of sea-level rise on shoreline change, barrier island geomorphology, and habitat availability for species such as the piping plover (Charadrius melodus)...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Assateague Island, Assateague Island, Assateague Island National Seashore, Assateague Island National Seashore, Atlantic Ocean, All tags...
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This part of DS 781 presents data for the transgressive contours of the Point Sur to Point Arguello, California, region. The vector data file is included in the “TransgressiveContours_PointSurToPointArguello.zip,” which is accessible from https://doi.org/10.5066/P97CZ0T7. As part of the USGS's California State Waters Mapping Project, a 50-m grid of sediment thickness for the seafloor within the 3-nautical mile limit between Point Sur and Point Arguello was generated from seismic-reflection data collected between 2008 and 2014, and supplemented with geologic structure (fault and fold) information following the methodology of Wong (2012). Water depths determined from bathymetry data were added to the sediment thickness...
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This data release contains coastal wetland synthesis products for the Atlantic-facing Eastern Shore of Virginia (the data release for the Chesapeake Bay-facing portion of the Eastern Shore of Virginia is found here: https://doi.org/10.5066/P997EJYB). Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and tidal range 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 of providing federal, state, and local managers with...
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In summer 2018, the U.S. Geological Survey partnered with the U.S Department of Energy and the Bureau of Ocean Energy Management to conduct the Mid-Atlantic Resources Imaging Experiment (MATRIX) as part of the U.S. Geological Survey Gas Hydrates Project. The field program objectives were to acquire high-resolution 2-dimensional multichannel seismic-reflection and split-beam echosounder data along the U.S Atlantic margin between North Carolina and New Jersey to determine the distribution of methane gas hydrates in below-sea floor sediments and investigate potential connections between gas hydrate dynamics and sea floor methane seepage. MATRIX field work was carried out between August 8 and August 28, 2018 on the...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Atlantic Ocean, BOEM, Bureau of Ocean Energy Management, CMHRP, Cape Hatteras, All tags...
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In summer 2018, the U.S. Geological Survey partnered with the U.S Department of Energy and the Bureau of Ocean Energy Management to conduct the Mid-Atlantic Resources Imaging Experiment (MATRIX) as part of the U.S. Geological Survey Gas Hydrates Project. The field program objectives were to acquire high-resolution 2-dimensional multichannel seismic-reflection and split-beam echosounder data along the U.S Atlantic margin between North Carolina and New Jersey to determine the distribution of methane gas hydrates in below-sea floor sediments and investigate potential connections between gas hydrate dynamics and sea floor methane seepage. MATRIX field work was carried out between August 8 and August 28, 2018 on the...
Categories: Data, Data Release - In Progress; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Atlantic Ocean, BOEM, Bureau of Ocean Energy Management, CMHRP, Cape Hatteras, All tags...
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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...
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In coastal areas of the United States, where water and land interface in complex and dynamic ways, it is common to find concentrated residential and commercial development. These coastal areas often contain various landholdings managed by Federal, State, and local municipal authorities for public recreation and conservation. These areas are frequently subjected to a range of natural hazards, which include flooding and coastal erosion. In response, the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline data to calculate rates of shoreline change along the conterminous coast of the United States, and select coastlines of Alaska and Hawaii, as part of the Coastal Change Hazards priority...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Baseline, CMGP, California, CenCal, Central California, All tags...
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In coastal areas of the United States, where water and land interface in complex and dynamic ways, it is common to find concentrated residential and commercial development. These coastal areas often contain various landholdings managed by Federal, State, and local municipal authorities for public recreation and conservation. These areas are frequently subjected to a range of natural hazards, which include flooding and coastal erosion. In response, the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline data to calculate rates of shoreline change along the conterminous coast of the United States, and select coastlines of Alaska and Hawaii, as part of the Coastal Change Hazards priority...
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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...
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The U.S. Geological Survey, in cooperation with the Massachusetts Office of Coastal Zone Management compiled Massachusetts vector shorelines into an updated dataset for the Office’s Shoreline Change Project. The Shoreline Change Project started in 1989 to identify erosion-prone areas of the Massachusetts coast by compiling a database of historical shoreline positions. Trends of shoreline position over long- and short-term timescales provide information to landowners, managers, and potential buyers about possible future changes to costal resources and infrastructure. This updated dataset strengthens the understanding of shoreline position change in Massachusetts. It includes U.S. Geological Survey vector shorelines...
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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...
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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...
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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...
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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...
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This part of DS 781 presents data for the faults of the Point Sur to Point Arguello, California, region. The vector data file is included in the “Faults_PointSurToPointArguello.zip,” which is accessible from https://doi.org/10.5066/P97CZ0T7. Faults in the Point Sur to Point Arguello region are identified on seismic-reflection data based on abrupt truncation or warping of reflections and (or) juxtaposition of reflection panels with different seismic parameters such as reflection presence, amplitude, frequency, geometry, continuity, and vertical sequence. Faults were primarily mapped by interpretation of seismic reflection profile data collected by the U.S. Geological Survey between 2008 and 2014.


map background search result map search result map Vegetation habitat units derived from 2009 aerial imagery and field data for the Elwha River estuary, Washington Vegetation habitat units derived from 2014 aerial imagery and field data for the Elwha River estuary, Washington Faults—Point Sur to Point Arguello, California Transgressive Contours—Point Sur to Point Arguello, California Multichannel Seismic-Reflection and Navigation Data Collected Using Sercel GI Guns and Geometrics GeoEel Digital Streamers During the Mid-Atlantic Resource Imaging Experiment (MATRIX), USGS Field Activity 2018-002-FA Split-beam Echo Sounder and Navigation Data Collected Using a Simrad EK80 Wide Band Tranceiver and ES38-10 Transducer During the Mid-Atlantic Resource Imaging Experiment (MATRIX), USGS Field Activity 2018-002-FA. 2018 mean high water shoreline of the coast of MA used in shoreline change analysis Long-term and short-term shoreline change rates for Outer Cape Cod, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 2010 Shorelines for Vieques, Culebra, and Main Island of Puerto Rico 1970s Shorelines for Vieques and Culebra, Puerto Rico Long-term shoreline change rates for the Florida east coast (FLec) coastal region using the Digital Shoreline Analysis System version 5 Short-term shoreline change rates for the Florida east coast (FLec) coastal region using the Digital Shoreline Analysis System version 5 Long-term shoreline change rates for the Florida panhandle (FLph) coastal region using the Digital Shoreline Analysis System version 5 Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2008 Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2014 Mean tidal range of marsh units in Eastern Shore of Virginia salt marshes Shorelines of the Central California coastal region (1852-2016) used in shoreline change analysis Intersects for the Southern California coastal region generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0 Long and short-term shoreline intersect points for the western coast of North Carolina (NCwest), calculated using the Digital Shoreline Analysis System version 5.1 2017 lidar-derived mean high water shoreline for the coast of North Carolina from Cape Hatteras to Cape Lookout (NCcentral) Vegetation habitat units derived from 2014 aerial imagery and field data for the Elwha River estuary, Washington Vegetation habitat units derived from 2009 aerial imagery and field data for the Elwha River estuary, Washington 1970s Shorelines for Vieques and Culebra, Puerto Rico Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2008 Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2014 Long-term and short-term shoreline change rates for Outer Cape Cod, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 Mean tidal range of marsh units in Eastern Shore of Virginia salt marshes 2017 lidar-derived mean high water shoreline for the coast of North Carolina from Cape Hatteras to Cape Lookout (NCcentral) 2010 Shorelines for Vieques, Culebra, and Main Island of Puerto Rico 2018 mean high water shoreline of the coast of MA used in shoreline change analysis Long-term shoreline change rates for the Florida panhandle (FLph) coastal region using the Digital Shoreline Analysis System version 5 Faults—Point Sur to Point Arguello, California Transgressive Contours—Point Sur to Point Arguello, California Intersects for the Southern California coastal region generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0 Short-term shoreline change rates for the Florida east coast (FLec) coastal region using the Digital Shoreline Analysis System version 5 Long-term shoreline change rates for the Florida east coast (FLec) coastal region using the Digital Shoreline Analysis System version 5 Shorelines of the Central California coastal region (1852-2016) used in shoreline change analysis Multichannel Seismic-Reflection and Navigation Data Collected Using Sercel GI Guns and Geometrics GeoEel Digital Streamers During the Mid-Atlantic Resource Imaging Experiment (MATRIX), USGS Field Activity 2018-002-FA Split-beam Echo Sounder and Navigation Data Collected Using a Simrad EK80 Wide Band Tranceiver and ES38-10 Transducer During the Mid-Atlantic Resource Imaging Experiment (MATRIX), USGS Field Activity 2018-002-FA.