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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 (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 (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 (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 (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 (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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This data release contains coastal wetland synthesis products for Chesapeake Bay. 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 tools to estimate the vulnerability and ecosystem service potential of these wetlands. For this purpose, the response and resilience of coastal wetlands to physical factors...
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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 (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 (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 (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 geochemical data included here were generated as part of the Earth Mapping Resources Initiative (Earth MRI), which was developed by the U.S. Geological Survey (USGS) in response to a Federal directive calling on various Federal agencies to address potential vulnerabilities in the Nation’s supply of critical mineral resources. Earth MRI is a partnership between the USGS, State Geological Surveys, and industry coordinating with other federal agencies to accomplish the mission. The primary purpose of this initiative is to identify potentially mineralized areas containing critical minerals by gathering new basic geologic data about the United States and its territories and to make these data publicly available through...
Categories: Data, Data Release - Revised; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service, Shapefile; Tags: Alabama, Alaska, Alaska Division of Geological & Geophysical Surveys, Arizona, Arizona Geological Survey, 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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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 (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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This data release supersedes version 1.0, published in September 2022 at https://doi.org/10.5066/P9XEFRYR. Versioning details are documented in the accompanying Dunex_revision_history.txt file. These data provide grain-size measurements from sediment samples collected as part of the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge, NC. DUNEX is a multi-agency, academic, and non-governmental organization collaborative community experiment designed to study nearshore coastal processes during storm events. USGS participation in DUNEX will contribute new measurements and models that will increase our understanding of storm impacts to coastal environments, including hazards...
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Reliable estimates of the magnitude and frequency of floods are an important part of the framework for hydraulic-structure design and flood-plain management. Annual peak flows measured at U.S. Geological Survey streamgages are used to compute flood-frequency estimates at those streamgages. However, flood-frequency estimates also are needed at ungaged stream locations. A process known as regionalization was used to develop regression equations to estimate the magnitude and frequency of floods at ungaged locations. This dataset contains the supporting tables and updated hydrologic region boundaries used in the 2017 flood-frequency study for Georgia, South Carolina, and North Carolina.
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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 (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...


map background search result map search result map Ports of the United States Geochemical data generated by projects funded by the USGS Earth Mapping Resources Initiative (ver. 9.0, February 2024) Magnitude and Frequency of Floods for Rural Streams in Georgia, South Carolina, and North Carolina, 2017-Data Elevation of marsh units in Chesapeake Bay salt marshes 2017 lidar-derived mean high water shoreline for the coast of North Carolina from Cape Fear to the South Carolina border (NCwest) 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 intersect points for the western coast of North Carolina (NCwest), calculated using the Digital Shoreline Analysis System version 5.1 Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the western coast of North Carolina from Cape Fear to the South Carolina border (NCwest) 2017 lidar-derived mean high water shoreline for the coast of North Carolina from Cape Hatteras to Cape Lookout (NCcentral) Baseline for the North Carolina coastal region from Cape Hatteras to Cape Lookout (NCcentral) Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the central coast of North Carolina from Cape Hatteras to Cape Lookout (NCcentral) 2017 lidar-derived mean high water shoreline for the southern coast of North Carolina from Cape Lookout to Cape Fear (NCsouth) Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the southern coast of North Carolina from Cape Lookout to Cape Fear (NCsouth) Long and short-term shoreline change rate transects for the southern North Carolina coastal region (NCsouth), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 Long and short-term shoreline intersect points for the southern coast of North Carolina (NCsouth), calculated using the Digital Shoreline Analysis System version 5.1 2017 lidar-derived mean high water shoreline for the coast of North Carolina from the Virginia border to Cape Hatteras (NCnorth) Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the northern coast of North Carolina from the Virginia border to Cape Hatteras (NCnorth) Long and short-term shoreline change rate transects for the northern North Carolina coastal region (NCnorth), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 Long and short-term shoreline intersect points for the northern coast of North Carolina (NCnorth), calculated using the Digital Shoreline Analysis System version 5.1 Grain-size analysis data of sediment samples from the beach and nearshore environments at the Pea Island National Wildlife Refuge DUNEX site, North Carolina in 2021 Grain-size analysis data of sediment samples from the beach and nearshore environments at the Pea Island National Wildlife Refuge DUNEX site, North Carolina in 2021 2017 lidar-derived mean high water shoreline for the coast of North Carolina from the Virginia border to Cape Hatteras (NCnorth) Long and short-term shoreline intersect points for the northern coast of North Carolina (NCnorth), calculated using the Digital Shoreline Analysis System version 5.1 Long and short-term shoreline change rate transects for the northern North Carolina coastal region (NCnorth), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the northern coast of North Carolina from the Virginia border to Cape Hatteras (NCnorth) 2017 lidar-derived mean high water shoreline for the coast of North Carolina from Cape Hatteras to Cape Lookout (NCcentral) Baseline for the North Carolina coastal region from Cape Hatteras to Cape Lookout (NCcentral) Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the central coast of North Carolina from Cape Hatteras to Cape Lookout (NCcentral) 2017 lidar-derived mean high water shoreline for the southern coast of North Carolina from Cape Lookout to Cape Fear (NCsouth) Long and short-term shoreline intersect points for the southern coast of North Carolina (NCsouth), calculated using the Digital Shoreline Analysis System version 5.1 Long and short-term shoreline change rate transects for the southern North Carolina coastal region (NCsouth), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the southern coast of North Carolina from Cape Lookout to Cape Fear (NCsouth) Elevation of marsh units in Chesapeake Bay salt marshes Magnitude and Frequency of Floods for Rural Streams in Georgia, South Carolina, and North Carolina, 2017-Data Ports of the United States Geochemical data generated by projects funded by the USGS Earth Mapping Resources Initiative (ver. 9.0, February 2024)