USGS task order 140G0218F0420 required Winter, 2018/Spring, 2019 LiDAR surveys to be collected over 32,562 square miles covering part or all of 82 counties in Georgia and 3 partial counties in South Carolina in support of the State of Georgia and the USGS 3DEP program. Aerial LiDAR data for this task order was planned, acquired, processed and produced at an aggregate nominal pulse spacing (ANPS...

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the USGS has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1997-2002. Each shoreline may represent a compilation of data from one or more sources for one or more dates provided by one or more agencies. Details regarding source are provided in the 'Data Quality Information' section of this metadata report. Shoreline vectors derived from historic sources (first three time periods) represent the high water line at the time of the survey, whereas modern shorelines (final time period) represent the mean high water line.

This is a tiled collection of the 3D Elevation Program (3DEP) and is one meter resolution. The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. Scientists and resource managers use 3DEP data for hydrologic modeling, resource monitoring, mapping and visualization, and many other applications. The elevations in this DEM represent the topographic bare-earth surface. USGS standard one-meter DEMs are produced exclusively from high resolution light detection and ranging (lidar) source data of one-meter or higher resolution. One-meter DEM surfaces are seamless within collection projects, but, not necessarily seamless across projects. The spatial reference used for tiles of the one-meter DEM within the conterminous United States (CONUS) is Universal Transverse Mercator (UTM) in units of meters, and in conformance with the North American Datum of 1983 ...

Rates of long-term and short-term shoreline change were generated in a GIS with the Digital Shoreline Analysis System (DSAS) version 2.0, an ArcView extension developed by the USGS in cooperation with TPMC Environmental Services. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcView contains three main components that define a baseline, generate orthogonal transects at a user-defined separation along the coast, and calculate rates of change (linear regression, endpoint rate, average of rates, average of endpoints, jackknife).

The dataset is a digital elevation model (DEM) of the bathymetry of Norfork Lake, Arkansas-Missouri, below a pool elevation of 580 ft above the North American Vertical Datum of 1988 (NAVD88). The DEM was derived from a terrain (digital terrain model, or DTM) created from a feature dataset of point (XYZ) data collected during an aerial LiDAR survey conducted in March, 2008, and a bathymetric survey conducted in September-October, 2015. References: Lee, 2013, Estimation of reservoir storage capacity using multibeam sonar and terrestrial LiDAR, Randy Poynter Lake, Rockdale County, Georgia, 2012: U.S. Geological Survey Scientific Investigations Map 3265, 1 sheet, https://pubs.usgs.gov/sim/3265/; Huizinga, 2016, Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, June 2–4, 2015: U.S. Geological Survey Scientific Investigations Report 2016–5061, 93 p., http://dx.doi.org/10.3133/sir20165061.

The dataset is a digital elevation model (DEM), in GeoTiff format, of the bathymetry of DeQueen Lake, Sevier County, Arkansas, below a pool elevation of 474 ft above the North American Vertical Datum of 1988 (NAVD88). The DEM was derived from a terrain (digital terrain model, or DTM) created from a feature dataset of XYZ (point) data from an aerial LiDAR survey conducted in March, 2008 for the U.S. Army Corps of Engineers, Little Rock District, and a bathymetric survey conducted in July, 2015, by the Lower Mississippi-Gulf Water Science Center of the U.S. Geological Survey (USGS) using methodologies for multi-beam sonar surveys similar to those described by Lee, K.G. (2013) and Huizinga (2016). References: Lee, K.G., 2013, Estimation of reservoir storage capacity using multibeam sonar and terrestrial LiDAR, Randy Poynter Lake, Rockdale County, Georgia, 2012: U.S. Geological Survey Scientific Investigations Map 3265, 1 sheet, https://pubs.usgs.gov/sim/3265/; Huizinga, R.J., 2016, Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, June 2–4, 2015: U.S. Geological Survey Scientific Investigations Report 2016–5061, 93 p., http://dx.doi.org/10.3133/sir20165061.

Rates of long-term and short-term shoreline change were generated in a GIS with the Digital Shoreline Analysis System (DSAS) version 2.0, an ArcView extension developed by the USGS in cooperation with TPMC Environmental Services. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcView contains three main components that define a baseline, generate orthogonal transects at a user-defined separation along the coast, and calculate rates of change (linear regression, endpoint rate, average of rates, average of endpoints, jackknife).

Attempts to stabilize the shore can greatly influence rates of shoreline change. Beach nourishment in particular will bias rates of observed shoreline change toward accretion or stability, even though the natural beach, in the absence of nourishment, would be eroding.

Pilkey and Clayton (1990) prepared a summary of identifiable beach nourishment projects in the Atlantic Coast region. Those records were used to identify shoreline segments that had been influenced by beach nourishment. Supplemental information regarding beach nourishment was collected from agencies familiar with nourishment projects in the State. All records were compiled to create a GIS layer depicting the spatial extents of nourishment projects within the State.

Beach erosion is a chronic problem along most open-ocean shores of the United States. As coastal populations continue to grow, and community infrastructures are threatened by erosion, there is increased demand for accurate information regarding past and present shoreline changes. There is also need for a comprehensive analysis of shoreline movement that is regionally consistent. To meet these national needs, the USGS National Assessment of Shoreline Change Project has collected and analyzed a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data.

This dataset consists of short-term (~30 years) shoreline change rates. Rate calculations were computed using the Digital Shoreline Analysis System (DSAS), an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using an end-point rate method based on available shorelines to provide an approximately 30-yr short-term rate. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to calculate short-term rates.

To make these results more accessible to the public and other agencies, the USGS created this web service. This web service was created utilizing ESRI ArcServer. This service meets open geospatial consortium standards.

The data compilation used to derive the shoreline change rates is available in a service with the title USGS Map service: National Shoreline Change - Historic Shorelines by State. The reference baseline used to derive the shoreline change rates is available in a service with the title USGS Map service: National Shoreline Change - Offshore Baseline. The locations of the transects used in the change rate calculation are available in a service with the title USGS Map service: National Shoreline Change - Intersection Points.

The geographic information system (GIS) data layers from this web service are cataloged by state for ease of access.

Rates of long-term and short-term shoreline change were generated in a GIS with the Digital Shoreline Analysis System (DSAS) version 2.0, an ArcView extension developed by the USGS in cooperation with TPMC Environmental Services. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcView contains three main components that define a baseline, generate orthogonal transects at a user-defined separation along the coast, and calculate rates of change (linear regression, endpoint rate, average of rates, average of endpoints, jackknife).

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the USGS has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Historical shoreline positions serve as easily understood features that can be used to describe the movement of beaches through time. These data are used to calculate rates of shoreline change for the U.S. Geological Survey's (USGS) National Assessment of Shoreline Change Project.

Each shoreline may represent a compilation of data from one or more sources for one or more dates provided by one or more agencies. Details regarding source are provided in the 'Data Quality Information' section of the individual shoreline metadata report.

To make this shoreline data more accessible to the public and other agencies, the USGS created this web service. This web service was created utilizing ESRI ArcServer. Vector shoreline layers were collected, organized by state, and symbology made consistent among similar data sets. This service meets open geospatial consortium standards.