2017-2018 lidar-derived mean high water shoreline for the coast of South Carolina

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Frequently anticipated questions:

What does this data set describe?

Title:
2017-2018 lidar-derived mean high water shoreline for the coast of South Carolina
Abstract:
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 two new mean high water (MHW) shorelines extracted from lidar data collected in 2010 and 2017-2018. Previously published historical shorelines for South Carolina (Kratzmann and others, 2017) were combined with the new lidar shorelines to calculate long-term (up to 166 years) and short-term (up to 18 years) rates of change. Files associated with the long-term and short-term rates are appended with "LT" and "ST", respectively. A proxy-datum bias reference line that accounts for the positional difference in a proxy shoreline (e.g. High Water Line (HWL) shoreline) and a datum shoreline (e.g. MHW shoreline) is also included in this release.
Supplemental_Information:
Cross-referenced citations are applicable to the dataset as a whole.
  1. How might this data set be cited?
    Bartlett, Marie K., and Weber, Kathryn M., 20230815, 2017-2018 lidar-derived mean high water shoreline for the coast of South Carolina: data release doi:10.5066/P9LLAZYE, U.S. Geological Survey, Coastal and Marine Hazards and Resources Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

    This is part of the following larger work.

    Bartlett, Marie K., Farris, Amy S., and Weber, Kathryn M., 2023, USGS National Shoreline Change — A GIS compilation of new lidar-derived shorelines (2010, 2017, and 2018) and associated shoreline change data for coastal South Carolina: data release doi:10.5066/P9LLAZYE, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Bartlett, M.K., Farris, A.S., and Weber, K.M., 2023, USGS National Shoreline Change — A GIS compilation of new lidar-derived shorelines (2010, 2017, and 2018) and associated shoreline change data for coastal South Carolina: U.S. Geological Survey data release, https://doi.org/P9LLAZYE.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -80.876682
    East_Bounding_Coordinate: -78.600358
    North_Bounding_Coordinate: 33.840628
    South_Bounding_Coordinate: 32.081464
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/6480bf00d34eac007b57a87f?name=SC_shoreline_2017_2018_browse.JPG (JPEG)
    Map view of dataset.
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 2017
    Ending_Date: 2018
    Currentness_Reference:
    ground condition at the time of survey
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: vector digital data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      This is a Vector data set. It contains the following vector data types (SDTS terminology):
      • String (155)
    2. What coordinate system is used to represent geographic features?
      Grid_Coordinate_System_Name: Universal Transverse Mercator
      Universal_Transverse_Mercator:
      UTM_Zone_Number: 17
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.9996
      Longitude_of_Central_Meridian: -81.0
      Latitude_of_Projection_Origin: 0.0
      False_Easting: 500000.0
      False_Northing: 0.0
      Planar coordinates are encoded using coordinate pair
      Abscissae (x-coordinates) are specified to the nearest 0.6096
      Ordinates (y-coordinates) are specified to the nearest 0.6096
      Planar coordinates are specified in meters
      The horizontal datum used is WGS_1984.
      The ellipsoid used is WGS_84.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.257223563.
  7. How does the data set describe geographic features?
    SC_shorelines_2017_2018
    This dataset includes polyline shoreline for 2017/2018 extracted from lidar data. (Source: U.S. Geological Survey (USGS))
    FID
    Internal feature number. (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Shape
    Feature geometry. (Source: Esri) Feature geometry. This shoreline is a polyline shapefile.
    Type
    The vertical shoreline reference used for shoreline extraction. (Source: USGS)
    ValueDefinition
    MHWMean high water - a datum-based elevation reference
    Date_
    Date of lidar survey from which the shoreline was extracted. (Source: USGS) Date is in mm/dd/yyyy format
    Shape_Leng
    Length of feature in meter units (WGS 1984 UTM Zone 17N) (Source: Esri)
    Range of values
    Minimum:20.472
    Maximum:14523.033
    Year_
    Four-digit year of shoreline. (Source: USGS)
    ValueDefinition
    2017Year of lidar survey
    2018Year of lidar survey
    Uncy
    Estimate of shoreline position uncertainty in meters. Actual shoreline position is assumed to be within the range of this value (plus or minus, meters). Methods used to calculate the uncertainty are listed in the process steps. (Source: USGS)
    Range of values
    Minimum:2.087
    Maximum:18.937
    Entity_and_Attribute_Overview:
    The entity and attribute information provided here describes the tabular data associated with the dataset. Please review the individual attribute descriptions for detailed information.
    Entity_and_Attribute_Detail_Citation: U.S. Geological Survey

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Marie K. Bartlett
    • Kathryn M. Weber
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    Marie K. Bartlett
    U.S. Geological Survey
    Geologist
    384 Woods Hole Rd
    Woods Hole, MA

    508-457-8700 x2306 (voice)
    mbartlett@usgs.gov

Why was the data set created?

Historical shoreline positions are used to describe the movement of beaches through time and to maintain a national database of shoreline change. This particular shoreline dataset is a mean high water (MHW) datum-based shoreline extracted using a profile method (Farris and others, 2018) for 2017-2018. The profile method extracts the MHW position from point cloud data using a Matlab based approach. This shoreline is used in conjunction with other shoreline files to calculate rates of shoreline change for coastal South Carolina.

How was the data set created?

  1. From what previous works were the data drawn?
    2017 SC Lidar (source 1 of 2)
    NOAA Office for Coastal Management (NOAA/OCM), 20170913, 2017 USACE NCMP Topobathy Lidar: East Coast (NY, NJ, DE, MD, VA, NC, SC, GA): NOAA's Ocean Service, Coastal Services Center (CSC), Charleston, SC.

    Online Links:

    Type_of_Source_Media: Digital and/or Hardcopy
    Source_Contribution:
    The bare-earth lidar point cloud data in LAS format were used to extract shorelines using methods described in the process steps. The data were downloaded using the cart feature in UTM Zone 17 projection with NAD83 horizontal datum and NAVD88 vertical datum (meters).
    2018 SC Lidar (source 2 of 2)
    NOAA Office for Coastal Management (NOAA/OCM), 20181108, 2018 USACE NCMP Topobathy Lidar: East Coast (CT, MA, ME, NC, NH, RI, SC): NOAA's Ocean Service, Coastal Services Center (CSC, Charleston, SC.

    Online Links:

    Type_of_Source_Media: Digital and/or Hardcopy
    Source_Contribution:
    The bare-earth lidar point cloud data in LAS format were used to extract shorelines using methods described in the process steps. The data were downloaded using the cart feature in UTM Zone 17 projection with NAD83 horizontal datum and NAVD88 vertical datum (meters).
  2. How were the data generated, processed, and modified?
    Date: 2022 (process 1 of 3)
    MHW shorelines are datum-based and in the case of the 2017/2018 shoreline, are extracted from lidar data using a profile method, described in Farris and others (2018). The appropriate MHW elevation values were obtained from Weber and others (2005). From the southern border with Georgia to Kiawah Island the MHW elevation is 0.75. North of Kiawah Island to the North Carolina border, the MHW elevation is 0.51. Person who carried out this activity:
    Marie K. Bartlett
    U.S. Geological Survey
    384 Woods Hole Rd
    Woods Hole, MA

    508-548-8700 x 2306 (voice)
    mbartlett@usgs.gov
    Date: 2022 (process 2 of 3)
    The profile method used to extract the operational MHW shoreline from the lidar point cloud data utilizing the Matlab-based approach (Matlab version 2019b) is described in Farris and others (2018). The profile method used a coast-following reference line with 20-meter spaced profiles. All lidar data points that were within 1 meter of each profile line were associated with that profile. All processing was done on the 2-meter-wide profiles, working on a single profile at a time. For each profile, a linear regression was fit through data points on the foreshore and the regression was evaluated at the MHW elevation to yield the cross-shore position of the MHW shoreline. If there was a data gap at MHW or if the MHW elevation was obscured by water points, the linear regression was simply extrapolated to the MHW elevation. For each profile, the foreshore beach slope was defined as the slope of the regression line. This slope is stored and later used for the calculation of the proxy-datum bias feature. Each MHW shoreline point that was extracted using this profile method has an uncertainty associated with it. For the new 2017/2018 lidar shoreline, this uncertainty includes four components: 1) the 95% confidence interval on the linear regression estimate of the shoreline position; 2) the vertical error of the raw lidar data as reported in the metadata; 3) a 15 cm vertical error in our chosen value of MHW, and; 4) the uncertainty due to extrapolation (if the shoreline was determined using extrapolation). These four components of uncertainty were added in quadrature to yield a total error for each shoreline point. The 2017 shoreline was extracted by Kathryn M. Weber The 2018 shoreline was extracted by Marie K. Bartlett Person who carried out this activity:
    Marie K. Bartlett
    U.S. Geological Survey
    384 Woods Hole Rd
    Woods Hole, MA

    508-548-8700 x 2306 (voice)
    mbartlett@usgs.gov
    Data sources used in this process:
    • 2017 SC Lidar
    • 2018 SC Lidar
    Date: 2022 (process 3 of 3)
    The 2017 and 2018 shoreline segments were merged into one shoreline file and imported into a personal geodatabase in ArcMap v10.7.1. Coordinate system: UTM Zone 17N (WGS84). Person who carried out this activity:
    Marie K. Bartlett
    U.S. Geological Survey
    384 Woods Hole Rd
    Woods Hole, MA

    508-548-8700 x 2306 (voice)
    mbartlett@usgs.gov
  3. What similar or related data should the user be aware of?
    Himmelstoss, Emily A., Farris, Amy S., Henderson, Rachel E., Kratzmann, Meredith G., Ergul, Ayhan, Zhang, Ouya, Zichichi, Jessica L., and Thieler, E. Robert, 2018, Digital Shoreline Analysis System (version 5.1): U.S. Geological Survey Software: software release version 5.1, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Use the first two links to access the software. The third link directs to the DSAS project page. Current software at time of use was 5.1.
    Himmelstoss, Emily A., Henderson, Rachel E., Kratzmann, Meredith G., and Farris, Amy S., 20211019, Digital Shoreline Analysis System (DSAS) version 5.1 User Guide: Open-File Report 2021-1091, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Use the first two access the user guide. The third link directs to the DSAS project page.
    Farris, Amy S., Weber, Kathryn M., Doran, Kara S., and List, Jeffrey H., 2018, Comparing Methods Used by the U.S. Geological Survey Coastal and Marine Geology Program for Deriving Shoreline Position from Lidar Data: Open-File Report 2018-1121, U.S. Geological Survey, Reston, VA.

    Online Links:

    Kratzmann, Meredith G., Himmelstoss, Emily A., and Thieler, E. Robert, 2017, National assessment of shoreline change – A GIS compilation of updated vector shorelines and associated shoreline change data for the Southeast Atlantic Coast: data release 2017, U.S. Geological Survey, Reston, VA.

    Online Links:

    Weber, Kathryn M., List, Jeffrey H., and Morgan, Karen L.M., 2005, An operational mean high water datum for determination of shoreline position from topographic Lidar data: Open-File Report 2005-1027, U.S. Geological Survey, Reston, VA.

    Online Links:

How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?
    The attributes are based on the requirements of the Digital Shoreline Analysis System (DSAS) which include a date and uncertainty value.
  2. How accurate are the geographic locations?
    Positional uncertainty associated with the 2017/2018 lidar shoreline was calculated at each transect and includes four components: 1) the 95% confidence interval on the linear regression estimate of the shoreline position; 2) the vertical error of the raw lidar data as reported in the metadata; 3) a 15 cm vertical error in our chosen value of MHW, and; 4) the uncertainty due to extrapolation (if the shoreline was determined using extrapolation).
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    This shoreline dataset is a mean high water (MHW) datum-based shoreline extracted using the profile method (Farris and others 2018). See process steps for description of use. Although not a continuous shoreline for the entire coast of South Carolina, this shoreline file is complete and contains all shoreline segments used to calculate shoreline change rates along sections of the South Carolina coastal region where lidar data were available. These data adequately represented the shoreline position at the time of the survey. Remaining gaps in these data, if applicable, are a consequence of non-existing data or existing data that did not meet quality assurance standards.
  5. How consistent are the relationships among the observations, including topology?
    Adjacent shoreline segments do not overlap and are not necessarily continuous. Shorelines were visually assessed in map view to verify that no erroneous data were included. These data contain some short line segments (less than 30 meters) that were part of how the data were originally compiled and are in fact the correct shoreline positions.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints None.
Use_Constraints Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. Please recognize the U.S. Geological Survey as the originator of the dataset. These data are not to be used for navigation.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey
    Attn: USGS ScienceBase
    Denver Federal Center, Building 810, Mail Stop 302
    Denver, CO
    United States

    1-888-275-8747 (voice)
    sciencebase@usgs.gov
  2. What's the catalog number I need to order this data set? The dataset contains the polyline shapefile of the 2017-2018 South Carolina lidar shoreline used to calculate long and short-term rates of change (SC_shoreline_2017_2018.shp and other shapefile components), browse graphic (SC_shoreline_2017_2018_browse.JPG), and the FGDC CSDGM metadata in XML format.
  3. What legal disclaimers am I supposed to read?
    Neither the U.S. Government, the Department of the Interior, nor the USGS, nor any of their employees, contractors, or subcontractors, make any warranty, express or implied, nor assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, nor represent that its use would not infringe on privately owned rights. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the USGS in the use of these data or related materials. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), and have been processed successfully on a computer system at the USGS, no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. The USGS or the U.S. Government shall not be held liable for improper or incorrect use of the data described and/or contained herein. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 15-Aug-2023
Metadata author:
Marie K. Bartlett
U.S. Geological Survey
384 Woods Hole Rd
Woods Hole, MA
USA

508-548-8700 x2306 (voice)
whsc_data_contact@usgs.gov
Contact_Instructions:
The metadata contact email address is a generic address in the event the person is no longer with USGS.
Metadata standard:
FGDC Content Standards for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/whcmsc/SB_data_release/DR_P9LLAZYE/SC_shoreline_2017_2018.faq.html>
Generated by mp version 2.9.51 on Fri Aug 18 08:53:16 2023