Long-term shoreline change rate transects for the South Carolina coastal region, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1

Metadata also available as - [Outline] - [Parseable text] - [XML]

Frequently anticipated questions:

What does this data set describe?

Long-term shoreline change rate transects for the South Carolina coastal region, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1
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.
Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.1, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate based on available shoreline data. 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 rates. This dataset consists of shoreline change rates calculated with DSAS version 5.1 and stored as a new transect layer. Original measurement transects are cast by DSAS from the baseline to intersect shoreline vectors, and the intersect data provide location and time information used to calculate rates of change.
  1. How might this data set be cited?
    Bartlett, Marie K., 20230815, Long-term shoreline change rate transects for the South Carolina coastal region, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1: 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:

    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: -80.876514
    East_Bounding_Coordinate: -78.554070
    North_Bounding_Coordinate: 33.850439
    South_Bounding_Coordinate: 32.080224
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/6480bf65d34eac007b57a91b?name=SC_rates_LT_browse.JPG (JPEG)
    Map view of dataset
  4. Does the data set describe conditions during a particular time period?
    Ending_Date: 2018
    ground condition at the time of shoreline source data
  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 (5595)
    2. What coordinate system is used to represent geographic features?
      Grid_Coordinate_System_Name: Universal Transverse Mercator
      UTM_Zone_Number: 17
      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?
    Rates of long-term shoreline change are calculated by DSAS and stored in the transect file, using the distance measurements between shorelines and baseline at each DSAS transect. These attributes are for long-term shoreline change rates with and without the proxy-datum bias correction applied. The shapefiles will have LT for long-term in filename. Rate calculations without the proxy-datum bias correction applied will have "NB_" In the attribute field title. (Source: U.S. Geological Survey (USGS))
    Internal feature number. (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Feature geometry. (Source: Esri) Feature geometry. Rates are polyline shapefiles.
    Unique identification number of the baseline segment. If BaselineID=0 no transects will be generated. Used by DSAS to determine transect ordering alongshore if multiple baseline segments exist. (Source: USGS)
    Range of values
    Optional field to aggregate transects on the basis of physical variations alongshore (for example, tidal inlets, change in coastal type, or hard stabilization features). This value was assigned by the user as an attribute to a baseline segment and results in a group average being reported in the DSAS summary text file. (Source: USGS)
    Range of values
    Assigned by DSAS based on ordering of transects along the baseline. Used to allow user to sort transect data along the baseline from baseline start to baseline end. (Source: USGS)
    Range of values
    Assigned by DSAS to record the azimuth of the transect measure in degrees clockwise from North. If a transect position has been adjusted during the editing process, the azimuth value in the attribute table is updated automatically. (Source: USGS)
    Range of values
    Number of shorelines used to compute shoreline change metrics. (Source: USGS)
    Range of values
    The Total Cumulative Distance (TCD) is the measure in meters along shore from the start of the baseline segment with an ID=1, and measured sequentially alongshore to the end of the final baseline segment. (Source: USGS)
    Range of values
    Length of feature in meter units (UTM zone 17N, WGS 84) (Source: USGS)
    Range of values
    A linear regression rate-of-change statistic was calculated by fitting a least-squares regression line to all shoreline points for a particular transect. Any shoreline points that are referenced to HWL were adjusted by the proxy-datum bias distance (meters) along the transect to correct for the offset between proxy-based HWL and datum-based MHW shorelines. The best-fit regression line is placed so that the sum of the squared residuals (determined by squaring the offset distance of each data point from the regression line and adding the squared residuals together) is minimized. The linear regression rate is the slope of the line. The rate is reported in meters per year with positive values indicating accretion and negative values indicating erosion. (Source: USGS)
    Range of values
    The LRR without the bias correction applied. Decimal values may be positive or negative, which is used to indicate landward (negative) or seaward (positive) direction from baseline origin. Reported in meters per year. (Source: USGS)
    Range of values
    The R-squared statistic, or coefficient of determination, is the percentage of variance in the data that is explained by a regression. It is a dimensionless index that ranges from 1.0 to 0.0 and measures how successfully the best-fit line accounts for variation in the data. The smaller the variability of the residual values around the regression line relative to the overall variability, the better the prediction (and closer the R-squared value is to 1.0). (Source: USGS)
    Range of values
    The LR2 without the bias correction applied. (Source: USGS)
    Range of values
    This quantity is the standard error of the regression, also known as the standard error of the estimate. To calculate it, the distance between each data point and the regression line is calculated. These distances are squared then summed. The sum is divided by the number of data point minus two. The square root is taken of the result. These are positive decimal values in meters. (Source: USGS)
    Range of values
    The LSE without the bias correction applied. (Source: USGS)
    Range of values
    The 90 percent confidence interval (LCI90) is calculated by multiplying the standard error of the slope by the two-tailed test statistic at the user-specified 90 percent confidence. This value is often reported in conjunction with the slope to describe the confidence of the reported rate. For example: LRR = 1.2 and LCI90 = 0.7 could be reported as a rate of 1.2 (+/-) 0.7 meters/year. These are positive decimal values in meters. (Source: USGS)
    Range of values
    The LCI90 without the bias correction applied. These are positive decimal values in meters. (Source: USGS)
    Range of values
    The entity and attribute information provided here describes the tabular data associated with long-term shoreline change rates. Long-term rates incorporate the known unidirectional offset between proxy-based high water line features and datum-based mean high water line features (the proxy-datum bias). Please review the individual attribute descriptions for detailed information. All calculations for length are in meter units and were based on the UTM zone 17N WGS 84 projection.
    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
  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
    384 Woods Hole Rd
    Woods Hole, MA
    United States

    508-457-8700 x2306 (voice)

Why was the data set created?

This dataset describes the long-term (up to 166 years) shoreline change rates for the South Carolina coastal region, used to maintain a national database of shoreline change.

How was the data set created?

  1. From what previous works were the data drawn?
    SC_historical_shorelines (source 1 of 1)
    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 doi:10.5066/F74X55X7, U.S. Geological Survey, Reston, VA.

    Online Links:

    Type_of_Source_Media: Digital and/or Hardcopy
    These shorelines were combined with new lidar shorelines for 2010, 2017, and 2018 and used within the Digital Shoreline Analysis System version 5.1 to produce long-term shoreline change rates.
  2. How were the data generated, processed, and modified?
    Date: 2022 (process 1 of 5)
    Historical shoreline data covering the coast of South Carolina from the previously published National Assessment of Shoreline Change: A GIS compilation of Updated Vector Shorelines and Associated Shoreline Change Data for the Southeast Atlantic Coast (USGS data release, https://doi.org/10.5066/F74X55X7.) were compiled and merged into a single feature class within a personal geodatabase in ArcMap v 10.7.1. The data were projected in ArcToolbox v10.7.1 > Data Management Tools > Projections and Transformations > Feature > Project. Parameters: input projection = geographic coordinates (WGS84); output projection = UTM zone 17N (WGS 84); transformation = none. Historical shoreline data covers date range 1852-2000 and includes one lidar-derived shoreline (2000). See associated source metadata (https://www.sciencebase.gov/catalog/item/58b89084e4b01ccd5500c2ac) in larger work citation for complete process steps for historical shoreline delineation. This process step and all subsequent process steps were performed by the same person - Marie K. Bartlett Person who carried out this activity:
    Marie K. Bartlett
    U.S. Geological Survey
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 x 2306 (voice)
    Date: 2022 (process 2 of 5)
    The datum-based, MHW shorelines (see larger work citation, SC_shoreline_2010 and SC_shoreline_2017_2018) and historical shorelines compiled for analysis (SC_historical_shorelines) were confirmed to have the same attribute fields required for use in DSAS before they were merged into a single feature class using Esri's ArcToolbox > Data Management > General > Merge, filename= SC_shorelines. Some shoreline segments from 1962 and 2000, and one segment from 1925 were removed from the dataset prior to analysis because they represented the wrong feature. Data sources used in this process:
    • SC_historical_shorelines
    Date: 2023 (process 3 of 5)
    Transect features were generated in a personal geodatabase using DSAS v5.1.2020.0720.0030. Parameters Used: baseline layer= SC_baseline, baseline group field=NULL, shoreline layer= SC_shorelines, transect spacing=50 meters, search distance=1000 meters, land direction=right, shoreline intersection=seaward, File produced = SC_transects_LT. Some transects were manually edited for length, moved, or deleted in an edit session using standard editing tools in the editor toolbar, in ArcMap v10.7.1. For additional details on these parameters, please see the DSAS help file distributed with the DSAS software, or visit the USGS website at:https://www.usgs.gov/centers/whcmsc/science/digital-shoreline-analysis-system-dsas
    Date: 2023 (process 4 of 5)
    Long-term rate calculations performed producing rates with and without the proxy-datum bias correction. Parameters Used: Shoreline layer = SC_shorelines, Shoreline date field = Date_, shoreline uncertainty field name = Uncy, default accuracy = 5.1 meters, shoreline intersection = seaward, stats calculations = [LRR], shoreline threshold = 3, confidence interval=90%. Files produced = SC_trans_LT_rates_20230504_120014, SC_trans_LT_intersect_20230504_120014. All shorelines have an uncertainty value listed in the attribute table that provides the horizontal uncertainty associated with the shoreline, regardless of the method used. Uncertainty for historical shorelines (1852-2000) is found in Kratzmann and others, 2017, which is listed as a source citation in this metadata file. The historical shoreline database contains both MHW and HWL shorelines thus a proxy-datum bias (PDB), stored as a line feature class appended to the reference baseline, is applied during rate calculation (see larger work citation, SC_bias_feature). For more information about the origin of the PDB see Ruggiero and List (2009), which is cross-referenced in this metadata file. Rate statistics are presented with and without the PDB correction applied, denoted in the transects/rates attribute table with “NB_” or “No bias”. The bias uncertainty values are stored within the bias feature attribute table.
    Date: 2023 (process 5 of 5)
    The rate feature class was exported to shapefiles in ArcMap v10.7.1 by right-clicking the transect layer > data > export data. Coordinate system: UTM Zone 17N (WGS84)
  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, 2021, 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:

    Use the first two links to access the software. The third link directs to the DSAS project page. Current version of 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 (version 5.1) User Guide: Open-File Report 2021-1091, U.S. Geological Survey, Reston, VA.

    Online Links:

    Refer to the DSAS user guide for more information about attribute requirements, accuracy reports, and feature creation.
    Himmelstoss, Emily A., Kraztmann, Meredith G., and Thieler, E. Robert, 20170718, National assessment of shoreline change—Summary statistics for updated vector shorelines and associated shoreline change data for the Gulf of Mexico and Southeast Atlantic coasts: Open-File Report 2017-1015, U.S. Geological Survey, Reston, VA.

    Online Links:

    Ruggiero, Peter, and List, Jeffrey H., 200909, Improving Accuracy and Statistical Reliability of Shoreline Position and Change Rate Estimates: Journal of Coastal Research vol. 255, Coastal Education and Research Foundation, Charlotte, NC.

    Online Links:

    Other_Citation_Details: ppg. 1069-1081

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

  1. How well have the observations been checked?
    The attributes of this dataset are based on the field requirements of the Digital Shoreline Analysis System and were automatically generated by the software during the generation of the transect layer or during the calculation of shoreline change rates performed by the software.
  2. How accurate are the geographic locations?
    The uncertainty of the linear regression rate is estimated by the elements LR2, LSE and LCI90. See the attribute definition of each for more information.
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    This dataset contains the transects automatically generated by the DSAS software application that were used to calculate shoreline change rates for the region. Additional transects may have been generated but did not intersect the minimum requirement of three shorelines, at least one of which must be a modern lidar shoreline. Shoreline change rates data are provided where there are available shorelines to compute change metrics. Though the full database of shorelines was utilized for analysis (1852-2018), gaps in shorelines or lack of lidar data in certain areas may mean that not all transects will incorporate every shoreline date in the rate calculations.
  5. How consistent are the relationships among the observations, including topology?
    These data were generated using DSAS v5.1. The transects automatically generated by the software were visually inspected along with the shoreline data prior to rate calculations. Sometimes transect positions were manually edited within a standard ArcMap edit session to adjust the position at which individual transects intersect the shorelines to better represent an orthogonal position to the general trend of the coast. It is possible that a small (centimeter-scale) offset may occur when projecting from outside of the spatial reference system used for analysis (UTM Zone 17N WGS84). This is an ArcGIS projection issue; rate data are unaffected.

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)
  2. What's the catalog number I need to order this data set? The dataset contains the polyline shapefile of South Carolina long-term rates of change (SC_rates_LT.shp and other shapefile components), browse graphic (SC_rates_LT_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?

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

508-548-8700 x2306 (voice)
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_rates_LT.faq.html>
Generated by mp version 2.9.51 on Fri Aug 18 08:53:16 2023