SC Bias Feature – Feature class containing South Carolina proxy-datum bias information to be used in the Digital Shoreline Analysis System

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Frequently anticipated questions:

What does this data set describe?

Title:
SC Bias Feature – Feature class containing South Carolina proxy-datum bias information to be used in the Digital Shoreline Analysis System
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. Additional citations are located within individual process steps that pertain specifically to the method described in that step.
  1. How might this data set be cited?
    Bartlett, Marie K., Farris, Amy S., and Henderson, Rachel E., 20230815, SC Bias Feature – Feature class containing South Carolina proxy-datum bias information to be used in the Digital Shoreline Analysis System: 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: -80.878051
    East_Bounding_Coordinate: -78.550084
    North_Bounding_Coordinate: 33.855480
    South_Bounding_Coordinate: 32.080213
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/6480c553d34eac007b57bbb8?name=SC_bias_browse.JPG (JPEG)
    Map view of dataset.
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 2018
    Currentness_Reference:
    ground condition at the time of elevation 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 (347)
    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_bias_feature
    Table containing attribute information associated with the data set. (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. The feature is a polyline shapefile.
    bias
    This field heading is case-sensitive and name specific. The field contains a proxy-datum bias value describing the unidirectional horizontal offset (in meters) between the MHW elevation of the lidar data and HWL shoreline positions. Values of 0.001 represent areas where no bias was applied. For details on the components that make up the proxy-datum bias, refer to the Methods section of USGS Open-File Report 2010-1118 cross-referenced in the metadata (Source: USGS)
    Range of values
    Minimum:0.001
    Maximum:20.447
    bias_uncy
    The field contains the plus/minus horizontal uncertainty (meters) in the lidar shoreline position at each cross-shore beach profile. Values of 0.001 represent areas where no bias was applied. For details on the components that make up this uncertainty, refer to the Methods section of USGS Open-File report 2010-1118 cross-referenced in the metadata. (Source: USGS)
    Range of values
    Minimum:0.001
    Maximum:10.760
    Shape_Leng
    Length of feature in meter units (WGS 1984 UTM Zone 17N) (Source: USGS)
    Range of values
    Minimum:6.389
    Maximum:5165.921

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
    • Amy S. Farris
    • Rachel E. Henderson
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    Rachel E. Henderson
    384 Woods Hole Road
    Woods Hole, MA
    US

    508-548-8700 (voice)
    508-547-2310 (FAX)
    rehenderson@usgs.gov

Why was the data set created?

This feature records the proxy-datum bias (PDB) and the uncertainty in the PDB. The "bias feature" is a shapefile representation the proxy-datum bias (PDB) data previously published in tabular format (Himmelstoss and others, 2010, and Himmelstoss and others, 2018). These PDB data are used to shift older proxy-based shorelines so that they can be directly compared to newer datum-based shorelines and accurate rates can be calculated. These data are provided for users of the ArcGIS DSAS extension and should only be used to determine the corrected change rate when both datum-based (e.g. MHW) and proxy-based (e.g. HWL) shorelines are included in the dataset. In this publication, the proxy-based shorelines used in the analysis are from Kratzmann and others, 2017.

How was the data set created?

  1. From what previous works were the data drawn?
    2010 SC Lidar (source 1 of 3)
    NOAA Office for Coastal Management (NOAA/OCM), 20160523, 2010 USACE NCMP Topobathy Lidar: Atlantic Coast (NC, SC, GA, FL): Office for Coastal Management, Charleston, SC.

    Online Links:

    Type_of_Source_Media: Digital and/or Hardcopy
    Source_Contribution:
    Point cloud data used to extract the 2010 MHW shoreline position and calculate slope around MHW along a profile.
    2017 SC Lidar (source 2 of 3)
    NOAA Office for Coastal Management (NOAA/OCM), 20170913, 2017 USACE NCMP Topobathy Lidar: East Coast (NY, NJ, DE, MD, VA, NC, SC, GA): Office for Coastal Management, Charleston, SC.

    Online Links:

    Type_of_Source_Media: Digital and/or Hardcopy
    Source_Contribution:
    Point cloud data used to extract the 2017 MHW shoreline position and calculate slope around MHW along a profile.
    2018 SC Lidar (source 3 of 3)
    NOAA Office for Coastal Management (NOAA/OCM), 20181108, 2018 USACE NCMP Topobathy Lidar: East Coast (CT, MA, ME, NC, NH, RI, SC): Office for Coastal Management, Charleston, SC.

    Online Links:

    Type_of_Source_Media: Digital and/or Hardcopy
    Source_Contribution:
    Point cloud data used to extract the 2018 MHW shoreline position and calculate slope around MHW along a profile.
  2. How were the data generated, processed, and modified?
    Date: 2022 (process 1 of 10)
    Step 1: The proxy-datum bias calculation is made possible by utilizing data acquired in the processing for the profile method of shoreline extraction similar to the one developed by Stockdon and others (2002). This method extracts an elevation-based shoreline from point cloud lidar data using a Matlab-based approach (Matlab version 2015b). Using a coast-following reference line with 20 m spaced cross shore profiles, lidar data is analyzed within a two-meter swath around each profile. This method is used to extract the mean high water (MHW) shoreline, as well as slope, and uncertainty information. For South Carolina, the slope and uncertainty information at each profile was averaged over time using data from the years 2010, 2017 and 2018 where available.
    Stockdon, H.F., Sallenger, A.H., List, J.H., and Holman, R.A., 2002, Estimation of shoreline position and change using airborne topographic lidar data:  Journal of Coastal Research, v.18, no. 3, p. 502-513. [Also available at https://www.jstor.org/stable/4299097] Person who carried out this activity:
    U.S. Geological Survey
    Attn: Amy S. Farris
    Oceanographer
    384 Woods Hole Road
    Woods Hole, MA
    US

    508-548-8700 x2344 (voice)
    508-457-2310 (FAX)
    afarris@usgs.gov
    Data sources used in this process:
    • 2010 SC Lidar
    • 2017 SC Lidar
    • 2018 SC Lidar
    Data sources produced in this process:
    • avg slope data
    Date: 2022 (process 2 of 10)
    Step 2: There is a known horizontal offset between the datum-based lidar MHW shoreline and the proxy-based historical shorelines on open-ocean sandy beaches that nearly always acts in one direction (Ruggiero and List, 2009). This bias is called the proxy-datum bias (PDB). The PDB is primarily due to wave run-up and thus is affected by the slope of the foreshore and the movement of water (waves, tides) onto the foreshore, see equation for the PDB and the PDB uncertainty in Ruggiero and List, 2009. These equations require beach slope and wave data. Ideally data collected at the time the proxy-based shoreline was collected would be used, however, for our purposes the PDB is estimated by averaging all available slope data (described in step 1) and averaging at least 10 years of historical wave data from a nearby buoy (https://www.ndbc.noaa.gov/) and the U.S. Wave Information Study (WIS - https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00071) The resulting PDB and PDB uncertainty is stored to a point shapefile at the intersection of the each profile with the coast-following reference line.
    Ruggiero, P., and List, J.H., 2009, Improving accuracy and statistical reliability of shoreline position and change rate estimates: Journal of Coastal Research, v. 25, no. 5, p. 1069-1081. [Also available at https://www.jstor.org/stable/27752753]
    National Data Buoy Center, National Oceanic and Atmospheric Administration (NOAA) Stennis Space Center, MS 39529 https://www.ndbc.noaa.gov/
    U.S. Wave Information Study, DOC/NOAA/NESDIS/NCEI National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce, https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00071 Person who carried out this activity:
    U.S. Geological Survey
    Attn: Amy S. Farris
    Oceanographer
    384 Woods Hole Road
    Woods Hole, MA
    US

    508-548-8700 x2344 (voice)
    508-457-2310 (FAX)
    afarris@usgs.gov
    Data sources used in this process:
    • avg slope data
    • buoy data
    Data sources produced in this process:
    • bias point data
    Date: 2022 (process 3 of 10)
    Step 3: To be used with DSAS, the data from the bias points must be connected to a shapefile that is near or adjacent to the DSAS baseline. However, the resulting bias points from the lidar shoreline extraction do not always fall near the baseline. The following steps (Step 4 - Step 9) detail how a series of transects are created to connect the point bias data to a coast following polyline feature. The following process steps were performed by the same person, Marie K. Bartlett. Person who carried out this activity:
    U.S. Geological Survey
    Attn: Marie K. Bartlett
    384 Woods Hole Road
    Woods Hole, MA
    USA

    508-548-8700 x2600 (voice)
    508-457-2310 (FAX)
    mbartlett@usgs.gov
    Date: 2022 (process 4 of 10)
    Step 4. A personal geodatabase was created and the baseline and sample shorelines for the project area were added (see larger work citation for data). Using DSAS v5.1, the default parameters were set for midshore baseline. Transects were cast using 20-meter spacing, a search distance of 1000, and smoothing distance of 2000. Once cast, the transects were evaluated with the original bias points to ensure the transects overlapped with the bias points and baseline. If needed, the transects were recast with a larger search distance. Data sources produced in this process:
    • transects
    Date: 2022 (process 5 of 10)
    Step 5. The data from the original bias points are transferred to the transects, using the ArcTool “Spatial Join” (ArcToolbox > Analysis Tools > Overlay > Spatial Join). The resulting Bias_transect contains all the original bias information. The Bias_transect is then converted to a midpoint using the ArcTool "Feature Vertices to Points" (ArcToolbox > Data Management Tools > Features > Feature Vertices to Points) and selecting the midpoint option. As the transects were cast with the midshore baseline options, the midpoint will intersect the baseline. The resulting Bias_midpoint, contains all the original bias information. Data sources used in this process:
    • bias point data
    • transects
    Data sources produced in this process:
    • Bias_midpoint
    Date: 2022 (process 6 of 10)
    Step 6. A copy of the baseline is created, and split into 20-meter increments, to match the spacing and detail of the bias_midpoint feature. Points spaced at 20 meters along the original baseline were created using the ArcTool "Generate Points along Lines" at a distance of 20 meters. Then the ArcTool "Split Line at Point" was used with the copy of the baseline, to generate a new feature that has 20 meter segments: Feature_20m. Data sources used in this process:
    • Bias_midpoint
    Data sources produced in this process:
    • Feature_20m
    Date: 2022 (process 7 of 10)
    Step 7. The data from Bias_midpoint are transferred to the new baseline Feature_20m, using the ArcTool “Spatial Join” (ArcToolbox > Analysis Tools > Overlay > Spatial Join) resulting in a new polyline feature (Feature_wbias) containing all the original bias information, at 20 meter increments. Data sources used in this process:
    • bias point data
    Data sources produced in this process:
    • Feature_wbias
    Date: 2022 (process 8 of 10)
    Step 8. The ArcTool "Unsplit Line" (ArcToolbox > Data Management Toolbox > Features > Unsplit Line) was used to reconnect any adjacent 20 meter segment with the same bias, and bias uncertainty values, reducing the number of small segments of bias feature. The final bias feature shapefile holds the bias and the bias uncertainty. These components are used by DSAS v5.1 to apply the proxy-datum bias correction to shoreline change calculations. Data sources used in this process:
    • Feature_wbias
    Data sources produced in this process:
    • Bias_Feature
    Date: 2022 (process 9 of 10)
    Step 9. The Bias_Feature was imported into a personal geodatabase in ArcCatalog v10.5 by right-clicking on the geodatabase > Import > Feature class (single). The feature class is used with the Digital Shoreline Analysis System (DSAS) v5.1 software to apply the proxy-datum bias to rate calculations.
    Date: 2022 (process 10 of 10)
    Step 10. The bias_feature was exported from a personal geodatabase in ArcCatalog v10.5 by right-clicking on the geodatabase > Export > Feature class (single). Coordinate System: UTM Zone 17N (WGS84) Data sources used in this process:
    • Bias_Feature
    Data sources produced in this process:
    • SC_Bias_Feature
  3. What similar or related data should the user be aware of?
    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:

    Himmelstoss, Emily A., Kratzmann, Meredith G., and Thieler, E. Robert, 2017, 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:

    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 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., 2021, 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 links to access the user guide. The third link directs to the DSAS project page.
    Stockdon, Hillary F., Sallenger, Asbury H., List, Jeffrey H., and Holman, Rob A., 2002, Estimation of shoreline position and change using airborne topographic lidar data: Journal of Coastal Research vol. 18, Coastal Education and Research Foundation, Charlotte, NC.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Stockdon, H.F., Sallenger, A.H., List, J.H., and Holman, R.A., 2002, Estimation of shoreline position and change using airborne topographic lidar data:  Journal of Coastal Research, v.18, no. 3, p. 502-513., https://www.jstor.org/stable/4299097
    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 in this feature class record positional and measurement uncertainties and datum offsets calculated from averaged slope data (2010-2018) and local wave data. The field names are based on the requirements for use within the Digital Shoreline Analysis System (DSAS) software (Himmelstoss and others, 2018).
  2. How accurate are the geographic locations?
    The horizontal location of the bias feature is coincident with the DSAS baseline. The baseline serves as a reference point for transects cast by the DSAS software. The baseline and bias feature do not correspond to any real-world feature.
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    The feature contains bias and uncertainty data where lidar data was available for the area. Adjustments were made where applicable after a visual inspection of the coastal shoreline type using high resolution digital imagery. Areas where bias is applied include open ocean sandy shorelines. Areas where bias was not applied include proximity to inlets, back barrier or marsh areas, rocky headlands and shoreline protection structures. In some cases the bias was adjusted to match adjacent bias values with similar morphology.
  5. How consistent are the relationships among the observations, including topology?
    Each line segment is a copy of the polyline baseline data for the area. The proxy-datum bias and bias uncertainty for each line segment are calculated using the slope data from available lidar surveys for the area (see process steps for details). Attributes populated include numerical values for adjusted bias (bias) and bias uncertainty (bias_uncy).

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 These data were generated for use within the DSAS v5.1 software, with shoreline data that has both mean high water (MHW) and high water line (HWL) data types present. Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. These data should not be used for any purpose other than that for which they are intended. The United States Geological Survey does not guarantee its validity. Assumptions, analyses, opinions, and actual outcomes may vary. The user should always verify actual data and exercise their own professional judgment when interpreting any outcomes. These data should not be used for any purpose other than that for which they are intended. The United States Geological Survey does not guarantee its validity. Assumptions, analyses, opinions, and actual outcomes may vary. The user should always verify actual data and exercise their own professional judgment when interpreting any outcomes. 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
    Federal Center, Building 810, MS 302
    Denver, CO

    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 proxy-datum bias and its uncertainty, (SC_Bias_Feature.shp and other shapefile components), browse graphic (SC_Bias_Feature_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. 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:
U.S. Geological Survey
Attn: Marie K. Bartlett
Geologist
384 Woods Hole Road
Woods Hole, MA
US

508-548-8700 x 2306 (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 Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/whcmsc/SB_data_release/DR_P9LLAZYE/SC_bias_feature.faq.html>
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