Bias Feature for the Georgia coastal region containing proxy-datum bias information to be used in the Digital Shoreline Analysis System version 5

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Frequently anticipated questions:

What does this data set describe?

Title:
Bias Feature for the Georgia coastal region containing proxy-datum bias information to be used in the Digital Shoreline Analysis System version 5
Abstract:
During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion along the southeast US coastline and implications for vulnerability to future storms.
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?
    U.S. Geological Survey, 20210929, Bias Feature for the Georgia coastal region containing proxy-datum bias information to be used in the Digital Shoreline Analysis System version 5: data release DOI:10.5066/P9J3CVN4, 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.

    Kratzmann, Meredith G., Farris, Amy S., Weber, Kathy M., Henderson, Rachel E., and Himmelstoss, Emily A., 2021, USGS National Shoreline Change: A GIS compilation of Updated Vector Shorelines (1800s - 2010s) and Associated Shoreline Change Data for the Georgia and Florida Coasts: data release DOI:10.5066/P9J3CVN4, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    suggested citation: Kratzmann, M.G., Farris, A.S., Weber, K.M., Henderson, R.E., and Himmelstoss, E.A., 2021, USGS National Shoreline Change: A GIS compilation of Updated Vector Shorelines (1800s - 2010s) and Associated Shoreline Change Data for the Georgia and Florida Coasts: U.S. Geological Survey data release, https://doi.org/10.5066/P9J3CVN4
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -81.464492
    East_Bounding_Coordinate: -80.839754
    North_Bounding_Coordinate: 32.031587
    South_Bounding_Coordinate: 30.711767
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/614a8e5dd34e0df5fb975913?name=BG_GA_bias.jpg (jpg)
    Map view of data
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 2021
    Currentness_Reference:
    ground condition
  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 (196)
    2. What coordinate system is used to represent geographic features?
      Horizontal positions are specified in geographic coordinates, that is, latitude and longitude. Latitudes are given to the nearest 0.0197393776. Longitudes are given to the nearest 0.0264608689. Latitude and longitude values are specified in Decimal seconds. 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?
    GA_bias.shp
    Proxy-datum bias and uncertainty values for the Georgia (GA) coastal region. (Source: U.S. Geological Survey)
    FID
    Internal feature number used as a unique identifier of an object within a table primarily used in shapefiles. (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Shape
    Feature geometry. (Source: Esri) Coordinates defining the features.
    OBJECTID
    A unique identification number for each segment. (Source: U.S. Geological Survey) Sequential unique whole numbers that are automatically generated.
    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. The average value for GA is 13.0 meters. Values of 0.001 represent areas where there is no bias applied. (Source: U.S. Geological Survey)
    Range of values
    Minimum:0.001
    Maximum:20.782215
    Units:meters
    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 there is no bias applied. (Source: U.S. Geological Survey)
    Range of values
    Minimum:0.001
    Maximum:12.467177
    Units:meters
    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)
    • U.S. Geological Survey
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    U.S. Geological Survey
    384 Woods Hole Road
    Woods Hole, MA
    US

    508-548-8700 (voice)
    508-457-2310 (FAX)
    rehenderson@contractor.usgs.gov

Why was the data set created?

Shoreline positions were compiled prior to and following Hurricane Irma along the sandy shorelines of the Gulf of Mexico and Atlantic coasts of Florida and the coast of Georgia. Shoreline positions from the mid-1800s through 2018 were used to update the shoreline change rates for Florida and Georgia using the Digital Shoreline Analysis System (DSAS) software. The shoreline positions and updated shoreline change rates provide actionable information to homeowners, coastal communities, and managers of public and private properties to improve resiliency for long-term hazards.
The bias feature is a polyline shapefile representation of the proxy-datum bias (PDB) data previously published in tabular format (Himmelstoss and others 2010, Himmelstoss and others 2018). These PDB data are used to reconcile the offset between proxy-based shorelines and more recent datum-based shorelines so they can be directly compared when calculating shoreline change rates.
The bias feature contains the proxy-datum bias (PDB) value and the uncertainty in the PDB for the Georgia (GA) coastal region. These data are provided for users of DSAS and should only be used to determine the corrected change rate when both proxy-based (e.g., HWL) and datum based (e.g., MHW) shorelines are present in the same dataset. 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.

How was the data set created?

  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
    Date: 2020 (process 1 of 11)
    The profile method for lidar shoreline extraction (Farris and others, 2018) identifies 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-meter spaced profiles, lidar data are analyzed within a two-meter swath around each profile. This method is used to extract MHW shoreline, slope, and uncertainty information. The slope data for each profile were saved. The slope at each profile was averaged over time using data from available lidar surveys 2000-2018. For more infomation regarding lidar shorelines for Georgia and Florida, see the shorelines metadata file associated with this dataset.
    Farris, A.S., Weber, K.M., Doran, K.S., and List, J.H., 2018, Comparing methods used by the U.S. Geological Survey Coastal and Marine Geology Program for deriving shoreline position from lidar data: U.S. Geological Survey Open-File Report 2018–1121, 13 p., https://doi.org/10.3133/ofr20181121
    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
    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
    384 Woods Hole Road
    Woods Hole, MA
    US

    508-548-8700 x2344 (voice)
    508-457-2310 (FAX)
    afarris@usgs.gov
    Date: 2020 (process 2 of 11)
    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, since this is usually impossible, the PDB is estimated by averaging all available slope data (generated in the previous process step) and averaging at least 10 years of historical wave data from a nearby buoy (https://www.ndbc.noaa.gov/) and the Wave Information Study (WIS) (https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00071). The PDB is stored to a point shapefile at the intersection of the each profile with the coast-following reference line.
    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
    384 Woods Hole Road
    Woods Hole, MA
    US

    508-548-8700 x2344 (voice)
    508-457-2310 (FAX)
    afarris@usgs.gov
    Date: 2020 (process 3 of 11)
    In order 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 detail how a series of transects are created to transfer the bias data from the bias points to a copy of the baseline. The following process steps were performed by the same person, Rachel E. Henderson. Person who carried out this activity:
    U.S. Geological Survey
    Attn: Rachel E. Henderson
    384 Woods Hole Road
    Woods Hole, MA
    USA

    508-548-8700 (voice)
    508-457-2310 (FAX)
    rehenderson@contractor.usgs.gov
    Date: 2020 (process 4 of 11)
    A personal geodatabase was created and the baseline and sample shorelines for the project area were added. Using DSAS v5.1, the default parameters were set for a midshore baseline. Transects were cast using a 20-meter spacing, a search distance of 1000 meters and smoothing distance of 2000 meters. 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: 2020 (process 5 of 11)
    The data from the original bias points were transferred to the transects using the tool "Spatial Join" in ArcToolbox v10.6 > Analysis Tools > Overlay > Spatial Join). The resulting Bias_transect file contains all the original bias information. The Bias_transect file is then converted to a point file (midpoint) using the tool "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 midpoints intersect the baseline. The resulting Bias_midpoint file 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: 2020 (process 6 of 11)
    A copy of the baseline was created and split into 20-meter increments to match the same spacing of the Bias_midpoint feature. Points along the original baseline were created using the tool "Generate Points along Lines" at a distance of 20 meters. Then the ArcCatalog v10.6 tool "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: 2020 (process 7 of 11)
    The data from Bias_midpoint were transferred to the new baseline Feature_20m, using the tool "Spatial Join" (ArcToolbox v10.6 > 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: 2020 (process 8 of 11)
    The "Unsplit Line" tool (ArcToolbox v10.6 > 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 the resultant bias feature. The final bias feature shapefile holds the bias value and the bias uncertainty. These components are used by the DSAS v5.1 software to apply the proxy-datum bias correction during shoreline change calculations. Data sources used in this process:
    • Feature_Wbias
    Data sources produced in this process:
    • Bias_Feature
    Date: 2020 (process 9 of 11)
    The bias feature was imported into a personal geodatabase in ArcCatalog v10.7 by right-clicking on the geodatabase > Import > Feature class (single). This process step and all subsequent process steps were performed by the same person - Meredith G. Kratzmann Person who carried out this activity:
    Meredith G. Kratzmann
    U.S. Geological Survey
    384 Woods Hole Road
    Woods Hole, MA
    USA

    508-548-8700 (voice)
    508-457-2310 (FAX)
    mkratzmann@contractor.usgs.gov
    Date: 2021 (process 10 of 11)
    The bias feature (GA_bias) was projected in ArcToolbox v10.7 > Data Management Tools > Projections and Transformations > Project. parameters: input projection - UTM zone 17N (WGS 84); output projection- geographic coordinates (WGS 84); transformation = none.
    Date: 27-Apr-2022 (process 11 of 11)
    Updated the cross-reference information with regards to the related Data Report (20220427). The metadata available from a harvester may supersede metadata bundled with the dataset. Compare the metadata dates to determine which metadata file is most recent. Person who carried out this activity:
    U.S. Geological Survey
    Attn: VeeAnn A. Cross
    384 Woods Hole Road
    Woods Hole, MA
    USA

    (508) 548-8700 x2251 (voice)
    508-457-2310 (FAX)
    vatnipp@usgs.gov
  3. What similar or related data should the user be aware of?
    Kratzmann, Meredith G., 2022, U.S. Geological Survey National Shoreline Change: Summary Statistics for Updated Vector Shorelines (1800s - 2010s) and Associated Shoreline Change Data for the Georgia and Florida Coasts: Data Report 1156, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Data Report associated with this data release: Kratzmann, M.G., Farris, A.S., Weber, K.M., Henderson, R.E., and Himmelstoss, E.A., 2021, USGS national shoreline change-A GIS compilation of updated vector shorelines (1800s - 2010s) and associated shoreline change data for the Georgia and Florida Coasts: U.S. Geological Survey data release, https://doi.org/10.5066/P9J3CVN4.
    Himmelstoss, Emily A., Farris, Amy S., Henderson, Rachel E., Kratzmann, Meredith G., Ergul, Ayhan, Zhang, Ouya, and Zichichi, Jessica L., 2018, Digital Shoreline Analysis System (version 5): U.S. Geological Survey Software: software release version 5, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details: Current version of software at time of use was 5.1
    Himmelstoss, E.A., Henderson, R.E., Kratzmann, M.G., and Farris, A., 2018, Digital Shoreline Analysis System (DSAS) Version 5 User Guide: Open File Report 2018-1179, U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole, MA.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Himmelstoss, E.A., Henderson, R.E., Kratzmann, M, Farris, A., 2018, DSAS version 5 user guide. U.S. Geological Survey report 2018-1179, https://doi.org/10.3133/ofr20181179
    Himmelstoss, Emily, Kratzmann, Meredith, 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, Kratzmann, Meredith, and Thieler, E. Robert, 2017, National Assessment of Shoreline Change: A GIS compilation of Updated Vector Shorelines and Associated Shoreline Change Data for the Gulf of Mexico Coast: Data release doi:10.5066/F78P5XNK, U.S. Geological Survey, Reston, VA.

    Online Links:

    Himmelstoss, Emily, Kratzmann, Meredith, 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:

    Morton, Robert A., and Miller, Tara L., 2005, National Assessment of Shoreline Change: Part 2 Historical Shoreline Changes and Associated Coastal Land Loss along the U.S. Southeast Atlantic Coast: Open-File Report 2005-1401, U.S. Geological Survey, Reston, VA.

    Online Links:

    Miller, Tara L., Morton, Robert A., and Sallenger, Asbury H., 2005, The National Assessment of Shoreline Change: A GIS Compilation of Vector Shorelines and Associated Shoreline Change Data for the U.S. Southeast Atlantic Coast: Open-File Report 2005-1326, U.S. Geological Survey, Reston, VA.

    Online Links:

    Morton, Robert A., Miller, Tara L., and Moore, Laura J., 2004, National Assessment of Shoreline Change: Part 1 Historical Shoreline Changes and Associated Coastal Land Loss along the U.S. Gulf of Mexico: Open-File Report 2004-1043, U.S. Geological Survey, Reston, VA.

    Online Links:

    Miller, Tara L., Morton, Robert A., Sallenger, Asbury H., and Moore, Laura J., 2004, The National Assessment of Shoreline Change: A GIS Compilation of Vector Shorelines and Associated Shoreline Change Data for the U.S. Gulf of Mexico: Open-File Report 2004-1089, 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, n/a.

    Online Links:

    Other_Citation_Details: pp. 1069-1081
    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:

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 proxy-datum offsets calculated from averaged slope data (2000-2018) 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 baseline. The baseline serves as a reference point for transects cast by the Digital Shoreline Analysis System (DSAS) software which does 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 bias feature file is complete and contains data used to apply the proxy-datum bias when calculating shoreline change rates in DSAS v5.
  5. How consistent are the relationships among the observations, including topology?
    Each line segment has a unique identification attribute (OBJECTID). The bias feature contains bias values and uncertainty of the bias values where lidar data were available.

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 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. 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 - GS 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 baselines used for the analysis of shoreline data (SHP and other shapefile components), browse graphic, and the FGDC CSDGM metadata.
  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?
  5. What hardware or software do I need in order to use the data set?
    These data are available in a polyline shapefile format. The user must have software to read and process the data components of a shapefile.

Who wrote the metadata?

Dates:
Last modified: 19-Mar-2024
Metadata author:
Meredith G. Kratzmann
U.S. Geological Survey
384 Woods Hole Road
Woods Hole, MA
USA

508-548-8700 (voice)
508-457-2310 (FAX)
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. (updated on 20240319)
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_P9J3CVN4/GA_bias_metadata.faq.html>
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