Alabama: bias feature containing proxy-datum bias information used in shoreline change rate calculations

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Frequently anticipated questions:

What does this data set describe?

Title:
Alabama: bias feature containing proxy-datum bias information used in shoreline change rate calculations
Abstract:
The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from various historical sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. Shorelines are compiled in a Geographic Information System (GIS) and analyzed in the USGS Digital Shoreline Analysis System (DSAS) software to calculate rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers understand which areas of the coast are vulnerable to change. The shoreline positions and shoreline change rates provide actionable information to homeowners, coastal communities, and managers of public and private properties to improve resiliency for coastal hazards.
  1. How might this data set be cited?
    Kratzmann, Meredith G., and Farris, Amy S., 20260622, Alabama: bias feature containing proxy-datum bias information used in shoreline change rate calculations: data release DOI:10.5066/P1JE2KSO, 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., and Weber, Kathryn M., 2026, National Shoreline Change—A GIS compilation of vector shorelines and associated shoreline change data from the 1800s to the 2020s for the coast of Alabama: data release DOI:10.5066/P1JE2KSO, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    suggested citation: Kratzmann, M.G., Farris, A.S., and Weber, K.M., 2026, National Shoreline Change—A GIS compilation of vector shorelines and associated shoreline change data from the 1800s to the 2020s for the coast of Alabama: U.S. Geological Survey data release, https://doi.org/10.5066/P1JE2KSO.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -88.350587
    East_Bounding_Coordinate: -87.517445
    North_Bounding_Coordinate: 30.278659
    South_Bounding_Coordinate: 30.216387
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/69e2b0f0b66b0195694c11f1?name=AL_bias.png&allowOpen=true (PNG)
    Map view of data. Orange line indicates extent of the bias feature for Alabama.
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 2026
    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 (84)
    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 0.0000001. Longitudes are given to the nearest 0.0000001. Latitude and longitude values are specified in Decimal degrees. 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?
    AL_bias.shp
    Proxy-datum bias and uncertainty values for the Alabama coastal region. (Source: U.S. Geological Survey)
    FID
    Internal feature number. (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Shape
    Feature geometry. (Source: Esri) Coordinates defining the features.
    bias
    The proxy-datum bias value describing the unidirectional horizontal offset (in meters) between MHW elevation and HWL shoreline positions. The average value for AL is 4.73 meters. (Source: U.S. Geological Survey)
    Range of values
    Minimum:4.33
    Maximum:5.99
    Units:meters
    bias_uncy
    The plus/minus horizontal uncertainty (meters) in the lidar shoreline position at each cross-shore beach profile. (Source: U.S. Geological Survey)
    Range of values
    Minimum:2.24
    Maximum:3.62
    Units:meters
    id
    A unique identification number for each segment. (Source: U.S. Geological Survey)
    Range of values
    Minimum:1
    Maximum:84
    Units:meters
    Entity_and_Attribute_Overview:
    The entity and attribute information provided here describes the tabular data associated with the bias feature for Alabama. 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)
    • Meredith G. Kratzmann
    • Amy S. Farris
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    U.S. Geological Survey
    Attn: Meredith G. Kratzmann
    384 Woods Hole Road
    Woods Hole, MA
    USA

    508-548-8700 (voice)
    508-457-2310 (FAX)

Why was the data set created?

Shoreline positions from the mid-1800s through the 2020s were used to calculate shoreline change rates for Alabama using the Digital Shoreline Analysis System v6.1 software. The shorelines dataset contains a combination of proxy-based (e.g., high water line) and datum-based (e.g., mean high water) shorelines. The bias feature is a polyline shapefile to be used in DSAS and is a representation of the proxy-datum bias (PDB) with bias uncertainty values. These PDB data are used to reconcile the offset between proxy- and datum-based shorelines so they can be directly compared when calculating shoreline change rates.

How was the data set created?

  1. From what previous works were the data drawn?
    AL_baseline (source 1 of 7)
    Kratzmann, Meredith G., 2026, Alabama: baseline generated to calculate shoreline change rates in Kratzmann, M.G., Farris, A.S., and Weber, K.M., 2026, National Shoreline Change—A GIS compilation of vector shorelines and associated shoreline change data from the 1800s to the 2020s for the coast of Alabama: U.S. Geological Survey data release, https://doi.org/10.5066/P1JE2KSO: data release DOI:10.5066/P1JE2KSO, U.S. Geological Survey, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

    Other_Citation_Details:
    The first link is to the larger work, the second link is to the baseline dataset.
    Type_of_Source_Media: digital data
    Source_Contribution:
    Baseline segments for Alabama (part of this same data release https://doi.org/10.5066/P1JE2KSO) are used by DSAS to cast measurement transects.
    2010 AL lidar (source 2 of 7)
    NOAA Office for Coastal Management Partners, 2026, 2010 USACE NCMP Topobathy Lidar: Gulf Coast (AL, FL): Office for Coastal Management, Charleston, SC.

    Online Links:

    Other_Citation_Details:
    Point cloud data were downloaded for Alabama. Projection = NAD_1983_2011_UTM_Zone_16N. Data accessed and downloaded in 08/2025 and 09/2025.
    Type_of_Source_Media: digital data
    Source_Contribution:
    Point cloud data used to extract the 2010 MHW shoreline position and calculate slope.
    2016 AL lidar (source 3 of 7)
    NOAA Office for Coastal Management Partners, 2026, 2016 USACE NCMP Topobathy Lidar: Gulf Coast (AL, FL, MS, TX): Office for Coastal Management, Charleston, SC.

    Online Links:

    Other_Citation_Details:
    Point cloud data were downloaded for Alabama. Projection = NAD_1983_2011_UTM_Zone_16N. Data accessed and downloaded in 06/2025.
    Type_of_Source_Media: digital data
    Source_Contribution:
    Point cloud data used to extract the 2016 MHW shoreline position and calculate slope.
    2022 AL lidar (source 4 of 7)
    NOAA Office for Coastal Management Partners, 2026, 2022 USACE NCMP Topobathy Lidar: Gulf Coast (AL, FL, MS): Office for Coastal Management, Charleston, SC.

    Online Links:

    Other_Citation_Details:
    Point cloud data were downloaded for Alabama. Projection = NAD_1983_2011_UTM_Zone_16N. Data accessed and downloaded in 08/2025.
    Type_of_Source_Media: digital data
    Source_Contribution:
    Point cloud data used to extract the 2022 MHW shoreline position and calculate slope.
    Buoy data (source 5 of 7)
    National Oceanic and Atmospheric Administration (NOAA), and National Weather Service (NWS), unknown, National Data Buoy Center: National Oceanic and Atmospheric Administration, Stennis Space Center, MS.

    Online Links:

    Type_of_Source_Media: digital data
    Source_Contribution:
    Buoy data used for processing lidar shorelines extracted using the profile method and calculating the proxy-datum bias for Alabama.
    WIS data (source 6 of 7)
    National Oceanic and Atmospheric Administration (NOAA), unknown, U.S. Wave Information Study (WIS): National Centers for Environmental Information, NOAA, U.S. Department of Commerce, Silver Spring, MD.

    Online Links:

    Type_of_Source_Media: digital data
    Source_Contribution:
    The WIS project produced an online database of hindcast, nearshore wave conditions covering U.S. coasts. Data used for calculating the proxy-datum bias for Alabama.
    DSAS v6.1 (source 7 of 7)
    Henderson, Rachel E., Farris, Amy S., Kratzmann, Meredith G., Bartlett, Marie K., Ergul, Ayhan, McAndrews, John, Cibaj, Raison, Zichichi, Jessica L., Himmelstoss, Emily A., and Thieler, E. Robert, 2026, Digital Shoreline Analysis System version 6.1: U.S. Geological Survey, Reston, VA.

    Online Links:

    Type_of_Source_Media: software
    Source_Contribution:
    Software used to cast temporary transects for the purpose of creating the bias feature for Alabama.
  2. How were the data generated, processed, and modified?
    Date: 2025 (process 1 of 7)
    Bias feature creation step 1: COLLECTING SLOPE DATA FROM POINT CLOUD LIDAR DATA. The proxy-datum bias calculation is made possible by utilizing data acquired during processing for the profile method of shoreline extraction similar to the one developed by Stockdon and others (2002). The method extracts an elevation-based shoreline from point cloud lidar data using a Matlab-based approach (Matlab version R2024A). Using a coast-following reference line with 20-m-spaced cross shore profiles, lidar data are 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 at each profile. For Alabama, slope and uncertainty were averaged using the lidar dataset years 2010, 2016 and 2022, where available. 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)
    Data sources used in this process:
    • 2010 AL lidar
    • 2016 AL lidar
    • 2022 AL lidar
    Data sources produced in this process:
    • Average slope data
    Date: 2025 (process 2 of 7)
    Bias feature creation step 2: CALCULATING THE PROXY-DATUM BIAS. There is a known horizontal offset between datum-based (MHW) shorelines and proxy-based (HWL) 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 or "bias"). 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 and averaging at least 10 years of historical wave data from a nearby buoy (National Data Buoy Center) and the U.S. Wave Information Study (WIS). The resulting bias and bias uncertainty information is stored in a shapefile as points at the intersection of each profile and the coast-following reference line. 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)
    Data sources used in this process:
    • Buoy data
    • WIS data
    • Average slope data
    Data sources produced in this process:
    • Bias points
    Date: 2026 (process 3 of 7)
    Bias feature creation step 3: TRANSECTS CAST TO CONNECT BIAS POINTS AND BASELINE. In order to be used in DSAS, data from the bias points must be connected to a shapefile that is near or coincident with the baseline. However, the bias points that result from the lidar shoreline extraction process (steps 1 and 2) do not always fall near the baseline. Transects were created for the sole purpose of connecting the bias points to the baseline. Transects were cast using DSAS v6.1 at 20-meter spacing, length= 1200 meters, smoothing value= 2000 meters. Transects were exported from DSAS and evaluated with the bias points in ArcGIS Pro v3.5.5 to ensure the transects were long enough.
    This and the following process steps were performed by the same person: Meredith Kratzmann. Person who carried out this activity:
    U.S. Geological Survey
    Attn: Meredith Kratzmann
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 (voice)
    508-457-2310 (FAX)
    Data sources used in this process:
    • DSAS v6.1
    Data sources produced in this process:
    • 20-meter transects
    Date: 2026 (process 4 of 7)
    Bias feature creation step 4: SPLIT BASELINE. In ArcGIS Pro v3.5.5, points were established along the baseline by a distance of 20 meters using the geoprocessing tool: Data Management Tools > Sampling > Generate Points Along Lines. Then, the baseline was split at those points using the tool: Data Management Tools > Features > Split Line at Point. Data sources used in this process:
    • AL_baseline
    Data sources produced in this process:
    • baseline20m
    Date: 2026 (process 5 of 7)
    Bias feature creation step 5: JOIN BIAS POINTS TO TRANSECTS. In ArcGIS Pro v3.5.5, bias points were joined to transects using the geoprocessing tool: Analysis Tools > Overlay > Spatial Join. Then, the transects that now have the bias were converted to points (midpoint) using the tool: Data Management Tools > Features > Feature Vertices To Points. Data sources used in this process:
    • 20-meter transects
    • Bias points
    Data sources produced in this process:
    • trans_bias_PT
    Date: 2026 (process 6 of 7)
    Bias feature creation step 6: CREATE BIAS FEATURE POLYLINE. In ArcGIS Pro v3.5.5, the transect bias points generated in process step 5 were joined to the baseline split into 20-meter segments (process step 4) using the geoprocessing tool: Analysis Tools > Overlay > Spatial Join. Then, the split line that now has bias data was unsplit using the tool: Data Management Tools > Features > Unsplit Line. The resultant file is the bias feature that was renamed and used in the long-term shoreline change rate calculations for Alabama. Data sources used in this process:
    • baseline20m
    • trans_bias_PT
    Data sources produced in this process:
    • AL_bias
    Date: 2026 (process 7 of 7)
    The baseline shapefile was projected in ArcGIS Pro v3.5.5 > Geoprocessing > Data Management Tools > Projections and Transformations > Project. Parameters: Input Coordinate System - NAD_1983_2011_UTM_Zone_16N; Output Coordinate System - GCS_WGS_1984; transformation = WGS_1984_(ITRF08)_To_NAD_1983_2011.
  3. What similar or related data should the user be aware of?
    Henderson, Rachel E., Farris, Amy S., Kratzmann, Meredith G., Bartlett, Marie K., Ergul, Ayhan, McAndrews, John, Cibaj, Raison, Zichichi, Jessica L., Himmelstoss, Emily A., and Thieler, E. Robert, 2026, Digital Shoreline Analysis System version 6.1: software release version 6.1.177, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Use the first link to access the publication page. The second link is to the current version of DSAS (v6.1). The third link directs to the DSAS project page.
    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:

    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, U.S. Geological Survey, Woods Hole, MA.

    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 the bias feature shapefile record positional and measurement uncertainties and proxy-datum offsets calculated from averaged slope data and local wave data (see process steps for details). The field names are based on the requirements for use within DSAS. Attributes for each segment include the bias value (bias), bias uncertainty (bias_uncy), and a unique identification number (id).
  2. How accurate are the geographic locations?
    The horizontal location of the bias feature is coincident with the baseline which 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 bias feature is complete and contains data necessary to apply the proxy-datum bias when calculating shoreline change rates in DSAS v6.1.
  5. How consistent are the relationships among the observations, including topology?
    The bias feature polyline is a copy of the Alabama baseline that is split into segments containing PDB data (see process steps for details).

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints No access constraints. Please see 'Distribution Information' for details.
Use_Constraints These data are marked with a Creative Commons CC0 1.0 Universal License. These data are in the public domain and do not have any use constraints. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations. These data were automatically generated using the DSAS v6.1 software application. 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)
  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?
    Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (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.
  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: 22-Jun-2026
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)
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_P1JE2KSO/AL_bias_metadata.faq.html>
Generated by mp version 2.9.51 on Mon Jun 22 16:21:27 2026