Meredith G. Kratzmann Amy S. Farris 20260622 1.0 vector digital data data release DOI:10.5066/P1JE2KSO Woods Hole Coastal and Marine Science Center, Woods Hole, MA U.S. Geological Survey, Coastal and Marine Hazards and Resources Program https://doi.org/10.5066/P1JE2KSO https://www.sciencebase.gov/catalog/item/69e2b0f0b66b0195694c11f1 Meredith G. Kratzmann Amy S. Farris Kathryn M. Weber 2026 1.0 vector digital data data release DOI:10.5066/P1JE2KSO Reston, VA U.S. Geological Survey 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. https://doi.org/10.5066/P1JE2KSO https://www.sciencebase.gov/catalog/item/69e2a7d5b66b0195694c1197 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. 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. 2026 ground condition Complete None planned -88.350587 -87.517445 30.278659 30.216387 ISO 19115 Topic Category oceans environment geoscientificInformation None Shoreline change Digital Shoreline Analysis System DSAS U.S. Geological Survey USGS Coastal and Marine Geology Program CMGP Woods Hole Coastal and Marine Science Center WHCMSC Linear Regression Rate LRR High Water Line HWL Mean High Water MHW proxy-datum bias PDB Bias feature Bias USGS Thesaurus geospatial datasets coastal processes USGS Metadata Identifier USGS:69e2b0f0b66b0195694c11f1 GNIS State of Alabama Dauphin Island Fort Morgan Alabama Gulf Shores None Gulf Coast Bon Secour National Wildlife Refuge United States of America North America No access constraints. Please see 'Distribution Information' for details. 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. U.S. Geological Survey Meredith G. Kratzmann mailing and physical

384 Woods Hole Road

Woods Hole MA 02543-1598 USA 508-548-8700 508-457-2310 mkratzmann@contractor.usgs.gov https://www.sciencebase.gov/catalog/file/get/69e2b0f0b66b0195694c11f1?name=AL_bias.png&allowOpen=true Map view of data. Orange line indicates extent of the bias feature for Alabama. PNG Microsoft Windows 11 Enterprise; Esri ArcGIS Pro 3.5.5 Rachel E. Henderson Amy S. Farris Meredith G. Kratzmann Marie K. Bartlett Ayhan Ergul John McAndrews Raison Cibaj Jessica L. Zichichi Emily A. Himmelstoss E. Robert Thieler 2026 publication software release version 6.1.177 Reston, VA U.S. Geological Survey 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. https://doi.org/10.5066/P1NHMJNC https://code.usgs.gov/cch/dsas https://www.usgs.gov/centers/whcmsc/science/digital-shoreline-analysis-system-dsas Peter Ruggiero Jeffrey H. List 200909 publication Journal of Coastal Research vol. 255 n/a Coastal Education and Research Foundation pp. 1069-1081 https://doi.org/10.2112/08-1051.1 Amy S. Farris Kathryn M. Weber Kara S. Doran Jeffrey H. List 2018 Open-File Report 2018–1121 Reston, VA U.S. Geological Survey https://doi.org/10.3133/ofr20181121 Hillary F. Stockdon Asbury H. Sallenger Jeffrey H. List Rob A. Holman 2002 publication Journal of Coastal Research vol. 18 Woods Hole, MA U.S. Geological Survey https://www.jstor.org/stable/4299097 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). The bias feature polyline is a copy of the Alabama baseline that is split into segments containing PDB data (see process steps for details). The bias feature is complete and contains data necessary to apply the proxy-datum bias when calculating shoreline change rates in DSAS v6.1. 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. Meredith G. Kratzmann 2026 1.0 vector digital data data release DOI:10.5066/P1JE2KSO Woods Hole Coastal and Marine Science Center, Woods Hole, MA U.S. Geological Survey The first link is to the larger work, the second link is to the baseline dataset. https://doi.org/10.5066/P1JE2KSO https://www.sciencebase.gov/catalog/item/69e2afc2b66b0195694c11e3 digital data 2026 publication date AL_baseline Baseline segments for Alabama (part of this same data release https://doi.org/10.5066/P1JE2KSO) are used by DSAS to cast measurement transects. NOAA Office for Coastal Management Partners 2026 vector digital dataset Charleston, SC Office for Coastal Management Point cloud data were downloaded for Alabama. Projection = NAD_1983_2011_UTM_Zone_16N. Data accessed and downloaded in 08/2025 and 09/2025. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=1064 https://www.fisheries.noaa.gov/inport/item/50083 digital data 201001 201003 ground condition 2010 AL lidar Point cloud data used to extract the 2010 MHW shoreline position and calculate slope. NOAA Office for Coastal Management Partners 2026 vector digital dataset Charleston, SC Office for Coastal Management Point cloud data were downloaded for Alabama. Projection = NAD_1983_2011_UTM_Zone_16N. Data accessed and downloaded in 06/2025. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=5186 https://www.fisheries.noaa.gov/inport/item/49738 digital data 20160723 20161010 ground condition 2016 AL lidar Point cloud data used to extract the 2016 MHW shoreline position and calculate slope. NOAA Office for Coastal Management Partners 2026 vector digital dataset Charleston, SC Office for Coastal Management Point cloud data were downloaded for Alabama. Projection = NAD_1983_2011_UTM_Zone_16N. Data accessed and downloaded in 08/2025. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=10314 https://www.fisheries.noaa.gov/inport/item/75435 digital data 20220717 20220719 ground condition 2022 AL lidar Point cloud data used to extract the 2022 MHW shoreline position and calculate slope. National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) unknown data viewer Stennis Space Center, MS National Oceanic and Atmospheric Administration https://www.ndbc.noaa.gov/ digital data 2010 2022 ground condition Buoy data Buoy data used for processing lidar shorelines extracted using the profile method and calculating the proxy-datum bias for Alabama. National Oceanic and Atmospheric Administration (NOAA) unknown data viewer Silver Spring, MD National Centers for Environmental Information, NOAA, U.S. Department of Commerce https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00071 https://www.ncei.noaa.gov/ digital data 2010 2022 ground condition WIS data 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. Rachel E. Henderson Amy S. Farris Meredith G. Kratzmann Marie K. Bartlett Ayhan Ergul John McAndrews Raison Cibaj Jessica L. Zichichi Emily A. Himmelstoss E. Robert Thieler 2026 publication Reston, VA U.S. Geological Survey https://doi.org/10.5066/P1NHMJNC https://code.usgs.gov/cch/dsas https://www.usgs.gov/centers/whcmsc/science/digital-shoreline-analysis-system-dsas software 2026 2026 publication date DSAS v6.1 Software used to cast temporary transects for the purpose of creating the bias feature for Alabama. 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. 2010 AL lidar 2016 AL lidar 2022 AL lidar 2025 Average slope data U.S. Geological Survey Amy S. Farris mailing and physical

384 Woods Hole Road

Woods Hole MA 02543 US 508-548-8700 x2344 508-457-2310 afarris@usgs.gov 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. Buoy data WIS data Average slope data 2025 Bias points U.S. Geological Survey Amy S. Farris Oceanographer mailing and physical

384 Woods Hole Road

Woods Hole MA 02543-1598 US 508-548-8700 x2344 508-457-2310 afarris@usgs.gov 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. DSAS v6.1 2026 20-meter transects U.S. Geological Survey Meredith Kratzmann Mailing and Physical

384 Woods Hole Road

Woods Hole MA 02543 508-548-8700 508-457-2310 mkratzmann@contractor.usgs.gov 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. AL_baseline 2026 baseline20m 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. 20-meter transects Bias points 2026 trans_bias_PT 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. baseline20m trans_bias_PT 2026 AL_bias 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. 2026 Vector String 84 0.0000001 0.0000001 Decimal degrees WGS_1984 WGS_84 6378137.0 298.257223563 AL_bias.shp Proxy-datum bias and uncertainty values for the Alabama coastal region. U.S. Geological Survey FID Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Feature geometry. 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. U.S. Geological Survey 4.33 5.99 meters bias_uncy The plus/minus horizontal uncertainty (meters) in the lidar shoreline position at each cross-shore beach profile. U.S. Geological Survey 2.24 3.62 meters id A unique identification number for each segment. U.S. Geological Survey 1 84 meters 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. U.S. Geological Survey U.S. Geological Survey - GS ScienceBase mailing address

Denver Federal Center, Building 810, Mail Stop 302

Denver CO 80225 United States 1-888-275-8747 sciencebase@usgs.gov 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. 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. Shapefile Esri ArcGIS Pro 3.5.5 Esri polyline shapefile These files (.cpg, .dbf, .prj, .sbn, .sbx, .shp, .html, and .shx) are a collection of files with a common filename prefix and must be downloaded and stored in the same directory. Together they are the components of the shapefile and include FGDC CSDGM-compliant metadata in HTML format. Unzip 0.068 https://doi.org/10.5066/P1JE2KSO https://www.sciencebase.gov/catalog/item/69e2b0f0b66b0195694c11f1 https://www.sciencebase.gov/catalog/file/get/69e2b0f0b66b0195694c11f1 The first link is to the USGS publication page, the second link is to the dataset page, and the third link downloads the data. None These data are available in a polyline shapefile format. The user must have software to read and process the data components of a shapefile. 20260622 Meredith G. Kratzmann U.S. Geological Survey mailing and physical

384 Woods Hole Road

Woods Hole MA 02543-1598 USA 508-548-8700 508-457-2310 whsc_data_contact@usgs.gov The metadata contact email address is a generic address in the event the person is no longer with USGS. FGDC Content Standards for Digital Geospatial Metadata FGDC-STD-001-1998 local time