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/69e2b013b66b0195694c11e7 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 compiled from existing and new sources are included in this dataset for Alabama from the 1800s to the 2020s. Alabama shorelines span 173 years ranging from 1849 to 2022 and were extracted from topographic survey sheets (T-sheets), aerial photographs, and lidar data. Source agencies include: USGS, National Oceanic and Atmospheric Administration (NOAA), U.S. Army Corps of Engineers (USACE), Mississippi Department of Environmental Quality, Office of Geology (MOG), University of South Alabama (USA), Florida Department of Environmental Protection (FLDEP), United States Department of Agriculture - Farm Service Agency Aerial Photography Field Office (USDA FSA APFO), Geological Survey of Alabama - Acquired from University of Alabama's Cartographic Research Laboratory (GSA/UA), USGS Earth Resources Observation and Science Center (USGS EROS), National Aeronautics and Space Administration (NASA), and National Park Service (NPS). In this release, nine new tidal datum-based mean high water (MHW) shorelines extracted from 1998, 2005, 2007, 2010, 2015, 2016, 2018, 2020, and 2022 lidar elevation data were used in the analysis (coverage not necessarily continuous statewide). Historical shoreline positions serve as easily understood features that can be used to describe the movement of beaches through time. Long-term (LT) century-scale and short-term (ST) decadal-scale shoreline change rates were generated using the Digital Shoreline Analysis System (DSAS) version 6.1. DSAS uses a measurement baseline method to calculate rate-of-change statistics. Transects are cast from the reference baseline to intersect each shoreline, establishing measurement points used to calculate shoreline change rates. 1849 2022 ground condition Complete None planned -88.345344 -87.518313 30.285429 30.219182 ISO 19115 Topic Category geoscientificInformation oceans environment None Shoreline Shoreline change Digital Shoreline Analysis System DSAS U.S. Geological Survey USGS Coastal and Marine Hazards and Resources Program CMHRP Woods Hole Coastal and Marine Science Center WHCMSC Mean High Water MHW High Water Line HWL Wet-Dry Line WDL Topographic Survey Sheet T-sheet USGS thesaurus geospatial datasets coastal processes aerial photography lidar digital elevation models USGS Metadata Identifier USGS:69e2b013b66b0195694c11e7 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. 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/69e2b013b66b0195694c11e7?name=AL_shorelines.png&allowOpen=true Map view of data. Blue lines indicate the extent of the shoreline data in 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 suggested citation: 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 https://doi.org/10.3133/ofr20181121 Kathryn M. Weber Jeffrey H. List Karen L.M. Morgan 2005 Open-File Report 2005-1027 Reston, VA U.S. Geological Survey https://doi.org/10.3133/ofr20051027 The data provided here are a compilation of shorelines from multiple sources, spanning 173 years. The attributes are based on the requirements of the Digital Shoreline Analysis System (DSAS) software and have gone through a series of quality assurance procedures. Adjacent shoreline segments do not overlap and are not necessarily continuous. Shorelines were quality checked for accuracy. Any slight offsets between adjacent segments due to georeferencing and digitizing error are taken into account in the uncertainty of the shoreline position, as reported in the horizontal accuracy section of this metadata file. This shoreline file is complete and contains all shoreline segments used to calculate shoreline change rates along sections of the Alabama coastal region where shoreline position data were available. These data adequately represented the shoreline position at the time of the survey. Gaps in these data, if applicable, are a consequence of non-existing data or existing data that did not meet quality assurance standards. The horizontal accuracy of the shoreline data varies with respect to the data source from which the shorelines were digitized, the lidar data from which the shorelines were extracted, the time period, and the method used to extract the shoreline data. T-sheet Shoreline Positional Uncertainty: Shorelines prior to 1960 (T-sheets) have an estimated positional uncertainty of plus or minus 10.8 meters (m). Shorelines from the 1960s-1980s (T-sheets) have an estimated positional uncertainty of plus or minus 5.1 m. Contour Shoreline Positional Uncertainty: Four sources of uncertainty were accounted for regarding shorelines extracted using the contour method (described in Farris and others, 2018): 1) The vertical uncertainty of the lidar data (0.15 - 0.29 m) as found in the original lidar source metadata; 2) the horizontal uncertainty of the lidar data (0.12 - 1.0 m) as found in the original lidar source metadata; 3) a mean high water (MHW) vertical uncertainty of 0.15 m (Weber and others, 2005); and 4) a horizontal uncertainty due to the creation of a Digital Elevation Model (DEM) from lidar point cloud data (0.5 m). The vertical uncertainty values (1 and 3 above) were converted to a horizontal uncertainty using the beach slope in order to calculate uncertainty by summation in quadrature of horizontal components. The beach slope was found by averaging slope values calculated from the lidar profile shorelines (see process steps for a description). Vertical uncertainty (VU) terms were divided by the average beach slope (expressed as rise/run) in order to get the horizontal component of the two vertical uncertainty terms: VU/TAN(slope*(3.14159/180)). In order to estimate the total horizontal uncertainty, the four horizontal components of uncertainty were added in quadrature (square root of the sum of the squares). These values are stored in the attribute table as Uncy. The average uncertainty, in meters, for the contour shorelines are as follows: AL 1998 = 3.01 m AL 2005 = 3.49 m AL 2007 = 3.07 m AL 2010 = 3.27 m AL 2015 = 1.86 m AL 2016 = 2.08 m AL 2018 (USACE) = 1.98 m AL 2018 (USGS) = 1.72 m AL 2020 = 2.42 m AL 2022 = 1.98 m Profile shoreline extraction was completed for three lidar datasets (AL 2010, AL 2016 and AL 2022). Profile Shoreline Positional Uncertainty: Four sources of uncertainty were accounted for regarding shorelines extracted using the profile method (method described in Farris and others, 2018): 1) the 95% confidence interval on the linear regression estimate of the shoreline position; 2) the uncertainty associated with the elevation of the raw lidar data; 3) a 15 cm vertical error in our chosen value of MHW; and 4) the uncertainty due to extrapolation (if the shoreline was determined using extrapolation). These components of uncertainty were added in quadrature to yield a total error for each shoreline point. These errors were averaged for each profile shoreline segment (up to 2 kilometers). The range of uncertainty the profile shorelines used is 0.99 to 5.25 m, with an average of 2.83 m (AL 2010), 2.05 m (AL 2016), and 1.87 m (AL 2022). See the Uncy field in the shorelines attribute table for the individual uncertainty values of profile shoreline segments. Himmelstoss, E.A. Kratzmann, M.G. Thieler, E.R. 2017 publication data release DOI:10.5066/F78P5XNK Reston, VA U.S. Geological Survey Alabama shoreline data from DOI:10.5066/F78P5XNK https://doi.org/10.5066/F78P5XNK https://www.sciencebase.gov/catalog/item/582ca4a5e4b04d580bd378ec digital data 1849 2001 ground condition Historical shorelines 1849-2001 Historical shorelines (T-sheet-derived, for example) from this publication (DOI:10.5066/F78P5XNK, downloaded in 2025) were used in the shoreline change analysis. Henderson, R.E. Nelson, P.R. Long, J.W. Smith, C.G. 2017 publication data release DOI:10.5066/F7T43RB5 Reston, VA U.S. Geological Survey Dauphin Island, Alabama, shoreline data from DOI:10.5066/F7T43RB5 https://doi.org/10.5066/F7T43RB5 https://coastal.er.usgs.gov/data-release/doi-F7T43RB5/ digital data 1940 2015 ground condition Dauphin shorelines 1940-2015 MHW lidar shorelines (1998-2014) and WDL proxy shorelines (1940-2015) from this publication (DOI:10.5066/F7T43RB5, downloaded in 2025) were used in the Alabama shoreline change analysis. NOAA Office for Coastal Management 2022 vector digital dataset Charleston, SC Office for Coastal Management Point cloud data were downloaded for Alabama. Projection = NAD_1983_2011_UTM_Zone_16N. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=22 https://www.fisheries.noaa.gov/inport/item/48152 digital data 19981029 19981109 ground condition AL 1998 PTS The elevation data were downloaded as a point cloud (.laz) for extraction of datum-based shoreline (contour method). Data accessed and downloaded in 11/2025. NOAA Office for Coastal Management Partners 2022 vector digital dataset Charleston, SC Office for Coastal Management Point cloud data were downloaded for Alabama. Projection = NAD_1983_2011_UTM_Zone_16N. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=31 https://www.fisheries.noaa.gov/inport/item/50056 digital data 20051012 20051211 ground condition AL 2005 PTS The elevation data were downloaded as a point cloud (.laz) for extraction of datum-based shoreline (contour method). Data accessed and downloaded in 11/2025. NOAA Office for Coastal Management Partners 2022 vector digital dataset Charleston, SC Office for Coastal Management Point cloud data were downloaded for Alabama. Projection = NAD_1983_2011_UTM_Zone_16N. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=522 https://www.fisheries.noaa.gov/inport/item/50105 digital data 20070627 20070630 ground condition AL 2007 PTS The elevation data were downloaded as a point cloud (.laz) for extraction of datum-based shoreline (contour method). Data accessed and downloaded in 09/2025. 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. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=1064 https://www.fisheries.noaa.gov/inport/item/50083 digital data 201001 201003 ground condition AL 2010 PTS The elevation data were downloaded as a point cloud (.laz) for extraction of datum-based shoreline (profile and contour methods). Data accessed and downloaded in 08/2025 and 09/2025. NOAA Office for Coastal Management Partners 2026 vector digital dataset Charleston, SC Office for Coastal Management Point cloud data were downloaded for Dauphin Island, Alabama. Projection = NAD_1983_2011_UTM_Zone_16N. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=10143 https://www.fisheries.noaa.gov/inport/item/73667 digital data 20150118 20150213 ground condition AL 2015 PTS The elevation data were downloaded as a point cloud (.laz) for extraction of datum-based shoreline (contour method). Data accessed and downloaded in 09/2025. 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. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=5186 https://www.fisheries.noaa.gov/inport/item/49738 digital data 20160723 20161010 ground condition AL 2016 PTS The elevation data were downloaded as a point cloud (.laz) for extraction of datum-based shoreline (profile method). Data accessed and downloaded in 06/2025. NOAA Office for Coastal Management Partners 2026 raster digital dataset Charleston, SC Office for Coastal Management DEM data were downloaded for Alabama. Projection = NAD_1983_2011_UTM_Zone_16N. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=6371 https://www.fisheries.noaa.gov/inport/item/49427 digital data 20160723 20161010 ground condition AL 2016 DEM The elevation data were downloaded as DEM tiles for extraction of datum-based shoreline (contour method). Data accessed and downloaded in 09/2025. NOAA Office for Coastal Management Partners 2026 vector digital dataset Charleston, SC Office for Coastal Management Point cloud data were downloaded for Dauphin Island, Alabama. Projection = NAD_1983_2011_UTM_Zone_16N. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9117 https://www.fisheries.noaa.gov/inport/item/64345 digital data 20181027 20181103 ground condition AL 2018 PTS The elevation data were downloaded as a point cloud (.laz) for extraction of datum-based shoreline (contour method). Data accessed and downloaded in 09/2025. NOAA Office for Coastal Management Partners 2026 raster digital dataset Charleston, SC Office for Coastal Management DEM data were downloaded for mainland Alabama. Projection = NAD_1983_2011_UTM_Zone_16N. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=8668 https://www.fisheries.noaa.gov/inport/item/55862 digital data 20181030 20181030 ground condition AL 2018 DEM The elevation data were downloaded as DEM tiles for extraction of datum-based shoreline (contour method). Data accessed and downloaded in 07/2025. NOAA National Geodetic Survey 2026 raster digital dataset Charleston, SC Office for Coastal Management DEM data were downloaded for Alabama (Block 6, Time Frame 5). Alabama dataset date= 02/22/2020. Projection = NAD_1983_2011_UTM_Zone_16N. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9708 https://www.fisheries.noaa.gov/inport/item/69338 digital data 20191204 20200502 ground condition AL 2020 DEM The elevation data were downloaded as DEM tiles for extraction of datum-based shoreline (contour method). Data accessed and downloaded in 07/2025. 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. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=10314 https://www.fisheries.noaa.gov/inport/item/75435 digital data 20220717 20220719 ground condition AL 2022 PTS The elevation data were downloaded as a point cloud (.laz) for extraction of datum-based shoreline (profile method). Data accessed and downloaded in 08/2025. NOAA Office for Coastal Management Partners 2026 raster digital dataset Charleston, SC Office for Coastal Management DEM data were downloaded for Alabama (Time Frame 1). Projection = NAD_1983_2011_UTM_Zone_16N. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=10315 https://www.fisheries.noaa.gov/inport/item/75692 digital data 20220717 20220719 ground condition AL 2022 DEM The elevation data were downloaded as DEM tiles for extraction of datum-based shoreline (contour method). Data accessed and downloaded in 09/2025. Historical shoreline data for Alabama were downloaded from a previous USGS publication (DOI:10.5066/F78P5XNK) and underwent basic quality checks and minor edits to the attribute table. The historical data contain proxy-based shorelines that represent the high-water line (HWL) at the time of survey and include one datum-based lidar shoreline from 2001. DOI:10.5066/F78P5XNK shorelines 2025 Historical shorelines 1849-2001 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 Shoreline data for Dauphin Island, Alabama were downloaded from a previous USGS publication (DOI:10.5066/F7T43RB5) and underwent basic quality checks and minor edits to shorelines and attribute table. The data contain proxy-based shorelines that represent the wet-dry line (WDL) at the time of the aerial survey (1940-2015) and include datum-based mean high water (MHW) lidar shorelines from 1998-2014. DOI:10.5066/F7T43RB5 shorelines 2025 Dauphin shorelines 1940-2015 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 Overview of the methods used to extract shoreline features from lidar data for Alabama: In this data release, two methods of shoreline extraction from lidar were used: the contour method and the profile method. Both methods use the Mean High Water (MHW) elevation from Weber and others (2005) for shoreline extraction. Described in Farris and others (2018), the contour method extracts the elevation of average MHW value from DEM data using the ArcGIS Pro tool Contour List with the MHW value chosen as the contour. Also described in Farris and others (2018), the profile method produces a datum-based mean high water (MHW) shoreline. The profile method extracts the MHW shoreline point from the lidar point cloud data, using a cross shore transect in a MATLAB-based approach. Please see subsequent process steps for details. These shorelines are polyline shapefiles that may be referred to as "profile shorelines" or "contour shorelines" in this metadata document to distinguish extraction methods, but note they are both lidar-derived. 2025 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 The following information applies to Alabama shorelines extracted using the profile method for the years 2010, 2016, and 2022. The profile method is used to extract the operational MHW shoreline from lidar point cloud data utilizing a MATLAB-based approach (MATLAB version R2024A) and is described in Farris and others (2018). The profile method used a coast-following reference line with 20-meter spaced profiles. All lidar data points that were within 1 meter of each profile line were associated with that profile. All processing was done on the 2-meter-wide profiles, working on a single profile at a time. For each profile, a linear regression was fit through data points on the foreshore and the regression was evaluated at the MHW elevation to yield the cross-shore position of the MHW shoreline. If there was a data gap at MHW or if the MHW elevation was obscured by water points, the linear regression was simply extrapolated to the MHW elevation. For each profile, the foreshore beach slope was defined as the slope of the regression line. This slope information is combined for all surveys and used to calculate uncertainty for profile- and contour-derived shorelines. The uncertainty associated with profile shorelines is described in the Horizontal Positional Accuracy Report of this metadata file. AL 2010 PTS AL 2016 PTS AL 2022 PTS 2025 AL 2010 profile shoreline AL 2016 profile shoreline AL 2022 profile shoreline U.S. Geological Survey Amy S. Farris Mailing and Physical

384 Woods Hole Road

Woods Hole MA 02543 508-548-8700 508-457-2310 afarris@usgs.gov Profile shorelines were prepared for use in DSAS. Attribute fields were added using ArcGIS Pro tool Add Fields (multiple): Geoprocessing > Data Management Tools > Fields > Add Fields (multiple). Fields added: Date_ (text), Uncy (Float), Source (text), Source_b (text), Year_ (Short), Default_D (Short), DSAS_Type (text), STATE (text), SRCE_INFO (text), DEM (text), MHW_elev (Double), Slope_ (Float). See the Entity Attributes section of this metadata file for definitions. All profile shorelines for Alabama were then merged into a single file using the ArcGIS Pro tool Merge: Geoprocessing > Data Management Tools > General > Merge. This and the following steps were performed by the same person: Meredith Kratzmann. AL 2010 profile shoreline AL 2016 profile shoreline AL 2022 profile shoreline 2025 AL profile shorelines 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 An inventory was conducted to identify all available lidar datasets for Alabama that were not included in the previous USGS publications (DOI:10.5066/F78P5XNK; DOI:10.5066/F7T43RB5). Datasets that met quality assurance standards for this analysis were processed for extraction using the contour method (described in Farris and others, 2018). Contour shorelines that were extracted for Alabama include the years: 1998, 2005, 2007, 2010, 2015, 2016, 2018, 2020, and 2022. In some cases, contour shoreline segments were used to fill in gaps of a profile shoreline extracted from the same dataset to provide more complete coverage. 2025 Datasets that were available as DEMs were downloaded from the NOAA Digital Coast Data Access viewer (https://coast.noaa.gov/dataviewer/#/lidar/search/): Projection= UTM; Zone= 16N; Horizontal Datum= NAD83; Vertical Datum= NAVD88; Output format= Raster (GeoTIFF); DEM cell size= 1 meter. Workflow used to extract a contour shoreline from a DEM: 1) DEM loaded into ArcGIS Pro v.3.5.5 2) Created contour polyline using ArcGIS Pro tool Contour List: Geoprocessing > Spatial Analyst Tools > Surface > Contour List. Input raster= DEM; Output polyline features= contour shoreline; Contour value= MHW (Alabama = 0.23). 3) Output contour edited as necessary to capture open-ocean sandy shoreline by visually comparing the line to imagery within ArcGIS Pro. 4) Contour shoreline smoothed using ArcGIS Pro tool Smooth Line: Geoprocessing > Cartography Tools > Generalization > Smooth Line. Smoothing algorithm= Polynomial Approximation with Exponential Kernel (PAEK); Smoothing tolerance= 5 meters. 5) Attribute fields were added to the contour shoreline using ArcGIS Pro tool Add Fields (multiple): Geoprocessing > Data Management Tools > Fields > Add Fields (multiple). Fields added: Date_ (text), Uncy (Float), Source (text), Source_b (text), Year_ (Short), Default_D (Short), DSAS_Type (text), STATE (text), SRCE_INFO (text), DEM (text), MHW_elev (Double), Slope_ (Float). See the Entity Attributes section of this metadata file for definitions. AL 2016 DEM AL 2018 DEM AL 2020 DEM AL 2022 DEM 2025 AL 2016 contour shoreline AL 2018 contour shoreline USACE AL 2020 contour shoreline AL 2022 contour shoreline Datasets that were not available as DEMs were downloaded as lidar point cloud files in Lidar Aerial Survey (LAS) format compressed to a ZIP format (LAZ) from the NOAA Digital Coast Data Access viewer (https://coast.noaa.gov/dataviewer/#/lidar/search/): Projection= UTM; Zone= 16N; Horizontal Datum= NAD83; Vertical Datum= NAVD88; Geoid= GEOID18; Output format= Points - LAZ; Data classes= Ground; Return Types= Any. The point cloud was used to create a DEM. 1) In ArcGIS Pro v.3.5.5, LAZ files were decompressed using the Convert LAS tool: Geoprocessing > Conversion Tools > Point Cloud > Convert LAS. Compression= No compression; File version= Same As Input; LAS Options= unchecked; Define Input Coordinate System= No LAS Files. Output= LAS files. 2) LAS files were combined into a LAS dataset (LASD) using ArcGIS Pro tool Create LAS Dataset: Geoprocessing > Data Management Tools > LAS Dataset > Create LAS Dataset. Coordinate system= NAD_1983_2011_UTM_Zone_16N. 3) The LASD file was converted to a DEM using ArcGIS Pro tool LAS Dataset to Raster: Geoprocessing > Conversion Tools > Point Cloud > LAS Dataset to Raster. Value field= Elevation; Interpolation Type= Binning Average Linear; Output data type= Floating Point; Sampling Type= Cell Size; Sampling Value= 1 or 3; Z Factor= 1. AL 1998 PTS AL 2005 PTS AL 2007 PTS AL 2010 PTS AL 2015 PTS AL 2018 PTS 2025 AL 1998 DEM AL 2005 DEM AL 2007 DEM AL 2010 DEM AL 2015 DEM AL 2018 DEM Using the DEMs created from point cloud data, a contour shoreline was extracted by the same workflow outlined above using the Contour List tool and edited/smoothed in ArcGIS Pro 3.5.5. Attribute fields were added to the contour shoreline using the tool Add Fields (multiple). AL 1998 DEM AL 2005 DEM AL 2007 DEM AL 2010 DEM AL 2015 DEM AL 2018 DEM 2025 AL 1998 contour shoreline AL 2005 contour shoreline AL 2007 contour shoreline AL 2010 contour shoreline AL 2015 contour shoreline AL 2018 contour shoreline USGS All lidar datasets used in this release contain date values that are provided in the raw data as GPS time. These values were converted to a calendar date for use in DSAS via Python code written by Zehao Xue and Amy Farris of USGS. 2025 Attribute fields were populated for each of the lidar shorelines. 2025 All contour shorelines were then merged into a single file using the ArcGIS Pro tool Merge: Geoprocessing > Data Management Tools > General > Merge. AL 1998 contour shoreline AL 2005 contour shoreline AL 2007 contour shoreline AL 2010 contour shoreline AL 2015 contour shoreline AL 2016 contour shoreline AL 2018 contour shoreline USGS AL 2018 contour shoreline USACE AL 2020 contour shoreline AL 2022 contour shoreline 2025 AL contour shorelines Historical shorelines were merged with the lidar shorelines in ArcGIS Pro v3.5.5 to produce a single shorelines file for Alabama using the Merge tool. A length field (Length_m) was added to the merged shorelines file using XTools v25.0: Tools > Calculate Geometry. Parameter= length; Output units= meters. Historical shorelines 1849-2001 Dauphin shorelines 1940-2015 AL profile shorelines AL contour shorelines 2025 AL shorelines The shorelines shapefile (AL_shorelines.shp) was imported as a layer into the Digital Shoreline Analysis System (DSAS) v6.1 software to perform rate calculations. For details, please see the DSAS project page: https://www.usgs.gov/centers/whcmsc/science/digital-shoreline-analysis-system-dsas 2026 The shorelines 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 1123 0.0000001 0.0000001 Decimal degrees WGS_1984 WGS_84 6378137.0 298.257224 AL_shorelines Shorelines for coastal Alabama used in shoreline change analysis. U.S. Geological Survey FID Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Feature geometry. Esri Feature type. Date_ Date of shoreline position; date of survey as indicated on source material. A default date of 07/01 was assigned to shorelines where only the year was known (month and day unknown). Using July, the mid-point month of the calendar year, minimizes the potential offset to the actual shoreline date by a maximum of six months. U.S. Geological Survey Date of the shoreline is represented as MM/DD/YYYY Uncy Estimate of shoreline position uncertainty in meters. Actual shoreline position is within the range of this value (plus or minus, meters). The historic shoreline uncertainty values incorporate measurement uncertainties associated with mapping methods and materials for historical shorelines, the geographic registration of shoreline position, and shoreline digitizing. U.S. Geological Survey 0.99 13.00 Source Agency that provided shoreline feature or the data source used to digitize shoreline feature. U.S. Geological Survey Agency name or acronym. See lineage for all data source citations. Source_b Type of data used to create shoreline. U.S. Geological Survey aerial - contour Shoreline derived from Aerial Photography (contour extraction method). U.S. Geological Survey aerials; ESCYR125 Shoreline derived from Aerial Photography (FLDEP dataset from DOI:10.5066/F78P5XNK). U.S. Geological Survey CSC data Vector digital shoreline data from NOAA Coastal Services Center (DOI:10.5066/F78P5XNK). U.S. Geological Survey lidar - contour Shoreline derived from lidar data (contour extraction method). Data from DOI:10.5066/F7T43RB5. U.S. Geological Survey lidar DEM - contour Shoreline derived from DEM created from lidar point cloud data (contour extraction method). U.S. Geological Survey lidar points - profile Shoreline derived from lidar point cloud data (profile extraction method). U.S. Geological Survey MOG data Vector digital shoreline data from Mississippi Department of Environmental Quality, Office of Geology (MOG) (DOI:10.5066/F78P5XNK). U.S. Geological Survey T-Sheet Shoreline derived from NOAA Topographic Survey Sheet (T-Sheet). U.S. Geological Survey USA data Vector digital shoreline data from University of South Alabama (USA) (DOI:10.5066/F78P5XNK). U.S. Geological Survey Year_ Four-digit year of shoreline U.S. Geological Survey 1849 2022 Default_D Differentiates between shorelines that have known month and day attributes and those that use the default value of 07/01 when only the year is known. U.S. Geological Survey 0 Shoreline month and day are known. U.S. Geological Survey 1 Shoreline month and day are unknown and default value of 07/01 was used. U.S. Geological Survey DSAS_type Shoreline type field used to specify the proxy or datum to which the shoreline is referenced. It is a required field when proxy-based and datum-based shorelines are combined to compute rates in DSAS. U.S. Geological Survey MHW Mean High Water (datum-based shoreline). U.S. Geological Survey HWL High Water Line (proxy-based shoreline). U.S. Geological Survey WDL Wet-Dry Line (proxy-based shoreline). U.S. Geological Survey STATE U.S. State where the shoreline data are located. U.S. Geological Survey ALABAMA Shoreline data are within the borders of Alabama. U.S. Geological Survey SRCE_INFO Information regarding source data used to digitize or extract the shoreline feature. U.S. Geological Survey Character string of length 50 DEM Description of DEM used to extract shoreline feature. Example of DEM (GeoTIFF) filename downloaded from NOAA Digital Coast Data Access Viewer: usace2022_gulf_dem_J1218431tR0_C1. DEMs created from point cloud data are noted. A null value of 9999 indicates that the shoreline was not extracted from a DEM. U.S. Geological Survey Character string of length 100 MHW_elev Value of average MHW elevation (meters above NAVD88) that was used to extract the contour shoreline from DEM or point cloud data. A null value of 9999 represents a shoreline not extracted with a MHW value (such as proxy-based T-sheet data). U.S. Geological Survey 0.23 Average MHW elevation (meters above NAVD88) for Alabama. U.S. Geological Survey 9999 Null value U.S. Geological Survey Slope_ The foreshore beach slope calculated during the profile shoreline extraction process (see process step for details). Slope values were only calculated for lidar shorelines extracted by the profile method. All other segments have a null value of 9999. U.S. Geological Survey 1.89 16.89 9999 Null value U.S. Geological Survey Length_m Length of shoreline segment in meter units (NAD_1983_2011_UTM_Zone_16N). U.S. Geological Survey 2.037 29725.090 The entity and attribute information provided here describes the tabular data associated with the dataset. Please review the individual attribute descriptions for detailed information. U.S. Geological Survey U.S. Geological Survey - ScienceBase mailing and physical address

Federal Center, Building 810, MS 302

Denver CO 80225 USA 1-888-275-8747 sciencebase@usgs.gov The dataset contains polyline shorelines (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 ArcGIS Pro version 3.5.5 Esri polyline shapefile (compressed to ZIP format) 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. Transfer size is in MB. Unzip 6.44 https://doi.org/10.5066/P1JE2KSO https://www.sciencebase.gov/catalog/item/69e2b013b66b0195694c11e7 https://www.sciencebase.gov/catalog/file/get/69e2b013b66b0195694c11e7 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 address

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