Alabama: shorelines (1849-2022) used to calculate shoreline change rates

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Frequently anticipated questions:

What does this data set describe?

Title:
Alabama: shorelines (1849-2022) used to calculate shoreline change rates
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: shorelines (1849-2022) used to calculate shoreline change rates: 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: -88.345344
    East_Bounding_Coordinate: -87.518313
    North_Bounding_Coordinate: 30.285429
    South_Bounding_Coordinate: 30.219182
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/69e2b013b66b0195694c11e7?name=AL_shorelines.png&allowOpen=true (PNG)
    Map view of data. Blue lines indicate the extent of the shoreline data in Alabama.
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date:
    Ending_Date: 2022
    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 (1123)
    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 1/298.257224.
  7. How does the data set describe geographic features?
    AL_shorelines
    Shorelines for coastal Alabama used in shoreline change analysis. (Source: U.S. Geological Survey)
    FID
    Internal feature number. (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Shape
    Feature geometry. (Source: 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. (Source: 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. (Source: U.S. Geological Survey)
    Range of values
    Minimum:0.99
    Maximum:13.00
    Source
    Agency that provided shoreline feature or the data source used to digitize shoreline feature. (Source: U.S. Geological Survey) Agency name or acronym. See lineage for all data source citations.
    Source_b
    Type of data used to create shoreline. (Source: U.S. Geological Survey)
    ValueDefinition
    aerial - contourShoreline derived from Aerial Photography (contour extraction method).
    aerials; ESCYR125Shoreline derived from Aerial Photography (FLDEP dataset from DOI:10.5066/F78P5XNK).
    CSC dataVector digital shoreline data from NOAA Coastal Services Center (DOI:10.5066/F78P5XNK).
    lidar - contourShoreline derived from lidar data (contour extraction method). Data from DOI:10.5066/F7T43RB5.
    lidar DEM - contourShoreline derived from DEM created from lidar point cloud data (contour extraction method).
    lidar points - profileShoreline derived from lidar point cloud data (profile extraction method).
    MOG dataVector digital shoreline data from Mississippi Department of Environmental Quality, Office of Geology (MOG) (DOI:10.5066/F78P5XNK).
    T-SheetShoreline derived from NOAA Topographic Survey Sheet (T-Sheet).
    USA dataVector digital shoreline data from University of South Alabama (USA) (DOI:10.5066/F78P5XNK).
    Year_
    Four-digit year of shoreline (Source: U.S. Geological Survey)
    Range of values
    Minimum:1849
    Maximum: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. (Source: U.S. Geological Survey)
    ValueDefinition
    0Shoreline month and day are known.
    1Shoreline month and day are unknown and default value of 07/01 was used.
    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. (Source: U.S. Geological Survey)
    ValueDefinition
    MHWMean High Water (datum-based shoreline).
    HWLHigh Water Line (proxy-based shoreline).
    WDLWet-Dry Line (proxy-based shoreline).
    STATE
    U.S. State where the shoreline data are located. (Source: U.S. Geological Survey)
    ValueDefinition
    ALABAMAShoreline data are within the borders of Alabama.
    SRCE_INFO
    Information regarding source data used to digitize or extract the shoreline feature. (Source: 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. (Source: 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). (Source: U.S. Geological Survey)
    ValueDefinition
    0.23Average MHW elevation (meters above NAVD88) for Alabama.
    9999Null value
    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. (Source: U.S. Geological Survey)
    ValueDefinition
    9999Null value
    Range of values
    Minimum:1.89
    Maximum:16.89
    Length_m
    Length of shoreline segment in meter units (NAD_1983_2011_UTM_Zone_16N). (Source: U.S. Geological Survey)
    Range of values
    Minimum:2.037
    Maximum:29725.090
    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)
    • 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 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.

How was the data set created?

  1. From what previous works were the data drawn?
    Historical shorelines 1849-2001 (source 1 of 14)
    Himmelstoss, E.A., Kratzmann, M.G., and Thieler, E.R., 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:

    Other_Citation_Details: Alabama shoreline data from DOI:10.5066/F78P5XNK
    Type_of_Source_Media: digital data
    Source_Contribution:
    Historical shorelines (T-sheet-derived, for example) from this publication (DOI:10.5066/F78P5XNK, downloaded in 2025) were used in the shoreline change analysis.
    Dauphin shorelines 1940-2015 (source 2 of 14)
    Henderson, R.E., Nelson, P.R., Long, J.W., and Smith, C.G., 2017, Vector shorelines and associated shoreline change rates derived from lidar and aerial imagery for Dauphin Island, Alabama: 1940–2015: data release DOI:10.5066/F7T43RB5, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Dauphin Island, Alabama, shoreline data from DOI:10.5066/F7T43RB5
    Type_of_Source_Media: digital data
    Source_Contribution:
    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.
    AL 1998 PTS (source 3 of 14)
    NOAA Office for Coastal Management, 2022, 1998 Fall Gulf Coast NOAA/USGS/NASA Airborne LiDAR Assessment of Coastal Erosion (ALACE) Project for the US Coastline: 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.
    Type_of_Source_Media: digital data
    Source_Contribution:
    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.
    AL 2005 PTS (source 4 of 14)
    NOAA Office for Coastal Management Partners, 2022, 2005 US Army Corps of Engineers (USACE) Post-Hurricane Katrina Topo/Bathy Project for the Alabama, Florida, Louisiana and Mississippi Coasts: 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.
    Type_of_Source_Media: digital data
    Source_Contribution:
    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.
    AL 2007 PTS (source 5 of 14)
    NOAA Office for Coastal Management Partners, 2022, 2007 USGS/NPS/NASA Experimental Advanced Airborne Research Lidar (EAARL): Northern Gulf of Mexico Barrier Islands: 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.
    Type_of_Source_Media: digital data
    Source_Contribution:
    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.
    AL 2010 PTS (source 6 of 14)
    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.
    Type_of_Source_Media: digital data
    Source_Contribution:
    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.
    AL 2015 PTS (source 7 of 14)
    NOAA Office for Coastal Management Partners, 2026, 2015 USGS Lidar: South Terrebonne and Gulf Islands, LA: Office for Coastal Management, Charleston, SC.

    Online Links:

    Other_Citation_Details:
    Point cloud data were downloaded for Dauphin Island, Alabama. Projection = NAD_1983_2011_UTM_Zone_16N.
    Type_of_Source_Media: digital data
    Source_Contribution:
    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.
    AL 2016 PTS (source 8 of 14)
    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.
    Type_of_Source_Media: digital data
    Source_Contribution:
    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.
    AL 2016 DEM (source 9 of 14)
    NOAA Office for Coastal Management Partners, 2026, 2016 USACE NCMP Topobathy Lidar DEM: Gulf Coast (AL, FL, MS, TX): Office for Coastal Management, Charleston, SC.

    Online Links:

    Other_Citation_Details:
    DEM data were downloaded for Alabama. Projection = NAD_1983_2011_UTM_Zone_16N.
    Type_of_Source_Media: digital data
    Source_Contribution:
    The elevation data were downloaded as DEM tiles for extraction of datum-based shoreline (contour method). Data accessed and downloaded in 09/2025.
    AL 2018 PTS (source 10 of 14)
    NOAA Office for Coastal Management Partners, 2026, 2018 USGS Topobathy Lidar: Gulf Coast Islands (AL, FL, LA): Office for Coastal Management, Charleston, SC.

    Online Links:

    Other_Citation_Details:
    Point cloud data were downloaded for Dauphin Island, Alabama. Projection = NAD_1983_2011_UTM_Zone_16N.
    Type_of_Source_Media: digital data
    Source_Contribution:
    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.
    AL 2018 DEM (source 11 of 14)
    NOAA Office for Coastal Management Partners, 2026, 2018 USACE NCMP Topobathy Lidar DEM: Gulf Coast (AL, MS): Office for Coastal Management, Charleston, SC.

    Online Links:

    Other_Citation_Details:
    DEM data were downloaded for mainland Alabama. Projection = NAD_1983_2011_UTM_Zone_16N.
    Type_of_Source_Media: digital data
    Source_Contribution:
    The elevation data were downloaded as DEM tiles for extraction of datum-based shoreline (contour method). Data accessed and downloaded in 07/2025.
    AL 2020 DEM (source 12 of 14)
    NOAA National Geodetic Survey, 2026, 2019 - 2020 NOAA NGS Topobathy Lidar DEM: Hurricane Michael (NW Florida): Office for Coastal Management, Charleston, SC.

    Online Links:

    Other_Citation_Details:
    DEM data were downloaded for Alabama (Block 6, Time Frame 5). Alabama dataset date= 02/22/2020. Projection = NAD_1983_2011_UTM_Zone_16N.
    Type_of_Source_Media: digital data
    Source_Contribution:
    The elevation data were downloaded as DEM tiles for extraction of datum-based shoreline (contour method). Data accessed and downloaded in 07/2025.
    AL 2022 PTS (source 13 of 14)
    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.
    Type_of_Source_Media: digital data
    Source_Contribution:
    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.
    AL 2022 DEM (source 14 of 14)
    NOAA Office for Coastal Management Partners, 2026, 2022 USACE NCMP Topobathy Lidar DEM: Gulf Coast (AL, FL, MS): Office for Coastal Management, Charleston, SC.

    Online Links:

    Other_Citation_Details:
    DEM data were downloaded for Alabama (Time Frame 1). Projection = NAD_1983_2011_UTM_Zone_16N.
    Type_of_Source_Media: digital data
    Source_Contribution:
    The elevation data were downloaded as DEM tiles for extraction of datum-based shoreline (contour method). Data accessed and downloaded in 09/2025.
  2. How were the data generated, processed, and modified?
    Date: 2025 (process 1 of 15)
    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. 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:
    • DOI:10.5066/F78P5XNK shorelines
    Data sources produced in this process:
    • Historical shorelines 1849-2001
    Date: 2025 (process 2 of 15)
    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. 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:
    • DOI:10.5066/F7T43RB5 shorelines
    Data sources produced in this process:
    • Dauphin shorelines 1940-2015
    Date: 2025 (process 3 of 15)
    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. 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)
    Date: 2025 (process 4 of 15)
    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. Person who carried out this activity:
    U.S. Geological Survey
    Attn: Amy S. Farris
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 (voice)
    508-457-2310 (FAX)
    Data sources used in this process:
    • AL 2010 PTS
    • AL 2016 PTS
    • AL 2022 PTS
    Data sources produced in this process:
    • AL 2010 profile shoreline
    • AL 2016 profile shoreline
    • AL 2022 profile shoreline
    Date: 2025 (process 5 of 15)
    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. 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:
    • AL 2010 profile shoreline
    • AL 2016 profile shoreline
    • AL 2022 profile shoreline
    Data sources produced in this process:
    • AL profile shorelines
    Date: 2025 (process 6 of 15)
    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.
    Date: 2025 (process 7 of 15)
    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. Data sources used in this process:
    • AL 2016 DEM
    • AL 2018 DEM
    • AL 2020 DEM
    • AL 2022 DEM
    Data sources produced in this process:
    • AL 2016 contour shoreline
    • AL 2018 contour shoreline USACE
    • AL 2020 contour shoreline
    • AL 2022 contour shoreline
    Date: 2025 (process 8 of 15)
    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. Data sources used in this process:
    • AL 1998 PTS
    • AL 2005 PTS
    • AL 2007 PTS
    • AL 2010 PTS
    • AL 2015 PTS
    • AL 2018 PTS
    Data sources produced in this process:
    • AL 1998 DEM
    • AL 2005 DEM
    • AL 2007 DEM
    • AL 2010 DEM
    • AL 2015 DEM
    • AL 2018 DEM
    Date: 2025 (process 9 of 15)
    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). Data sources used in this process:
    • AL 1998 DEM
    • AL 2005 DEM
    • AL 2007 DEM
    • AL 2010 DEM
    • AL 2015 DEM
    • AL 2018 DEM
    Data sources produced in this process:
    • 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
    Date: 2025 (process 10 of 15)
    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.
    Date: 2025 (process 11 of 15)
    Attribute fields were populated for each of the lidar shorelines.
    Date: 2025 (process 12 of 15)
    All contour shorelines were then merged into a single file using the ArcGIS Pro tool Merge: Geoprocessing > Data Management Tools > General > Merge. Data sources used in this process:
    • 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
    Data sources produced in this process:
    • AL contour shorelines
    Date: 2025 (process 13 of 15)
    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. Data sources used in this process:
    • Historical shorelines 1849-2001
    • Dauphin shorelines 1940-2015
    • AL profile shorelines
    • AL contour shorelines
    Data sources produced in this process:
    • AL shorelines
    Date: 2026 (process 14 of 15)
    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
    Date: 2026 (process 15 of 15)
    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.
  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:

    Other_Citation_Details:
    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
    Weber, Kathryn M., List, Jeffrey H., and Morgan, Karen L.M., 2005, An operational mean high water datum for determination of shoreline position from topographic lidar data: Open-File Report 2005-1027, 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 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.
  2. How accurate are the geographic locations?
    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.
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    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.
  5. How consistent are the relationships among the observations, including topology?
    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.

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. 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 - ScienceBase
    Federal Center, Building 810, MS 302
    Denver, CO
    USA

    1-888-275-8747 (voice)
  2. What's the catalog number I need to order this data set? The dataset contains polyline shorelines (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_shorelines_metadata.faq.html>
Generated by mp version 2.9.51 on Mon Jun 22 16:21:27 2026