Satellite-derived shorelines for the U.S. Atlantic coast (1984-2021)

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Frequently anticipated questions:

What does this data set describe?

Title:
Satellite-derived shorelines for the U.S. Atlantic coast (1984-2021)
Abstract:
This dataset contains shoreline positions derived from available Landsat satellite imagery for five states (Delaware, Maryland, Viginia, Georgia, and Florida) along the U.S. Atlantic coast for the time period 1984 to 2021. An open-source toolbox, CoastSat (Vos and others, 2019a and 2019b), was used to classify coastal Landsat imagery and detect shorelines at the sub-pixel scale. Resulting shorelines are presented in KMZ format. Significant uncertainty is associated with the locations of shorelines in extremely dynamic regions, including at the locations of river mouths, tidal inlets, capes, and ends of spits. These data are readily viewable in Google Earth. For best display of results, it is recommended to turn off any 3D viewing. For technical users and researchers, data can be ingested into Global Mapper or QGIS for more detailed analysis. Similar shoreline positions for North Carolina and South Carolina are available from Barnard and others, 2023 at https://doi.org/10.5066/P9W91314.
Supplemental_Information:
This data release was funded by the USGS Coastal and Marine Hazards and Resources Program. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
  1. How might this data set be cited?
    Vitousek, Sean F., Vos, Kilian, Barnard, Patrick L., and O’Neill, Andrea C., 20230315, Satellite-derived shorelines for the U.S. Atlantic coast (1984-2021): data release DOI:10.5066/P9BQQTCI, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, CA.

    Online Links:

    This is part of the following larger work.

    Barnard, Patrick L., Befus, Kevin, Danielson, Jeffrey J., Engelstad, Anita C., Erikson, Li H., Foxgrover, Amy C., Hayden, Maya K., Hoover, Daniel J., Leijnse, Tim, Massey, Chris, McCall, Robert, Nadal-Caraballo, Norberto C., Nederhoff, Kees, Ohenhen, Leonard, O’Neill, Andrea C., Parker, Kai A., Shirzaei, Manoocher, Su, Xin, Thomas, Jennifer A., Ormondt, Maarten van, Vitousek, Sean F., Vos, Kilian, and Yawn, Madison C., 2023, Future coastal hazards along the U.S. Atlantic coast: data release DOI:10.5066/P9BQQTCI, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, CA.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -82.11192
    East_Bounding_Coordinate: -75.32334
    North_Bounding_Coordinate: 38.81563
    South_Bounding_Coordinate: 26.06347
  3. What does it look like?
    SatelliteDerivedShorelines_US_Atlanticcoast.png (png)
    Image map showing showing study area for satellite derived shorelines along SE Atlantic coast.
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 1984
    Ending_Date: 2021
    Currentness_Reference:
    collection years of satellite imagery used to determine shoreline positions
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: Shoreline positions in Google Earth KMZ formats
  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):
      • GT-polygon composed of chains (100000)
    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 0.000001. Longitudes are given to the nearest 0.000001. Latitude and longitude values are specified in Decimal Degrees. The horizontal datum used is North American Datum 1983.
      The ellipsoid used is Geodetic Reference System 80.
      The semi-major axis of the ellipsoid used is 6378137.000000.
      The flattening of the ellipsoid used is 1/298.257222.
      Vertical_Coordinate_System_Definition:
      Depth_System_Definition:
      Depth_Datum_Name: NAVD88
      Depth_Resolution: 1.0
      Depth_Distance_Units: meters
      Depth_Encoding_Method: Implicit coordinate
  7. How does the data set describe geographic features?
    Shoreline positions for historical period (1984-2021) for the U.S. Atlantic coast, derived from satellite imagery
    KMZ file consists of shoreline positions derived from imagery of the U.S. Atlantic coast. Shorelines are represented as lines colored based on the date of imagery acquisition. Older shorelines are displayed in blue, and in red for newer shorelines. (Source: Producer Defined)
    CoastSat_shoreline
    Position of unique shoreline segment derived from satellite imagery for date and time indicated. (Source: Producer Defined) geographic position of shoreline derived from satellite imagery.
    Entity_and_Attribute_Overview:
    Shoreline positions for period 1984-2021 along the U.S. Atlantic coast.
    Entity_and_Attribute_Detail_Citation:
    Shoreline positions for period 1984-2021 along the U.S. Atlantic coast. The KMZ files consist of shoreline positions derived from satellite imagery. Shorelines are represented as lines colored based on the date of imagery acquisition. Older shorelines are displayed in blue, and in red for newer shorelines.

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Sean F. Vitousek
    • Kilian Vos
    • Patrick L. Barnard
    • Andrea C. O’Neill
  2. Who also contributed to the data set?
    This data release was funded by the USGS Coastal and Marine Hazards and Resources Program.
  3. To whom should users address questions about the data?
    U.S. Geological Survey, Pacific Coastal and Marine Science Center
    Attn: PCMSC Science Data Coordinator
    2885 Mission Street
    Santa Cruz, CA

    831-427-4747 (voice)
    pcmsc_data@usgs.gov

Why was the data set created?

These data provide estimates of automatically detected coastal shoreline position for resource managers, science researchers, students, and the general public. These data can be used with geographic information systems, shoreline evolution models, or other software to assist identifying and assessing possible areas of vulnerability, along with appropriate inclusion of uncertainty. These data are not intended to be used for navigation or in lieu of definitive shoreline datasets.

How was the data set created?

  1. From what previous works were the data drawn?
    Landsat imagery (source 1 of 2)
    U.S. Geological Survey, 2021, Landsat imagery (from Landsat 5-8) for the U.S. southeast Atlantic coast: U.S. Geological Survey, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution:
    The archive of Landsat 5-8 satellite imagery accessed through Google Earth Engine was used to derive shoreline positions for the study area.
    FES 2014 (source 2 of 2)
    Carrere, L., Lyard, F., Cancet, M., Guillot, A., and Picot, N., 20160501, FES (Finite Element Solution) 2014, a new tidal model—Validation results and perspectives for improvements: AVISO, online.

    Online Links:

    Type_of_Source_Media: online model
    Source_Contribution:
    Tidal corrections in the shoreline position were made tiwth tide height predicted from the FES 2014 model.
  2. How were the data generated, processed, and modified?
    Date: 09-Feb-2021 (process 1 of 6)
    Set up CoastSat toolbox (Vos and others, 2019a and 2019b) for implementation along the region of interest. Toolbox set up in python 3.7 to run for geography spanning coastline for the U.S. Atlantic coast, for the time period of 01 March 1984 to 27 April 2021. The beach slopes used for the tidal corrections were automatically derived from the raw satellite shorelines using the method explained by Vos and others (2020). CoastSat operates on the same transects as the CoSMoS-COAST model for the region (Vitousek and others, 2023), modified from the transects of the Digital Shoreline Analysis System (DSAS; Himmelstoss and others, 2021). The transects were grouped (including a 500 m lateral buffer) into several different bounding boxes for which the satellite imagery was extracted. The bounding boxes had an average size of 16 km2 (a maximum of 32 km2 and a minimum of 1 km2).
    Date: 01-Apr-2021 (process 2 of 6)
    Ran CoastSat toolbox on Landsat imagery available through Google Earth Engine (Gorelick and others, 2017) for geography and time period of interest. Only cloudless imagery or imagery with less than 50 percent cloud cover was used. Imagery had horizontal resolution of 30 m, which was pan-sharpened to 15 m. Tidal corrections were applied using tide heights estimated from the FES 2014 Tidal model. Data sources used in this process:
    • FES 2014, Landsat imagery
    Date: 15-Sep-2021 (process 3 of 6)
    Checked output to ensure quality results. These shorelines represent the automatically detected shoreline segments as identified by CoastSat (no other adjustments). The accuracy of the satellite-derived shoreline (SDS) for this area was addressed in Vos and others (2019a), who compared SDS observations with ground-based surveys at Duck, NC. They found an RMS accuracy of about 9 m (root mean square error). Lacking additional, sufficient ground-based observations for the purposes of further robust error estimates, authors use an error of 10 m (in root mean square error) for the SDS dataset. In dynamic locations, including areas such as river mouths, capes, and ends of spits, uncertainty is greater, and locations should be inspected and used with care.
    Date: 16-Dec-2021 (process 4 of 6)
    Checked all output to ensure quality results.
    Date: 10-Jan-2022 (process 5 of 6)
    Organized final extracted shorelines into KMZ files grouped by state. Shorelines are represented as lines that are colored based on the date of imagery acquisition. Older shorelines are displayed in blue, and in red for newer shorelines.
    Date: 16-May-2023 (process 6 of 6)
    Edits were made to correct spelling in author name. No data were changed. The metadata available from a harvester may supersede metadata bundled within a download file. Users are advised to compare the metadata date of this file to any similar file to ensure they are using the most recent version. (scochran@usgs.gov)
  3. What similar or related data should the user be aware of?
    Barnard, Patrick L., Befus, Kevin, Danielson, Jeffrey J., Engelstad, Anita C., Erikson, Li H., Foxgrover, Amy C., Hardy, Matthew W., Hoover, Daniel J., Leijnse, Tim, Massey, Chris, McCall, Robert, Nadal-Caraballo, Norberto C., Nederhoff, Kees, Ohenhen, Leonard, O’Neill, Andrea C., Parker, Kai A., Shirzaei, Manoocher, Su, Xin, Thomas, Jennifer A., Ormondt, Maarten van, Vitousek, Sean F., and Yawn, Madison C., 2023, Future coastal hazards along the U.S. North and South Carolina coasts.

    Online Links:

    Other_Citation_Details:
    Barnard, P.L., Befus, K., Danielson, J.J., Engelstad, A.C., Erikson, L.H., Foxgrover, A.C., Hardy, M.W., Hoover, D.J., Leijnse, T., Massey, C., McCall, R., Nadal-Caraballo, N.C., Nederhoff, K., Ohenhen, L., O’Neill, A.C., Parker, K.A., Shirzaei, M., Su, X., Thomas, J.A., van Ormondt, M., Vitousek, S.F., Vos K., and Yawn, M.C., 2023 Future coastal hazards along the U.S. North and South Carolina coasts: U.S. Geological Survey data release, https://doi.org/10.5066/P9W91314
    Vitousek, S., Barnard, P.L., Limber, P.W., Erikson, L.H., and Cole, B., 2017, A model integrating longshore and cross-shore processes for predicting long-term shoreline response to climate change.

    Online Links:

    Other_Citation_Details:
    Vitousek, S., Barnard, P.L., Limber, P., Erikson, L.H., and Cole, B., 2017, A model integrating longshore and cross-shore processes for predicting long-term shoreline response to climate change: Journal of Geophysical Research--Earth Surface, v. 122, p. 782-806.
    Vitousek, S., Cagigal, L., Montano, J., Rueda, A., Mendez, F., Coco, G., and Barnard, P.L., 2021, The application of ensemble wave forcing to quantify uncertainty of shoreline change predictions.

    Online Links:

    Other_Citation_Details:
    Vitousek, S., Cagigal, L., Montaño, J., Rueda, A., Mendez, F., Coco, G., and Barnard, P.L., 2021, The application of ensemble wave forcing to quantify uncertainty of shoreline change predictions: Journal of Geophysical Research: Earth Surface, v. 126, e2019JF005506.
    Vitousek, Sean, Vos, Kilian, Barnard, Patrick L., and O’Neill, Andrea C., 2023, Projections of Shoreline Change of current and future (2005-2100) sea-level rise scenarios for the U.S. Atlantic coast.

    Online Links:

    Other_Citation_Details:
    Barnard, P.L., Befus, K., Nadal-Caraballo, N.C., Danielson, J., Engelstad, A., Erikson, L.H., Foxgrover, A.C., Hardy, M., Hoover, D., Leijnse, T., Massey, C., McCall, R., Nederhoff, K., Ohenhen, L., O'Neill, A.C., Parker, K., Shirzaei, M., Su, X., Thompson, J., van Ormondt, M., Vitousek, S., Vos, K., Yawn, M.C., 2023. Future Coastal Hazards along the U.S. Atlantic coast. U.S. Geological Survey data release, https://doi.org/10.5066/P9BQQTCI
    Vos, K., Harley, M.D., Splinter, K.D., Simmons, J.A., and Turner, I.L., 2019, Sub-annual to multi-decadal shoreline variability from publicly available satellite imagery.

    Online Links:

    Other_Citation_Details:
    Vos, K., Harley, M.D., Splinter, K.D., Simmons, J.A., and Turner, I.L., 2019, Sub-annual to multi-decadal shoreline variability from publicly available satellite imagery: Coastal Engineering, v. 150, p. 160-174.
    Vos, K., Splinter, K.D., Harley, M.D., Simmons, J.A., and Turner, I.L., 2019, CoastSat: A Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery.

    Online Links:

    Other_Citation_Details:
    Vos, K., Splinter, K.D., Harley, M.D., Simmons, J.A., and Turner, I.L., 2019, CoastSat: A Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery: Environmental Modelling and Software, v. 122, 104528.
    Vos, K., Harley, M.D., Splinter, K.D., Walker, A., and Turner, I.L., 2020, Beach slopes from satellite‐derived shorelines.

    Online Links:

    Other_Citation_Details:
    Vos, K., Harley, M.D., Splinter, K.D., Walker, A., and Turner, I.L, 2020, Beach slopes from satellite‐derived shorelines: Geophysical Research Letters, v. 47, e2020GL088365.
    Gorelick, N., Hancher, M., Dixon, M., Ilyshechenko, S., Thau, D., and Moore, R., 2017, Google Earth Engine: Planetary-scale geospatial analysis for everyone..

    Online Links:

    Other_Citation_Details:
    Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore, R., 2017, Google Earth Engine: Planetary-scale geospatial analysis for everyone: Remote Sensing of Environment, v. 202, p. 18-27.
    Himmelstoss, E.A., Farris, A.S., Henderson, R.E., Kratzmann, M.G., Ergul, A., Zhang, O., Zichichi, J.L., and Thieler, E.R., 2021, Digital Shoreline Analysis System (version 5.1).

    Online Links:

    Other_Citation_Details:
    Himmelstoss, E.A., Farris, A.S., Henderson, R.E., Kratzmann, M.G., Ergul, A., Zhang, O., Zichichi, J.L., Thieler, E.R., 2021, Digital Shoreline Analysis System (version 5.1): U.S. Geological Survey software release, https://code.usgs.gov/cch/dsas.

How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?
    Attribute values are estimates of shoreline position based on satellite imagery. The accuracy of this method was assessed by Vos and others (2019a), who compared data with ground-based surveys at Duck, North Carolina. In line with these estimates, authors are using a cross-shore horizontal error of 10 m (root mean square error) in most locations. In dynamic locations, including areas such as river mouths, capes, and ends of spits, uncertainty is greater, and positions should be inspected and used with care.
  2. How accurate are the geographic locations?
    Data are concurrent with specified transect locations.
  3. How accurate are the heights or depths?
    N/A
  4. Where are the gaps in the data? What is missing?
    Data set is considered complete for the information presented and will be updated as needed.
  5. How consistent are the relationships among the observations, including topology?
    Data have undergone QA/QC and fall within expected/reasonable ranges.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints None
Use_Constraints USGS-authored or produced data and information are in the public domain from the U.S. Government and are freely redistributable with proper metadata and source attribution. Please recognize and acknowledge the U.S. Geological Survey as the originator(s) of the dataset and in products derived from these data.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey - CMGDS
    2885 Mission Street
    Santa Cruz, CA

    831-427-4747 (voice)
    pcmsc_data@usgs.gov
  2. What's the catalog number I need to order this data set? These data are available in KMZ format (zipped KML files), by state. Virginia, Maryland and Delaware are combined in one KMZ file.
  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 on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty.
  4. How can I download or order the data?
    • Availability in digital form:
      Data format: KMZ file for Florida in format KML (version Google Earth Pro (version 7.3, Google, 2017)) Features are in KMZ format (a zipped form of KML) and are projected in UTM Zone 17 coordinates, with horizontal datum NAD83 and vertical datum NAVD88. Size: 96.9
      Network links: https://doi.org/10.5066/P9BQQTCI
      Data format: KMZ file for Georgia in format KML (version Google Earth Pro (version 7.3, Google, 2017)) Features are in KMZ format (a zipped form of KML) and are projected in UTM Zone 17 coordinates, with horizontal datum NAD83 and vertical datum NAVD88. Size: 32.6
      Network links: https://doi.org/10.5066/P9BQQTCI
      Data format: KMZ file for Virginia, Maryland and Delaware in format KML (version Google Earth Pro (version 7.3, Google, 2017)) Features are in KMZ format (a zipped form of KML) and are projected in UTM Zone 18 coordinates, with horizontal datum NAD83 and vertical datum NAVD88. Size: 32.7
      Network links: https://doi.org/10.5066/P9BQQTCI
    • Cost to order the data: None.

  5. What hardware or software do I need in order to use the data set?
    These data can be viewed with Google Earth software, and other compatible GIS software such as Global Mapper or QGIS.

Who wrote the metadata?

Dates:
Last modified: 16-May-2023
Metadata author:
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Attn: PCMSC Science Data Coordinator
2885 Mission Street
Santa Cruz, CA

831-427-4747 (voice)
pcmsc_data@usgs.gov
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/pcmsc/DataReleases/CMGDS_DR_tool/DR_P9BQQTCI/SatelliteDerivedShorelines_metadata.faq.html>
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