2018 Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis

Metadata also available as - [Outline] - [Parseable text] - [XML]

Frequently anticipated questions:

What does this data set describe?

Title:
2018 Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis
Abstract:
The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas most susceptible to erosion or accretion. These data can help coastal managers understand which areas of the coast are vulnerable. This data release and other associated products represent an expansion of the USGS national-scale shoreline database to include Puerto Rico and its islands, Vieques and Culebra. The United States Geological Survey (USGS) in cooperation with the Coastal Research and Planning Institute of Puerto Rico (CoRePI, part of the Graduate School of Planning at the University of Puerto Rico, Rio Piedras Campus) has derived and compiled a database of historical shoreline positions using a variety of methods. These shorelines are used to measure the rate of shoreline change over time.
Supplemental_Information:
Described in Farris and others (2018), the contour method extracts the elevation of average MHW value from DEM data using ArcMap tool Contour List with the MHW value chosen for the contour, and profile method extracts the MHW position from point could data using a Matlab based approach. The resulting shorelines are polyline shapefiles. Cross-referenced citations are applicable to the dataset as a whole. Additional citations are located within individual process steps that pertain specifically to the method described in that step.
  1. How might this data set be cited?
    Heslin, Julia L., Henderson, Rachel E., Weber, Kathryn M., and Himmelstoss, Emily A., 20211119, 2018 Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis: data release DOI:10.5066/P9AZYW74, U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

    This is part of the following larger work.

    Heslin, Julia L., Henderson, Rachel E., and Himmelstoss, Emily A., 2021, A GIS Compilation of Vector Shorelines for Puerto Rico from 2015 to 2018: data release DOI:10.5066/P9AZYW74, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Heslin, J.L., Henderson, R.E., and Himmelstoss, E.A., 2021, A GIS compilation of vector shorelines for Puerto Rico from 2015 to 2018: U.S. Geological Survey data release, https://doi.org/10.5066/P9AZYW74.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -67.2715
    East_Bounding_Coordinate: -65.2441
    North_Bounding_Coordinate: 18.5195
    South_Bounding_Coordinate: 17.9267
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/613f7a90d34e1449c5d35c9e?name=PR_2018_Lidar_Shoreline.jpg (JPEG)
    Map of the USACE 2018 MHW shoreline (shown in green) extracted from lidar data, with the extent of lidar coverage highlighted in red.
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 03-Jul-2018
    Ending_Date: 28-Jul-2018
    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 (2758)
    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 0.0197395052. Longitudes are given to the nearest 0.0264490611. Latitude and longitude values are specified in Decimal seconds. The horizontal datum used is WGS_1984.
      The ellipsoid used is WGS_84.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.257223563.
  7. How does the data set describe geographic features?
    PR_2018_USACE_MHW_Shoreline.shp
    The mean high water (MHW) shoreline for the Puerto Rican coast 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) Coordinates defining the features.
    CONTOUR
    The height of MHW was determined from vdatum provided by NOAA. (https://vdatum.noaa.gov/). One MHW value was used for a continuous section of coast (as opposed to using a continuously varying value). This value is always within 15 cm of the value returned by vdatum at any point along the coast. (Source: U.S. Geological Survey)
    Range of values
    Minimum:0.13
    Maximum:0.13
    DSAS_DATE
    Date of shoreline position; date of survey as indicated on source material. (Source: U.S. Geological Survey) Date of the shoreline in mm/dd/yyyy
    UNCY
    Estimate of shoreline position uncertainty derived by adding in quadrature the identified components of uncertainty described in the horizontal positional accuracy section of this metadata file. Actual shoreline position is assumed to be within the range of this value (plus or minus, meters). (Source: U.S. Geological Survey)
    Range of values
    Minimum:0.95
    Maximum:5.50
    PROXY
    Method of deriving shoreline feature. These shorelines were all extracted from lidar using a MHW elevation. When combined with other data (high water line, wet-dry line) for shoreline analysis this field preserves the method used to derive this shoreline. (Source: U.S. Geological Survey)
    ValueDefinition
    MHWThe average Mean high water (MHW) for Puerto Rico, as described in process steps
    AGENCY
    The agency that provided the source data to create the shoreline (Source: U.S. Geological Survey)
    ValueDefinition
    USACE FEMAThe United States Army Corps of Engineers and Federal Emergency Management Agency
    TYPE
    The type of source data used to create the shoreline (Source: U.S. Geological Survey)
    ValueDefinition
    LidarLight detection and ranging elevation data
    METHOD
    Method of shoreline extraction from lidar - contour or profile. See process steps for details. (Source: U.S. Geological Survey)
    ValueDefinition
    ProfileShorelines were extracted using the profile method (Farris and others, 2018)
    ContourShorelines were extracted using the contour method (Farris and others, 2018)

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Julia L. Heslin
    • Rachel E. Henderson
    • Kathryn M. Weber
    • Emily A. Himmelstoss
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    U.S. Geological Survey
    Attn: Rachel E. Henderson
    384 Woods Hole Road
    Woods Hole, MA
    USA

    508-548-8700 (voice)
    rehenderson@contractor.usgs.gov

Why was the data set created?

This shoreline dataset is a mean high water (MHW) datum-based shoreline extracted using the contour and the profile method (Farris and others 2018). See process steps for descriptioin of use. These data are used in conjunction with other shoreline files to calculate rates of shoreline change.

How was the data set created?

  1. From what previous works were the data drawn?
    vdatum (source 1 of 4)
    NOAA, 20201203, vertical Datum transformation (Vdatum) version 4.2.1: NOAA Office for Coastal Management (OCM), Charleston, SC.

    Online Links:

    Type_of_Source_Media: online
    Source_Contribution: used to define MHW elevation for Puerto Rico.
    2018 DEM (source 2 of 4)
    Office for Coastal Management (OCM) Partners, and NOAA Office for Coastal Management, 20190702, 2018 USACE FEMA Topobathy Lidar DEM: Main Island, Culebra, and Vieques, Puerto Rico: NOAA Office for Coastal Management (OCM), Charleston, SC.

    Online Links:

    Type_of_Source_Media: online
    Source_Contribution:
    The raster digital elevation model (in GeoTIFF format) was used to extract a polyline shoreline. The data were downloaded using the following parameters: projection in State Plane 1983; Zone 5200 Puerto Rico, NAD83 horizontal datum; PRVD02 vertical datum. The raster resolution is 1 meter.
    2018 point cloud data (source 3 of 4)
    Office for Coastal Management (OCM) Partners, and NOAA Office for Coastal Management, 20190702, 2018 USACE FEMA Topobathy Lidar: Main Island, Culebra, and Vieques, Puerto Rico Point Cloud files with Orthometric Vertical Datum Puerto Rico Vertical Datum of 2002 (PRVD02) using GEOID18: NOAA Office for Coastal Management (OCM), Charleston, SC.

    Online Links:

    Type_of_Source_Media: online
    Source_Contribution:
    The bare earth point cloud data in LAS format were used to extract shorelines using the profile method described in the process steps.
    2018 lidar flight line information (source 4 of 4)
    USACE NCMP and FEMA, 20190702, JALBTCX 2018 Flight Lines: Dates Flown: USACE, Charleston, SC.

    Online Links:

    Type_of_Source_Media: online
    Source_Contribution:
    The flight line data was used to extract the date for contour shoreline segments.
  2. How were the data generated, processed, and modified?
    Date: 01-Jan-2020 (process 1 of 10)
    Overview of the methods used to extract shoreline features in Puerto Rico and the islands of Vieques and Culebra: This data release has two methods of shoreline extraction: the contour method and the profile method. Both methods use the MHW elevation for shoreline extraction. The average MHW for Puerto Rico was calculated using NOAA’s vdatum tool (version 4.1.2; https://vdatum.noaa.gov/) to model the regional surface using local MHW values based on the PRVD02 vertical datum.
    The contour method was the primary method in the shoreline extraction process. Described in Farris and others (2018), the contour method extracts the elevation of average MHW value from DEM data using ArcMap tool “Contour List” with the MHW value chosen for the contour. These shorelines are polyline shapefiles.
    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. Person who carried out this activity:
    Rachel E. Henderson
    U.S. Geological Survey
    Researcher VII
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 (voice)
    rehenderson@contractor.usgs.gov
    Date: 01-Feb-2020 (process 2 of 10)
    Definition of average MHW for Puerto Rico: The height of MHW was determined from vdatum provided by NOAA. (https://vdatum.noaa.gov/). We continued the practice set out by Weber and others (2005) of using one MHW value for a continuous section of coast (as opposed to using a continuously varying value). This value is always within 6 cm of the value returned by vdatum at any point along the coast. The MHW value ranges from 0.09 m to 0.19 m from all tide observation stations in Puerto Rico, Vieques, and Culebra. Taking the mean from each of those MHW observations results in 0.13 m. This is the contour value used to delineate the shoreline and is recorded as the contour attribute in this shapefile. Person who carried out this activity:
    Rachel E. Henderson
    U.S. Geological Survey
    Researcher VII
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 (voice)
    rehenderson@contractor.usgs.gov
    Data sources used in this process:
    • vdatum
    Date: 01-Apr-2020 (process 3 of 10)
    Contour Shoreline extraction: A suite of ArcGIS tools (ArcGIS version 10.7.1) were compiled into a series of in-house models with ArcGIS ModelBuilder and used to help automate the contour method of shoreline extraction. First, the MHW shoreline elevation (0.13 m NAV88) was extracted from the DEMs using the ArcGIS Contour List tool (ArcToolbox > Spatial Analyst > Surface > Contour List). This step was iterated for each individual DEM in the study area. As a result, individual shapefiles were created for each DEM. Person who carried out this activity:
    Julia L. Heslin
    U.S. Geological Survey
    Geographer
    384 Woods Hole Road
    Woods Hole, MA

    508-457-2262 (voice)
    jheslin@usgs.gov
    Data sources used in this process:
    • 2018 DEM
    Data sources produced in this process:
    • PR MHW Contours
    Date: 01-May-2020 (process 4 of 10)
    Contour Shoreline smoothing: Each contour shoreline was generalized using the Smooth Line tool (ArcToolbox > Cartography > Generalization > Smooth Line), applying the PAEK algorithm with a 5 m tolerance. The shoreline features were then merged (ArcToolbox > Data Management > General > Merge) into one feature class. Person who carried out this activity:
    Julia L. Heslin
    U.S. Geological Survey
    Geographer
    384 Woods Hole Road
    Woods Hole, MA

    508-457-2262 (voice)
    jheslin@usgs.gov
    Data sources used in this process:
    • PR MHW Contours
    Data sources produced in this process:
    • PR Smoothed Contour
    Date: 01-Jun-2020 (process 5 of 10)
    Contour Shoreline date calculation: The date for each shoreline is required to identify the dataset, and is used for shoreline change analysis with DSAS (Himmelstoss and others 2018). The date for each contour shoreline was calculated using the corresponding flight paths layer provided by the United States Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX).
    The flight paths were downloaded from the “JALBTCX 2018 Flight Lines: Dates Flown” ArcGIS Online layer (https://usgs.maps.arcgis.com/home/item.html?id=4e70d40f9c8340b58c58935e99b0d960). The flight lines from Puerto Rico were selected and saved as a line shapefile. The flight lines were also projected to match the same projection as the contour shorelines (ArcToolbox > Data Management > Projections and Transformations > Project).
    The dates associated with the flight lines in the attribute table were used to apply the date to the contour shoreline features. In some instances, however, there were multiple flight lines to one shoreline feature as multiple flight line paths overlapped with each other. In this case, the average date was calculated and applied to those shoreline features.
    To do this, the date field from the flight lines was converted to the Julian day (in this case, Julian day refers to the day of the year number).
    In order to spatially join the flight lines to the contour shorelines, the flight lines were converted from a line to polygon shapefile using the Minimum Bounding Geometry Tool (ArcToolbox > Data Management > Features > Minimum Bounding Geometry). A “Count” field was added and calculated with a value of 1 in the flight line boundary polygon shapefile. Then, the contour shorelines were split where they intersected with the flight line boundaries. This was done by creating a separate point shapefile where the contours intersected with the flight line boundary (ArcToolbox > Analysis > Overlay > Intersect) and then split the contours at these intersection points (ArcToolbox > Data Management > Features > Split Line at Point).
    Each of these split contours were then spatially joined to the corresponding flight line boundary or boundaries within which they fell (ArcToolbox > Analysis > Overlay > Spatial Join). The sum of the Julian day and Count fields was designated as the merge rule when spatially joining the flight line boundaries to the contours.
    The summed Julian day field was divided by the summed Count field to derive the average Julian day for each of the contour shorelines. The average Julian day was then converted back to a date as a text field, compatible with DSAS. Person who carried out this activity:
    Julia L. Heslin
    U.S. Geological Survey
    Geographer
    384 Woods Hole Road
    Woods Hole, MA

    508-457-2262 (voice)
    jheslin@usgs.gov
    Data sources used in this process:
    • PR Smoothed Contour
    • 2018 lidar flight line information
    Data sources produced in this process:
    • PR Contour with DATE
    Date: 01-Jul-2020 (process 6 of 10)
    Contour Shoreline attributes: Additional attributes are added UNCY (see Horizontal Positional Accuracy Report), PROXY (MHW), AGENCY, TYPE (lidar), METHOD (contour). Person who carried out this activity:
    Julia L. Heslin
    U.S. Geological Survey
    Geographer
    384 Woods Hole Road
    Woods Hole, MA

    508-457-2262 (voice)
    jheslin@usgs.gov
    Data sources used in this process:
    • PR Contour with DATE
    Data sources produced in this process:
    • PR Contour with ATTRIBUTES
    Date: 01-Aug-2020 (process 7 of 10)
    Contour Shoreline edits: The shoreline was then manually edited with the lidar data displayed with categorized elevation values to highlight the MHW values and a modern base map image for reference. Segments of the contour that did not fall near the open ocean MHW were removed. As noted areas with insufficient coverage due to data gaps in the DEM at or near the mean high water line, were flagged for additional analysis using the Profile method (Farris, and others 2018). Person who carried out this activity:
    Rachel E. Henderson
    U.S. Geological Survey
    Researcher VII
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 (voice)
    rehenderson@contractor.usgs.gov
    Data sources used in this process:
    • PR Contour with ATTRIBUTES
    Data sources produced in this process:
    • PR Contour Shoreline
    Date: 01-Sep-2020 (process 8 of 10)
    Profile Shoreline extraction: The profile method of extraction was used for over 31 kilometers of shoreline where data gaps were present in the contour shoreline. The a profile method extracts the operational Mean High Water (MHW) shoreline from the lidar point cloud data, using a Matlab-based approach (Matlab version 2015b) similar to the one developed by Stockdon and others (2002). Elevation values for the height of MHW were determined from vdatum (version 4.1) provided by NOAA (https://vdatum.noaa.gov/). We continued the practice set out by Weber and others, (2005) of using one MHW value for a continuous section of coast (as opposed to using a continuously varying value). We chose this value such that it is always within 6 cm of the value returned by vdatum at any point along the coast. For example, we used MHW = 0.13 m for all of Puerto Rico even though the MHW varies across the island from 0.09m to 0.19m from all tide observation stations in Puerto Rico. Profile shorelines were not extracted for the islands of Vieques and Culebra.
    This profile method uses a coast-following reference line with 20 m spaced cross shore profiles. All lidar data points that are within 1 m of each profile are associated with that profile. All work is done on the 2 m 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. Foreshore beach slope is defined as the slope of the regression line. Each MHW shoreline point that was extracted using this profile method has an uncertainty associated with it. See the Horizontal Positional Accuracy Report for details.
    The final output is a shoreline comprised of the MHW shoreline points, with attributes added for Shoreline Type (MHW), Date, and Uncertainty. Person who carried out this activity:
    Kathryn M. Weber
    U.S. Geological Survey
    Oceanographer
    384 Woods Hole Road
    Woods Hole, MA

    508-457-2351 (voice)
    kweber@usgs.gov
    Data sources used in this process:
    • 2018 point cloud data
    Data sources produced in this process:
    • PR Profile Shoreline
    Date: 01-Oct-2020 (process 9 of 10)
    Combined the Profile and Contour Shorelines and updated attributes for profile segments (PROXY, AGENCY, TYPE, METHOD). Person who carried out this activity:
    Rachel E. Henderson
    U.S. Geological Survey
    Researcher VII
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 (voice)
    rehenderson@contractor.usgs.gov
    Data sources used in this process:
    • PR Profile Shoreline
    • PR Contour Shoreline
    Data sources produced in this process:
    • PR MHW Shoreline
    Date: 01-Nov-2020 (process 10 of 10)
    Final coordinate transformation from "NAD_1983_NSRS2007_StatePlane_Puerto_Rico_Virgin_Isls_FIPS_5200" to "GCS_WGS_1984". Person who carried out this activity:
    Rachel E. Henderson
    U.S. Geological Survey
    Researcher VII
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 (voice)
    rehenderson@contractor.usgs.gov
    Data sources used in this process:
    • PR MHW Shoreline
    Data sources produced in this process:
    • PR_2018_USACE_MHW_Shoreline
  3. What similar or related data should the user be aware of?
    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:

    Himmelstoss, Emily A., Farris, Amy S., Henderson, Rachel E., Kratzmann, Meredith G., Ergul, Ayhan, Zhang, Ouya, and Zichichi, Jessica L., 20181230, Digital Shoreline Analysis System (version 5.0): U.S. Geological Survey software: software release version 5.0, U.S. Geological Survey, Reston, VA.

    Online Links:

    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:

    Heslin, Julia L., Henderson, Rachel E., and Himmelstoss, Emily A., 20211101, Historical Shorelines for Puerto Rico from 1901 to 1987: U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

    Bracero-Marrero, Loderay, Barreto-Orta, Maritza, Hernández-Montcourt, Nias, and Maldonado-González, Ruben, 20211101, A GIS compilation of Vector Shorelines and Shoreline Classification for Puerto Rico from 1970 and 2010: data release https://doi.org/10.5066/P9SEUAHC, U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

    Heslin, Julia L., Henderson, Rachel E., and Himmelstoss, Emily A., 2021, Puerto Rico Shoreline Change: A GIS Compilation of Shorelines, Baselines, Intersects, and Change Rates using the Digital Shoreline Analysis System version 5.1: U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

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

  1. How well have the observations been checked?
    The attributes are based on the requirements of the Digital Shoreline Analysis System (DSAS) software, please refer to cross reference for citation.
  2. How accurate are the geographic locations?
    Contour Shoreline Positional Uncertainty: We accounted for three sources of uncertainty in the contour method: 1) The vertical uncertainty of the lidar data, which is stated as 0.196 m in the lidar metadata; 2) a mean high water (MHW) uncertainty of 0.06 m to account for our simplified use of a single MHW value when in reality MHW continuously varies around the islands; and 3) the horizontal uncertainty due to the 1 meter cell size of the DEM.
    This 1 meter cell limits us to a plus or minus 0.5 m confidence in the location of the shoreline. Since the first two sources of uncertainty are vertical measurements, we converted both of them to a horizontal uncertainty using the beach slope. The beach slope was found by averaging all slope values calculated from the lidar profile shorelines (see process steps for a description). We divided both of the vertical uncertainty terms by the average beach slope (expressed as rise/run) in order to get the horizontal component of the two vertical uncertainty terms. In order to estimate the total horizontal uncertainty, the three, now horizontal, components of uncertainty were added in quadrature. These are stored in the attribute table. The average uncertainty for the contour shoreline for the state is 1.98 meters.
    Profile Shoreline Positional Uncertainty: This uncertainty includes three components: 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 and; 3)the uncertainty due to extrapolation. These three 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 2km). Range of uncertainty for the entire profile shoreline dataset is 0.9 to 5.5 meters, with an average of 2.45 meters. See the data field UNCY for individual shoreline uncertainties.
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    Although not a continuous shoreline for Puerto Rico, this shoreline file is complete and contains all shoreline segments where shoreline position data needed to be extracted. Areas with insufficient coverage to extract a contour shoreline are due primarily to data gaps in the DEM at or near the mean high water line. These locations were analyzed using an alternate shoreline extraction method: the profile method (Farris, and others 2018), which extracts the MHW position from more complete point could data, and allows for interpolation of MHW position in situations of minor data gaps. Remaining gaps in these data are a consequence of non-existing data or existing data that did not meet quality assurance standards. See source citations and process steps for a link to the lidar tile index, which describes the exact lidar data coverage.
  5. How consistent are the relationships among the observations, including topology?
    Adjacent shoreline segments do not overlap and are not necessarily continuous. Visual QC was performed in ArcMap, displaying shorelines over imagery (Esri World Imagery in map view) to verify that data landward of the expected shoreline (such as low lying inland areas, or inland marsh areas) were removed. Shorelines located near the no data extent of the elevation dataset were removed as well.

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:
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.
  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)
    sciencebase@usgs.gov
  2. What's the catalog number I need to order this data set? The dataset contains the polyline shapefile of shoreline data for Puerto Rico derived from 2018 USACE FEMA lidar using both contour (DEM) and profile (point cloud) shoreline extraction methods, and the FGDC CSDGM metadata in XML format
  3. What legal disclaimers am I supposed to read?
    Neither the U.S. Government, the Department of the Interior, nor the USGS, nor any of their employees, contractors, or subcontractors, make any warranty, express or implied, nor assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, nor represent that its use would not infringe on privately owned rights. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the USGS in the use of these data or related materials.
    Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
  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: 19-Nov-2021
Metadata author:
Rachel E. Henderson
U.S. Geological Survey
384 Woods Hole Road
Woods Hole, MA
USA

508-548-8700 (voice)
rehenderson@contractor.usgs.gov
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_P9AZYW74/PR_2018_USACE_MHW_Shoreline_metadata.faq.html>
Generated by mp version 2.9.50 on Mon Nov 29 09:51:00 2021