DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2014

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Frequently anticipated questions:

What does this data set describe?

Title:
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2014
Abstract:
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.
Supplemental_Information:
Another version of these datasets is available at https://doi.org/10.5066/f7gf0s0z (Doran and others 2017). These data are scheduled to be released in an existing data publication. Because that release has not yet occurred and the data were made available to us prior to publication, we are publishing them here. As a result some of the processing is different from what is described in the associated methods report (Zeigler and others, 2019). For example, rather than being published in a stripped-down tabular format, we are publishing them as a projected shapefile.
  1. How might this data set be cited?
    Sturdivant, Emily J., Zeigler, Sara L., Gutierrez, Benjamin T., and Weber, Kathryn M., 2019, DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2014: data release DOI:10.5066/P944FPA4, 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.

    Sturdivant, Emily J., Zeigler, Sara L., Gutierrez, Benjamin T., and Weber, Kathryn M., 2019, Barrier island geomorphology and shorebird habitat metrics—Four sites in New York, New Jersey, and Virginia, 2010–2014: data release DOI:10.5066/P944FPA4, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Sturdivant, E.J., Zeigler, S.L., Gutierrez, B.T., and Weber, K.M., 2019, Barrier island geomorphology and shorebird habitat metrics—Four sites in New York, New Jersey, and Virginia, 2010–2014: U.S. Geological Survey data release, https://doi.org/10.5066/P944FPA4.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -73.31591126
    East_Bounding_Coordinate: -72.71293618
    North_Bounding_Coordinate: 40.7753295
    South_Bounding_Coordinate: 40.62070676
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/5d0bc940e4b0941bde4fc625/?name=fiis_DC_DT_SLpts_browse.png (PNG)
    Example geomorphology points (mean high water shoreline, dune toe, and dune crest) overlain on the DEM from the source lidar dataset.
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 06-Apr-2014
    Ending_Date: 21-Apr-2014
    Currentness_Reference:
    Ground condition measured by source lidar data.
  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?
    2. What coordinate system is used to represent geographic features?
      Grid_Coordinate_System_Name: Universal Transverse Mercator
      Universal_Transverse_Mercator:
      UTM_Zone_Number: 18
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.9996
      Longitude_of_Central_Meridian: -75.0
      Latitude_of_Projection_Origin: 0
      False_Easting: 500000.0
      False_Northing: 0
      Planar coordinates are encoded using coordinate pair
      Abscissae (x-coordinates) are specified to the nearest 0.6096
      Ordinates (y-coordinates) are specified to the nearest 0.6096
      Planar coordinates are specified in meters
      The horizontal datum used is North_American_Datum_1983.
      The ellipsoid used is GRS_1980.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.257222101.
      Vertical_Coordinate_System_Definition:
      Altitude_System_Definition:
      Altitude_Datum_Name: NAVD88
      Altitude_Resolution: 0.000001
      Altitude_Distance_Units: meter
      Altitude_Encoding_Method: Attribute values
  7. How does the data set describe geographic features?
    fiis14_DCpts
    Attribute values of 3,612 dune crest positions recorded in the shapefile fiis14_DCpts.shp. (Source: USGS)
    FID
    Internal feature number. (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Shape
    Feature geometry. (Source: Esri)
    ValueDefinition
    PointPoint geometry
    state
    State segment file identification (ID) number. (Source: Producer defined)
    ValueDefinition
    16New York
    segment
    Segment ID number used in processing. (Source: Producer defined)
    Range of values
    Minimum:40
    Maximum:44
    Units:integer
    profile
    Grid row number corresponding to a cross-shore profile location within the given segment. (Source: Producer defined)
    Range of values
    Minimum:1
    Maximum:3166
    Units:integer
    lon
    Longitude in WGS 84 (Source: Producer defined)
    Range of values
    Minimum:-73.3125545943
    Maximum:-72.7131091218
    Units:decimal degrees
    lat
    Latitude in WGS 84 (Source: Producer defined)
    Range of values
    Minimum:40.6212365711
    Maximum:40.7759089676
    Units:decimal degrees
    east
    Easting in NAD 83 UTM Zone 18N (Source: Producer defined)
    Range of values
    Minimum:642719.603309
    Maximum:692988.57902
    Units:meters
    north
    Northing in NAD 83 UTM Zone 18N (Source: Producer defined)
    Range of values
    Minimum:4498103.064189
    Maximum:4516397.430454
    Units:meters
    x
    Cross-shore feature location relative to the generalized reference line, only relevant during processing. (Source: Producer defined)
    Range of values
    Minimum:-1022.825128
    Maximum:57.227863
    Units:meters
    z_err
    Root mean squared vertical error of feature elevation (NAVD88). (Source: Producer defined)
    Range of values
    Minimum:0.013625
    Maximum:2.0135
    Units:meters
    dhigh_z
    Feature elevation (NAVD88). (Source: Producer defined)
    Range of values
    Minimum:1.774658
    Maximum:11.907064
    Units:meters
    fiis14_DTpts
    Attributes for 2,564 dune toe positions recorded in the shapefile fiis14_DTpts.shp. (Source: USGS)
    FID
    Internal feature number. (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Shape
    Feature geometry. (Source: Esri)
    ValueDefinition
    PointPoint geometry
    state
    State segment file identification (ID) number. (Source: Producer defined)
    ValueDefinition
    16New York
    segment
    Segment ID number used in processing. (Source: Producer defined)
    Range of values
    Minimum:40
    Maximum:44
    Units:integer
    profile
    Grid row number corresponding to a cross-shore profile location within the given segment. (Source: Producer defined)
    Range of values
    Minimum:1
    Maximum:3166
    Units:integer
    lon
    Longitude in WGS 84 (Source: Producer defined)
    Range of values
    Minimum:-73.3126657332
    Maximum:-72.7130277285
    Units:decimal degrees
    lat
    Latitude in WGS 84 (Source: Producer defined)
    Range of values
    Minimum:40.6211712262
    Maximum:40.7757518808
    Units:decimal degrees
    east
    Easting in NAD 83 UTM Zone 18N (Source: Producer defined)
    Range of values
    Minimum:642710.395471
    Maximum:692995.903137
    Units:meters
    north
    Northing in NAD 83 UTM Zone 18N (Source: Producer defined)
    Range of values
    Minimum:4498085.612319
    Maximum:4516380.170101
    Units:meters
    x
    Cross-shore feature location relative to the generalized reference line, only relevant during processing. (Source: Producer defined)
    Range of values
    Minimum:-1011.575128
    Maximum:65.977863
    Units:meters
    z_err
    Root mean squared vertical error of feature elevation (NAVD88). (Source: Producer defined)
    Range of values
    Minimum:0.027039
    Maximum:1.341
    Units:meters
    dlow_z
    Feature elevation (NAVD88). (Source: Producer defined)
    Range of values
    Minimum:1.675586
    Maximum:5.670033
    Units:meters
    fiis14_SLpts
    Attribute values for 4,978 shoreline positions recorded in the shapefile fiis14_SLpts.shp. (Source: USGS)
    FID
    Internal feature number. (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Shape
    Feature geometry. (Source: Esri)
    ValueDefinition
    PointPoint geometry
    state
    State segment file identification (ID) number. (Source: Producer defined)
    ValueDefinition
    16New York
    segment
    Segment ID number used in processing. (Source: Producer defined)
    Range of values
    Minimum:40
    Maximum:44
    Units:integer
    profile
    Grid row number corresponding to a cross-shore profile location within the given segment. (Source: Producer defined)
    Range of values
    Minimum:1
    Maximum:3165
    Units:integer
    x
    Cross-shore feature location relative to the generalized reference line, only relevant during processing. (Source: Producer defined)
    Range of values
    Minimum:-970.556152
    Maximum:149.920426
    Units:meters
    slope
    Mean beach slope calculated between dune toe and shoreline (NAVD88). (Source: Producer defined)
    Range of values
    Minimum:-0.232168
    Maximum:-0.00047
    Units:radians
    lon
    Longitude in WGS 84 (Source: Producer defined)
    Range of values
    Minimum:-73.315764
    Maximum:-72.712936
    Units:decimal degrees
    lat
    Latitude in WGS 84 (Source: Producer defined)
    Range of values
    Minimum:40.620563
    Maximum:40.77533
    Units:decimal degrees
    east
    Easting in NAD 83 UTM Zone 18N (Source: Producer defined)
    Range of values
    Minimum:642446.417555
    Maximum:693004.852218
    Units:meters
    north
    Northing in NAD 83 UTM Zone 18N (Source: Producer defined)
    Range of values
    Minimum:4498016.457292
    Maximum:4516333.479934
    Units:meters
    x_err
    Root mean squared vertical error of shoreline position (x). (Source: Producer defined)
    Range of values
    Minimum:6.0714e-06
    Maximum:1.1796
    Units:meters
    Entity_and_Attribute_Overview:
    This section provides a separate detailed entity and attribute information sections for each dataset described in these metadata. Each shapefile has a companion CSV file that contains the same information. The first row of the CSV is a header line and corresponds to the attributes described in the detailed entity and attribute section (except for the Shape attribute) for that particular dataset. Fields in the CSV may be reordered and the FID field may be renamed to OBJECTID.
    Entity_and_Attribute_Detail_Citation: Methods Open-File Report by Zeigler and others, 2019

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Emily J. Sturdivant
    • Sara L. Zeigler
    • Benjamin T. Gutierrez
    • Kathryn M. Weber
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    Emily J. Sturdivant
    U.S. Geological Survey
    Geographer
    384 Woods Hole Road
    Woods Hole, MA
    USA

    (508) 548-8700 x2230 (voice)
    (508) 457-2310 (FAX)
    esturdivant@usgs.gov

Why was the data set created?

These datasets measure positions of geomorphic features, specifically dune crests, dune toes, and mean high water (MHW) shoreline pertaining to sandy beaches at Fire Island, NY in 2014. They can be used to calculate beach width and height. The source data were created for the purpose of modeling coastal hazards related to dune overtopping.

How was the data set created?

  1. From what previous works were the data drawn?
    Lidar point cloud (source 1 of 1)
    Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Office for Coastal Management (OCM), and U.S. Geological Survey, 20160109, 2014 USGS CMGP Lidar: Post Sandy (Long Island, NY).

    Online Links:

    Type_of_Source_Media: digital data
    Source_Contribution:
    Lidar survey that was used to estimate dune morphology variables.
  2. How were the data generated, processed, and modified?
    Date: 2017 (process 1 of 3)
    A customized MATLAB routine was used to extract beach and dune morphology. The routine determines the position of the mean high water (MHW) shoreline and the position and elevation of dune toe and dune crest. The routine is summarized below. Refer to Stockdon and others (2012) for details and figures. A version of these data are released in Doran and others (2017).
    Processing was performed in MATLAB version 2017a. Source lidar point clouds were adjusted to MHW. The NAVD88 elevation of MHW is 0.46 m for the region encompassing Fire Island (Weber and others, 2005). The input lidar dataset was the lidar point cloud (see Source Information section). The automated routine (see below) was executed iteratively to optimize the parameters based on visual comparison with high-resolution imagery. Results were considered low quality and required modifications to the parameters if numerous feature positions appeared to be erroneous or if there were large alongshore gaps in the output features. Once optimal parameters were determined, the routine was run for a final time.
    The shoreline position extraction selects the MHW shoreline grid cell within a dynamic distance of a prior shoreline. Stockdon and others (2012, p. 18) used a distance of 3 standard deviations of all shoreline positions within the grid segment. Starting with 3 standard deviations, the search distance was optimized to produce both quality and quantity of shoreline points as determined by the operator through trial and error. This usually resulted in a search distance between 0.5 and 3 standard deviations of the shoreline points within the grid segment. The prior shoreline was a first approximation and was selected as the most recent shoreline in a shoreline database.
    The following summarizes the feature extraction routine:
    First, lidar point cloud data are interpolated to 10 m (alongshore) by 2.5 m (cross-shore) grids oriented parallel to a roughly shore-parallel reference line that is used for all such feature extractions (Doran and others, 2017). Interpolation uses a Hanning window that is twice as wide as the grid resolution to minimize noise. Automated routines then identify the position of the three features (dune crest, shoreline, and dune toe) for each elevation profile. Each step is performed by a separate MATLAB program.
    To determine the dune crest position, the algorithm selects the peak of the most seaward sand dune. It does so by classifying inflection points in cross-shore slope as morphologic crests and troughs and identifying the highest crest elevation as the primary dune. In the absence of a dune, the beach berm or seaward edge of the bluff or hard structure (e.g., road, parking lot, seawall) was extracted. The selection is limited to areas within 200 m of the shoreline, seaward of built structures, less than 0.5 m vertical error, and higher than the MHW elevation.
    For each profile, the position of the MHW shoreline is determined. The cross-shore location of the MHW shoreline is automatically extracted with the incorporation of the RMS error surface. The probability that a grid cell elevation value is equal to MHW elevation is estimated from a normal distribution of beach elevation. The grid cell with the highest probability within a defined dynamic distance (standard deviation multiplier of all shoreline points within the grid segment) of a prior shoreline is selected as the most likely shoreline. The dynamic search distance varies based on the generalized beach width of the region. A more precise location of MHW is interpolated from a linear regression of the selected point and adjacent grid cells. A confidence interval for the estimate is defined from the regression error and the error in the lidar data.
    Once the dune crest position is established, the dune toe position is determined. First, if the dune crest position is understood to represent a beach berm because the elevation is less than the high water line (HWL), dune toe position is not determined for the given profile. In the remainder of cases, dune toe is identified as the point of maximum slope change between the shoreline and the dune crest unless the elevation of that point is within 0.5 m of the dune crest elevation or the curvature of the profile around the dune toe was negative.
    The feature positions resulting from the automated routine are manually verified by overlaying the horizontal positions on high-resolution coastal imagery. Profiles with identified inconsistencies are viewed in a customized MATLAB Graphical User Interface (GUI) that displays the features with the lidar data (interpolated and point cloud) and allows the operator to relocate or delete feature positions. High density of built structures and complex topography often cause errors in the feature positions that require manual editing.
    The positions are exported from Matlab with geographic coordinate values (WGS84) in a table of comma-separated values and converted to an Esri shapefile in NAD83 UTM Zone 18N (Make XY Event Layer tool in ArcGIS 10.5). Coordinates were transformed from WGS84 to NAD83 using the transformation WGS_1984_(ITRF00)_To_NAD_1983 (WKID: 108190, accuracy: 0.1 m). Person who carried out this activity:
    Kathryn M Weber
    U.S. Geological Survey
    384 Woods Hole Road
    Woods Hole, MA
    United States

    508-457-8700 x2351 (voice)
    508-457-2310 (FAX)
    kweber@usgs.gov
    Data sources used in this process:
    • Lidar point cloud
    Date: 2018 (process 2 of 3)
    Positions were converted from a table of comma-separated values to a shapefile using the function functions_warcpy.MorphologyCSV_to_FCsByFeature in the python package bi-transect-extractor (Sturdivant, 2018; version 1.0).
    The dune crest, dune toe, and shoreline positions were overlaid on the DEM in ArcGIS 10.5 to check for incongruences between the morphology points and the elevation. Features that displayed logical inconsistency relative to the other features were flagged. For example, dune toe and crest points located seaward of shoreline points would be flagged and evaluated with reference to the DEM to determine which of the features were the more accurate.
    Finally, the points were converted from shapefile format to comma-separated text using the ArcGIS tool Export Table (version 10.5). Both the shapefile and the CSV files are included in this data release. Person who carried out this activity:
    Emily J Sturdivant
    U.S. Geological Survey
    384 Woods Hole Road
    Woods Hole, MA
    US

    508-457-8700 x2230 (voice)
    508-457-2310 (FAX)
    esturdivant@usgs.gov
    Date: 10-Aug-2020 (process 3 of 3)
    Added keywords section with USGS persistent identifier as theme keyword. Person who carried out this activity:
    U.S. Geological Survey
    Attn: VeeAnn A. Cross
    Marine Geologist
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 x2251 (voice)
    508-457-2310 (FAX)
    vatnipp@usgs.gov
  3. What similar or related data should the user be aware of?
    Zeigler, Sara L., Sturdivant, Emily J., and Gutierrez, Benjamin T., 2019, Evaluating barrier island characteristics and piping plover (Charadrius melodus) habitat availability along the U.S. Atlantic coast—Geospatial approaches and methodology: Open-File Report 2019–1071, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Details the methods used to process these data for use in barrier island and piping plover habitat modeling.
    Weber, Kathryn M., List, Jeffrey H., and Karen L. M. Morgan, 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:

    Other_Citation_Details:
    Provides regional mean high water elevation used to determine shoreline position.
    Doran, Kara J., Long, Joseph W., Birchler, Justin J, Brenner, Owen T., Hardy, Matthew W., Karen L. M. Morgan, Stockdon, Hilary F., and Torres, Miguel L., 2017, Lidar-derived Beach Morphology (Dune Crest, Dune Toe, and Shoreline) for U.S. Sandy Coastlines: U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Affiliated datasets created using the same methods. A version of this geomorph points dataset may become available as 14CNT02_morphology.zip. These data were made available to us prior to publication. As a result some of the processing is different from what is described here.
    Stockdon, Hilary F., Doran, Kara J., Thompson, D. M., Sopkin, K. L., Plant, Nathaniel G., and Sallenger, Asbury H., 2012, National assessment of hurricane-induced coastal erosion hazards: Gulf of Mexico: Open-File Report 2012–1084, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details: Provides the methods for feature extraction (pp. 17–23).

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

  1. How well have the observations been checked?
    Horizontal and vertical accuracy were estimated and recorded automatically during processing (see sections Positional Accuracy and Entity and Attribute Information). All output feature positions were manually verified against external aerial imagery and elevation data; positions deemed incorrect were manually deleted or relocated.
  2. How accurate are the geographic locations?
    Horizontal accuracy is dependent on the lidar point uncertainty and the density of and scatter in the lidar data points.
    For the shoreline points (fiis14_SLpts.shp) cross-shore positional accuracy is determined for each feature elevation based upon the scatter of data in the lidar grid cell. It is reported in the field 'x_err'.
  3. How accurate are the heights or depths?
    Vertical accuracy is determined for each dune crest (fiis14_DCpts.shp) feature and dune toe (fiis14_DTpts.shp) feature based upon the scatter of data in the lidar grid cell. It is reported in the field 'z_err'.
  4. Where are the gaps in the data? What is missing?
    These data include dune crest positions and elevations (fiis14_DCpts.shp). In the absence of a dune, the seaward edge of the bluff or hard structure (e.g., seawall, road, parking lot) or the peak of the berm was chosen as the dune crest. Alongshore gaps of feature positions exist where the feature could not be accurately located along the profile.
    These data include dune toe positions and elevations (fiis14_DTpts.shp). Dune toe position is not determined for a given profile if any of the following conditions are met: dune crest elevation is less than the high water line (HWL) (the feature identified is interpreted as a beach berm); if the elevation of what would be considered the dune toe (the point of maximum slope change between the shoreline and the dune crest) is within 0.5 m of the dune crest elevation; if the curvature of the profile around the preliminary dune toe is negative.
    For the shoreline points (fiis14_SLpts.shp), alongshore gaps of feature positions exist where the feature could not be accurately located along the profile. Unlike the dune morphology positions, the shoreline positions do not include feature elevation. The shoreline elevation is considered the mean high water (MHW) elevation as documented by Weber and others (2005). Sandy shorelines are expected to be generally linear features. Consequently, an operator removed shoreline points where groups of three or fewer consecutive points (occupying 20 m or less alongshore) were separated from the shoreline trend in the surrounding areas (a general line suggested by the rest of the shoreline points and inferred by the operator).
  5. How consistent are the relationships among the observations, including topology?
    This dataset consists of three point shapefile datasets produced from elevation data and tidal datum values through an automated process described below. It was not explicitly checked for topological consistency, but feature locations were verified by displaying them with aerial imagery and digital elevation models. Incorrect feature positions were manually deleted or relocated.

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 (USGS) as the source of this information.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey - ScienceBase
    Denver Federal Center, Building 810, Mail Stop 302
    Denver, CO
    United States

    1-888-275-8747 (voice)
    sciencebase@usgs.gov
  2. What's the catalog number I need to order this data set? These datasets contain three individual shapefile point and corresponding CSV datasets: Dune crest points (fiis14_DCpts.shp and other shapefile components, fiis14_DCpts.csv), dune toe points (fiis14_DTpts.shp and other shapefile components, fiis14_DTpts.csv) and shoreline points (fiis14_SLpts.shp and other shapefile components, fiis14_SLpts.csv). Additionally, the CSDGM FGDC metadata (fiis14_DC_DT_SLpts_meta.xml) in XML format and the browse graphic (fiis_DC_DT_SLpts_browse.png) in PNG format are included. These datasets can be downloaded individually or packaged on-demand in a zip file (see the Digital Transfer Option section).
  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. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), and have been processed successfully on a computer system at the 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. The USGS or the U.S. Government shall not be held liable for improper or incorrect use of the data described and/or contained herein. Any use of trade, firm, or product 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?
    To utilize these data, the user must have software capable of reading shapefile or CSV format.

Who wrote the metadata?

Dates:
Last modified: 19-Nov-2021
Metadata author:
Emily Sturdivant
U.S. Geological Survey
Geographer
384 Woods Hole Road
Woods Hole, MA
USA

(508) 548-8700 x2230 (voice)
(508) 457-2310 (FAX)
whsc_data_contact@usgs.gov
Contact_Instructions:
The metadata contact email address is a generic address in the event the metadata contact is no longer with the USGS or the email is otherwise invalid.
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_P944FPA4/fiis14_DC_DT_SLpts_meta.faq.html>
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