DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Myrtle Island, VA, 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: Myrtle Island, VA, 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). The data were made available to this project prior to being released by Doran and others (2017). Slight differences between the two versions may be caused by data clean-up that was performed by this project in some cases.
  1. How might this data set be cited?
    Sturdivant, Emily J., Zeigler, Sara L., Gutierrez, Benjamin T., and Weber, Kathryn M., 20191220, DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Myrtle Island, VA, 2014: data release DOI:10.5066/P9V7F6UX, 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.

    Sturdivant, Emily J., Zeigler, Sara L., Gutierrez, Benjamin T., and Weber, Kathryn M., 2019, Barrier island geomorphology and shorebird habitat metrics: Sixteen sites on the U.S. Atlantic Coast, 2013–2014: data release DOI:10.5066/P9V7F6UX, 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—Sixteen sites on the U.S. Atlantic Coast, 2013–2014: U.S. Geological Survey data release, https://doi.org/10.5066/P9V7F6UX.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -75.82839272
    East_Bounding_Coordinate: -75.81686785
    North_Bounding_Coordinate: 37.20430161
    South_Bounding_Coordinate: 37.18513614
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/5daa37d0e4b09fd3b0c9cedd/?name=DC_DT_SLpts_asis_browse.png (PNG)
    Example geomorphology points (mean high water shoreline, dune toe, and dune crest) overlain on the DEM. This example is for Assateague Island, MD and may not represent this dataset.
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 08-Jan-2014
    Ending_Date: 27-Jul-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
      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?
    myr14_DCpts
    Attribute values of 318 dune crest positions recorded in the Esri shapefile myr14_DCpts.shp. (Source: USGS)
    FID
    Internal feature number (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Shape
    Feature geometry. (Source: Esri) Coordinates defining the features.
    state
    State segment file identification (ID) number. (Source: Producer defined)
    ValueDefinition
    12Virginia
    seg
    Segment ID number used in processing (also labeled "segment"). (Source: Producer defined)
    Range of values
    Minimum:33
    Maximum:37
    profile
    Grid row number corresponding to a cross-shore profile location within the given segment. (Source: Producer defined)
    Range of values
    Minimum:1
    Maximum:94
    lon
    Longitude in WGS 84. Negative values indicate western hemisphere. (Source: Producer defined)
    Range of values
    Minimum:-75.828393
    Maximum:-75.81679
    Units:decimal degrees
    lat
    Latitude in WGS 84 (Source: Producer defined)
    Range of values
    Minimum:37.185136
    Maximum:37.204282
    Units:decimal degrees
    easting
    Easting in NAD 83 UTM Zone 18N (Source: Producer defined)
    Range of values
    Minimum:426471.264295
    Maximum:427512.565393
    Units:meters
    northing
    Northing in NAD 83 UTM Zone 18N (Source: Producer defined)
    Range of values
    Minimum:4115731.720474
    Maximum:4117849.060002
    Units:meters
    dhigh_x
    Cross-shore feature location relative to the generalized reference line, only relevant during processing. (Source: Producer defined)
    Range of values
    Minimum:-934.851967
    Maximum:-270.564218
    Units:meters
    dhigh_z
    Feature elevation (NAVD88). (Source: Producer defined)
    Range of values
    Minimum:0.86518
    Maximum:1.913864
    Units:meters
    z_error
    Root mean squared vertical error of feature elevation (NAVD88). (Source: Producer defined)
    Range of values
    Minimum:0.01009
    Maximum:0.324658
    Units:meters
    myr14_DTpts
    Attributes for 32 dune toe positions recorded in the Esri shapefile myr14_DTpts.shp. (Source: USGS)
    FID
    Internal feature number (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Shape
    Feature geometry. (Source: Esri) Coordinates defining the features.
    state
    State segment file identification (ID) number. (Source: Producer defined)
    ValueDefinition
    12Virginia
    seg
    Segment ID number used in processing (also labeled "segment"). (Source: Producer defined)
    Range of values
    Minimum:34
    Maximum:36
    profile
    Grid row number corresponding to a cross-shore profile location within the given segment. (Source: Producer defined)
    Range of values
    Minimum:5
    Maximum:94
    lon
    Longitude in WGS 84. Negative values indicate western hemisphere. (Source: Producer defined)
    Range of values
    Minimum:-75.821064
    Maximum:-75.816539
    Units:decimal degrees
    lat
    Latitude in WGS 84 (Source: Producer defined)
    Range of values
    Minimum:37.190334
    Maximum:37.197438
    Units:decimal degrees
    easting
    Easting in NAD 83 UTM Zone 18N (Source: Producer defined)
    Range of values
    Minimum:427126.739892
    Maximum:427534.678541
    Units:meters
    northing
    Northing in NAD 83 UTM Zone 18N (Source: Producer defined)
    Range of values
    Minimum:4116302.674986
    Maximum:4117087.390241
    Units:meters
    dlow_x
    Cross-shore feature location relative to the generalized reference line, only relevant during processing. (Source: Producer defined)
    Range of values
    Minimum:-548.775347
    Maximum:-376.100088
    Units:meters
    dlow_z
    Feature elevation (NAVD88). (Source: Producer defined)
    Range of values
    Minimum:1.012952
    Maximum:1.23232
    Units:meters
    z_error
    Root mean squared vertical error of feature elevation (NAVD88). (Source: Producer defined)
    Range of values
    Minimum:0.028808
    Maximum:0.139695
    Units:meters
    myr14_SLpts
    Attribute values for 165 shoreline positions recorded in the Esri shapefile myr14_SLpts.shp. (Source: USGS)
    FID
    Internal feature number (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Shape
    Feature geometry. (Source: Esri) Coordinates defining the features.
    state
    State segment file identification (ID) number. (Source: Producer defined)
    ValueDefinition
    12Virginia
    seg
    Segment ID number used in processing (also labeled "segment"). (Source: Producer defined)
    Range of values
    Minimum:33
    Maximum:36
    profile
    Grid row number corresponding to a cross-shore profile location within the given segment. (Source: Producer defined)
    Range of values
    Minimum:1
    Maximum:94
    sl_x
    Cross-shore feature location relative to the generalized reference line, only relevant during processing. (Source: Producer defined)
    Range of values
    Minimum:-573.999718
    Maximum:-305.391101
    Units:meters
    ci95_slx
    95% confidence interval for the shoreline position. (Source: Producer defined)
    Range of values
    Minimum:0.000346
    Maximum:0.264165
    Units:meters
    slope
    Mean beach slope calculated between dune toe and shoreline (NAVD88). (Source: Producer defined)
    Range of values
    Minimum:-0.088553
    Maximum:-0.004906
    Units:radians
    easting
    Easting in NAD 83 UTM Zone 18N (Source: Producer defined)
    Range of values
    Minimum:426541.838151
    Maximum:427597.773927
    Units:meters
    northing
    Northing in NAD 83 UTM Zone 18N (Source: Producer defined)
    Range of values
    Minimum:4115756.871306
    Maximum:4117199.927066
    Units:meters
    MHW
    Mean high water offset in meters. (Source: Weber and others (2005))
    Range of values
    Minimum:0.34
    Maximum:0.34
    Units:meters
    Entity_and_Attribute_Overview:
    This section provides a separate detailed entity and attribute information section 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 for that particular dataset. Fields may be reordered and the FID field may be replaced by a software-specific OBJECTID value, in which values do not directly match. The Shape attribute is unique to the shapefile format and is populated with NoData values in the CSV.
    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?
    Sara L. Zeigler
    U.S. Geological Survey
    384 Woods Hole Road
    Woods Hole, MA
    United States

    508-548-8700 x2290 (voice)
    szeigler@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 Myrtle Island, VA 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), National Geodetic Survey (NGS), Remote Sensing Division, 20170320, 2014 NOAA Post Hurricane Sandy Topobathymetric LiDAR Mapping for Shoreline Mapping.

    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 was released in Doran and others (2017).
    Processing was performed in MATLAB version 2017a. Source lidar point clouds were adjusted to NAVD88 through a MHW-offset correction factor. The NAVD88 elevation of MHW is 0.34 m for the region encompassing Myrtle Island (Weber and others, 2005).
    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 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 distance of a prior shoreline is selected as the most likely shoreline. 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.
    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:
    Kara Doran
    U.S. Geological Survey
    600 4th Street South
    St. Petersburg, FL
    United States

    727-502-8117 (voice)
    727-502-8182 (FAX)
    kdoran@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, 2019; 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. Shoreline points were removed 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). This is because sandy shorelines are expected to be generally linear features and these irregularities are often caused by an adjoining bar.
    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.
    Sturdivant, Emily J., 2019, bi-transect-extractor: software release DOI:10.5066/P915UYMY, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Custom-built package used for data processing. The Jupyter notebook file distributed with these data were part of the processing to create these data. The notebook relies on this software package.
    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 geomorphology points dataset is available as 14CNT01_morphology.zip. These data were made available to us prior to publication and as a result, processing steps may differ 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 (myr14_SLpts.shp) cross-shore positional accuracy is estimated by calculating the 95% confidence interval of the linear regression of the shoreline position. It is reported in the field 'ci95_slx'.
  3. How accurate are the heights or depths?
    Vertical accuracy is determined for each dune crest (myr14_DCpts.shp) feature and dune toe (myr14_DTpts.shp) feature based upon the scatter of data in the lidar grid cell. It is reported in the field 'z_error'.
  4. Where are the gaps in the data? What is missing?
    These data include dune crest positions and elevations (myr14_DCpts.shp), dune toe positions and elevations (myr14_DTpts.shp), and MHW shoreline positions (myr14_SLpts.shp). Processing attempted to locate positions every 10 m alongshore, but alongshore gaps greater than 10 m exist where features could not be accurately located along the cross-shore processing profile. Dune toe position is only determined for a given profile if certain criteria are met (see first process step for details). During post-processing, shoreline points were removed where groups of three or fewer consecutive points were separated from the shoreline trend in the surrounding areas.
  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. Alongshore gaps of feature positions exist where the feature could not be accurately located along the profile. Additionally, shoreline points were removed where groups of three or fewer consecutive points were separated from the shoreline trend in the surrounding areas.
    Dune crest positions may indicate the peak of the berm rather than a dune crest. Dune toe position is only determined for a given profile if certain criteria are met (see first process step for details). The shoreline elevation is considered the elevation of mean high water (MHW) as documented by Weber and others (2005).

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 (myr14_DCpts.shp and other shapefile components, myr14_DCpts.csv), dune toe points (myr14_DTpts.shp and other shapefile components, myr14_DTpts.csv) and shoreline points (myr14_SLpts.shp and other shapefile components, myr14_SLpts.csv). Additionally, the CSDGM FGDC metadata (myr14_DC_DT_SLpts_meta.xml) in XML format and the browse graphic (DC_DT_SLpts_asis_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-Mar-2024
Metadata author:
Sara L. Zeigler
U.S. Geological Survey
384 Woods Hole Road
Woods Hole, MA
USA

508-548-8700 x2290 (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 person is no longer with USGS. (updated on 20240319)
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_P9V7F6UX/myr14_DC_DT_SLpts_meta.faq.html>
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