Supplemental data for Over and Sherwood (2025), Washover and washout locations and landcover classifications after hurricanes Florence, Dorian, Harvey, Ike, and Sandy in North Carolina, Texas, and New York.

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Frequently anticipated questions:

What does this data set describe?

Title:
Supplemental data for Over and Sherwood (2025), Washover and washout locations and landcover classifications after hurricanes Florence, Dorian, Harvey, Ike, and Sandy in North Carolina, Texas, and New York.
Abstract:
The data in this release support the journal article "Outwash events inhibit vegetation recovery and prolong coastal vulnerability". The research details the vegetation cover in washover and washout locations in North Carolina, Texas, and New York after hurricanes Florence, Dorian, Harvey, Ike, and Sandy. Aerial imagery observations indicate that washout sites create ponds and have a slower vegetation recovery to pre-storm levels than washover sites. Select imagery was classified into sand, water, and vegetation. To reproduce the results and figures in the paper, the extents of the analysis are provided in a GeoPackage organized by location, hurricane, and type of extent including washout, washover, and ponds. The results of the landcover classifications and the percent vegetation cover within the indiviudal extents are also provided.
Supplemental_Information:
These data are in direct support of the related journal article: Over, J.R., and Sherwood, C.R., 2025, Outwash events inhibit vegetation recovery and prolong coastal vulnerability: Journal of Geophysical Research: Earth Surfaces, 130(6), e2024JF008162, https://doi.org/10.1029/2024JF008162.
  1. How might this data set be cited?
    Over, Jin-Si R., and Sherwood, Christopher R., 20250611, Supplemental data for Over and Sherwood (2025), Washover and washout locations and landcover classifications after hurricanes Florence, Dorian, Harvey, Ike, and Sandy in North Carolina, Texas, and New York.: data release DOI:10.5066/P1PGG57F, U.S. Geological Survey, Coastal and Marine Hazards and Resources Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Over, J.R., and Sherwood, C.R., 2025, Supplemental data for Over and Sherwood (2025), Washover and washout locations and landcover classifications after hurricanes Florence, Dorian, Harvey, Ike, and Sandy in North Carolina, Texas, and New York: U.S. Geological Survey data release, https://doi.org/10.5066/P1PGG57F.
    These data are in direct support of the related jounral article: Over, J.R., and Sherwood, C.R., 2025, Outwash events inhibit vegetation recovery and prolong coastal vulnerability: Journal of Geophysical Research: Earth Surfaces, 130(6), e2024JF008162, https://doi.org/10.1029/2024JF008162.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -97.03555499
    East_Bounding_Coordinate: -72.87221368
    North_Bounding_Coordinate: 40.73136616
    South_Bounding_Coordinate: 27.86610871
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/6705b0ccd34edddc3ed257c5?name=ROI_Example.JPG&allowOpen=true (JPEG)
    An example of some washout regions of interest on North Core Banks.
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 19-May-2008
    Currentness_Reference:
    dates reflect time series of classified data.
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: vector and tabular 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):
      • G-polygon (653)
    2. What coordinate system is used to represent geographic features?
      The map projection used is WGS 1984 Web Mercator Auxiliary Sphere.
      Projection parameters:
      Standard_Parallel: 0.0
      Longitude_of_Central_Meridian: 0.0
      False_Easting: 0.0
      False_Northing: 0.0
      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 D_WGS_1984.
      The ellipsoid used is WGS84.
      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?
    Over_and_Sherwood_Supp_Extents.gpkg
    Table containing attribute information associated with the dataset; main.BP_Ike_ROI, main.FI_Sandy_Washover, main.NCB_Dorian_Washout, main.NCB_Dorian_Washout_Ponds, main.NCB_NCB_IslandPlatform_ROI, and main.SJI_Harvey_Washout. (Source: USGS)
    OBJECTID
    Automatically generated non-repeating internal feature number. (Source: Esri)
    Range of values
    Minimum:1
    Maximum:460
    Shape
    Feature geometry (Source: Esri)
    ValueDefinition
    polygonA shape defined by one or more rings, where a ring is a path that starts and ends at the same point.
    Area_m2
    Geodesic area of polygon. (Source: Esri)
    Range of values
    Minimum:6
    Maximum:5,409,860
    Units:square meters
    Date
    Date in YYYYMMDD corresponding to the initial imagery or orthomosaic the polygon was digitized from (see larger work citation for a table of dates and imagery sources). A NaN occurs if polygon is not generated off of a specific date. (Source: Producer defined) Character string.
    Location
    Abbreviated code of the geographic location of the polygons. (Source: Producer defined)
    ValueDefinition
    NCBNorth Core Banks
    SJISan Jose Island
    BPBolivar Peninsula
    FIFire Island
    Hurricane
    Name of the hurricane(s) associated with the polygon(s). If multiple hurricanes are associated, they are separated by a /. (Source: World Meteorological Organization) Character string.
    Over_and_Sherwood_2025_Supp_VegetationCoverRaw.csv
    Table containing attribute information and classification data. (Source: USGS)
    Unique_ID
    Generated non-repeating identification number. (Source: USGS)
    Range of values
    Minimum:0
    Maximum:764
    ID
    Identification Number for individual washout or washover extents in each Hurricane and location pair that repeats for multiple dates of analysis. NaN occurs in polygons that are not washout or washover extents. (Source: USGS)
    Range of values
    Minimum:0
    Maximum:89
    Area_m2
    Geodesic area of polygon. (Source: Esri)
    Range of values
    Minimum:46
    Maximum:5,409,860
    Units:square meters
    Date
    Date in YYYYMMDD corresponding to the imagery or orthomosaic the analysis was completed on (see journal Supporting Information) for a table of dates and imagery sources). (Source: Producer defined) Character string.
    Location
    Abbreviated code of the geographic location of the analysis. (Source: Producer defined)
    ValueDefinition
    NCBNorth Core Banks
    SJISan Jose Island
    BPBolivar Peninsula
    FIFire Island
    Hurricane
    Name of the hurricane associated with the analysis. (Source: World Meteorological Organization) Character string.
    Type
    The type of feature or location being analyzed (see process steps and larger work citation for more detail). (Source: Producer defined)
    ValueDefinition
    ROIA region of interest.
    WashoutA digitized washout feature.
    WashoverA digitized washover feature.
    Dense_Vegetation
    Interpreted unsupervised landcover classification of vegetation with little to no clear patches between individual plants. A NaN value occurs if vegetation was not split between dense and sparse. (Source: Producer defined)
    Range of values
    Minimum:0
    Maximum:9,853,569
    Units:pixels
    Sparse_Vegetation
    Interpreted unsupervised landcover classification of vegetation with clear patches between individual plants. A NaN value occurs if vegetation was not split between dense and sparse. (Source: Producer defined)
    Range of values
    Minimum:0
    Maximum:6,380,229
    Vegetation
    Interpreted unsupervised landcover classification of vegetation (may be the sum of the sparse and dense vegetation classes). (Source: Producer defined)
    Range of values
    Minimum:0
    Maximum:16,028,076
    Units:pixels
    Sand
    Interpreted unsupervised landcover classification of sand or bare ground with the assumed substrate of sand. (Source: Producer defined)
    Range of values
    Minimum:91
    Maximum:7,730,937
    Units:pixels
    Water
    Interpreted unsupervised landcover classification of water. (Source: Producer defined)
    Range of values
    Minimum:0
    Maximum:2,618,180
    Units:pixels
    %_Cover
    The vegetation cover for each extent calculated by dividing the Vegetation class by the sum of the Vegetation, Sand, and Water classes multiplied by 100. (Source: Producer defined)
    Range of values
    Minimum:0.00
    Maximum:88.97
    Units:percent
    Entity_and_Attribute_Overview:
    The GeoPackage contains individual feature classes, labeled as main.Location_Hurricane_Type, that are being used as boundaries for the classification analysis. Location and Hurricane are in the attribute tables and Type includes Washout, Washover, Washout ponds, and ROI. The OBJECTID in the GeoPackage feature classes corresponds to the ID attribute in the csv.
    Entity_and_Attribute_Detail_Citation: USGS

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Jin-Si R. Over
    • Christopher R. Sherwood
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    Jin-Si R. Over
    U.S. Geological Survey, Woods Hole Coastal and Marine Science Center
    Geographer
    384 Woods Hole Rd.
    Woods Hole, MA

    508-548-8700 x2297 (voice)
    jover@usgs.gov

Why was the data set created?

The geographic extents and results of the analysis allow others to reproduce our analyses. Landcover classifications support the study of vegetation recovery on coasts after storm events.

How was the data set created?

  1. From what previous works were the data drawn?
    NCB Imagery 1 (source 1 of 5)
    Kranenburg, Christine J, Ritchie, Andrew C, Brown, Jenna A, Over, Jin-Si R, Sherwood, Christopher R, Warrick, Jonathan, and Wernette, Phillipe A, 2022, Aerial imagery of the North Carolina coast: 2019-10-11: U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center.

    Online Links:

    Type_of_Source_Media: Digital
    Source_Contribution: Used to delineate ponds on North Core Banks.
    NCB Imagery 2 (source 2 of 5)
    Kranenburg, Christine J, Ritchie, Andrew C, Brown, Jenna A, Over, Jin-Si R, Sherwood, Christopher R, Warrick, Jonathan, and Wernette, Phillipe A, 2022, Aerial imagery of the North Carolina coast: 2020-09-28: U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center.

    Online Links:

    Type_of_Source_Media: Digital
    Source_Contribution: Used to delineate ponds on North Core Banks.
    NCB Imagery 3 (source 3 of 5)
    Kranenburg, Christine J, Ritchie, Andrew C, Brown, Jenna A, Over, Jin-Si R, Sherwood, Christopher R, Warrick, Jonathan, and Wernette, Phillipe A, 2024, Aerial imagery of the North Carolina coast: 2022-10-27 to 2022-10-28: U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center.

    Online Links:

    Type_of_Source_Media: Digital
    Source_Contribution: Used to delineate ponds on North Core Banks.
    NCB Imagery 4 (source 4 of 5)
    Kranenburg, Christine J, Brown, Jenna A, Ritchie, Andrew C, Over, Jin-Si R, Buscombe, Daniel D., Sherwood, Christopher R, and Warrick, Jonathan, 2025, Aerial Imagery of the North Carolina Coast: 2024-11-06 to 2024-11-13: U.S. Geological Survey, Pacific Coastal and Marine Science Center.

    Online Links:

    Type_of_Source_Media: Digital
    Source_Contribution: Used to delineate ponds on North Core Banks
    NCB DEMs (source 5 of 5)
    Ritchie, Andrew C, Over, Jin-Si R, Kranenburg, Christine J, Brown, Jenna A, Buscombe, Daniel D., Sherwood, Christopher R, Warrick, Jonathan, and Wernette, Phillipe A, 2022, Aerial photogrammetry data and products of the North Carolina coast: U.S. Geological Survey, Pacific Coastal and Marine Science Center.

    Online Links:

    Type_of_Source_Media: Digital
    Source_Contribution: Used to delineate washout channels on North Core Banks
  2. How were the data generated, processed, and modified?
    Date: 2025 (process 1 of 2)
    GEOPACKAGE (Over_and_Sherwood_Supp_Extents.gpkg) NORTH CORE BANKS: Island platform region of interest (ROI) feature class (main.NCB_IslandPlatform_ROI) was created assess the landcover of the area adjacent to and affected by overwash and outwash events. The ROI aims to remove water (ocean) and back barrier marsh, which do not perform well in the unsupervised classification. The Hurricane Florence washover extents (main.NCB_Florence_Washover) were delineated by digitizing the extent of the interpreted sand class from an unsupervised classification (the number of classes is set to 3 with a minimum class size of 20 and sample interval of 10) of the 2018-10-07 orthomosaic (Ritchie and others, 2020) and clipping to the dune line in ArcPro (v 3.0.0). The Hurricane Dorian washout extents (main.NCB_Dorian_Washout) were delineated by the difference between NCB digital elevation models (Ritchie and others, 2022) from 2019-08-30 and 2019-09-12 following Sherwood and others (2023). Ponds in washout channels were hand digitized (main.NCB_Dorian_Washout_ponds) by J. Over, using the imagery from 2019-10-11, 2020-09-28, and 2022-10-20 (Kranenburg and others, 2022, 2023, 2024, 2025) that were turned into orthomosaics following Over and others (2021). SAN JOSE ISLAND: Individual washout channels were hand digitized by J. Over from 2017-08-29 georectified Google Earth imagery (main.SJI_Harvey_Washout). BOLIVAR PENINSULA: Hurricane Ike did not create individual washout channels, so two same sized ROI boxes were created next to each other on georectifed Google Earth Imagery to encompass the extent of washout that was replanted by the local government and an extent that was not remediated (main.BP_Ike_ROI). FIRE ISLAND: Washout extents were obtained from C. Kilheffer, and provided in main.FI_Sandy_Washover, to recreate the areas of vegetation recovery studied in Kilheffer and others (2019). Data sources used in this process:
    • NCB Imagery 1
    • NCB Imagery 2
    • NCB Imagery 3
    • NCB Imagery 4
    • NCB DEMs
    Date: 2025 (process 2 of 2)
    CLASSIFICATION DATA (Over_and_Sherwood_2025_Supp_VegetationCoverRaw.csv) Values are provided in the CSV by class, extent ID, and date. Percent cover is calculated by dividing the sum of the pixel count of vegetation classes by the pixel count sum of all classes and multiplied by 100. NORTH CORE BANKS: For each date (2018-10-08, 2019-08-30, 2019-10-11, 2020-09-28, 2022-10-20, 2024-11-06) an unsupervised classification was performed on the orthomosaic within the island platform ROI (main.NCB_IslandPlatform_ROI), the Hurricane Florence washover extents (main.NCB_Florence_Washover), and the Hurricane Dorian washout extents (main.NCB_Dorian_Washout) in ArcPro (v. 3.0.0) with 3 classes, a minimum class size of 20, and sample interval of 10. The three classes were visually interpreted into dense vegetation, sparse vegetation, and sand. Areas under the digitized ponds (when present), were assigned to water. A quality check was done with stratified random points using the Create Accuracy Assessment Points (n=200) and then the Compute Confusion Matrix Tool. For 2019-10-08 the overall accuracy (± 95% confidence interval (CI)) was 0.92±0.04, 2019-08-30 was 0.88±0.04, 2019-10-11 was 0.87±0.04, 2020-09-28 was 0.90±0.04, 2022-10-20 was 0.84±0.05, and 2024-11-06 was 0.88±0.04. SAN JOSE ISLAND: For each date (2017-03-25, 2017-08-29, 2020-10-31, 2022-03-23, and 2023-06-25) georectified Google Earth imagery was converted to a GeoTIFF. For each date an unsupervised classification was performed on the GeoTIFFs within the Hurricane Harvey washout extents (main.SJI_Harvey_Washout) in ArcPro (v. 3.0.0) with 3 classes, a minimum class size of 20, and sample interval of 10. The three classes were visually interpreted into vegetation, sand, and water. A quality check was done with stratified random points using the Create Accuracy Assessment Points (n=200) and then the Compute Confusion Matrix Tool. For 2017-03-25 the overall accuracy (± 95% CI) was 0.91±0.04, 2017-08-29 was 0.88±0.04, 2020-10-31 was 0.93±0.03, 2022-03-23 was 0.96±0.03, and 2023-06-25 was 0.94±0.04. Values are provided in the CSV by class, extent ID, and date. BOLIVAR PENINSULA: For each date (2008-05-19, 2010-01-08, 2013-04-19, 2018-01-02, and 2022-01-21) georectified Google Earth imagery was converted to a GeoTIFF. For each date an unsupervised classification was performed on the GeoTIFFs within the two Hurricane Ike ROIs (main.BP_Ike_ROI) in ArcPro (v. 3.0.0) with 3 classes, a minimum class size of 20, and sample interval of 10. The three classes were visually interpreted into vegetation, sand, and water. A quality check was done with random points using the Create Accuracy Assessment Points (n=100) and then the Compute Confusion Matrix Tool. For 2008-05-19 the overall accuracy (± 95% CI) was 0.92±0.05, 2010-01-08 was 0.91±0.05, 2013-04-19 was 0.96±0.04, 2018-01-02 was 0.97±0.03, and 2022-01-21 was 0.95±0.04. FIRE ISLAND: For each date (2017-10-01, 2019-09-19, and 2021-04-04) georectified Google Earth imagery was converted to a GeoTIFF. For each date an unsupervised classification was performed on the GeoTIFFs within the Hurricane Sandy washout extents (main.FI_Sandy_Washover) in ArcPro (v. 3.0.0) with 2 classes, a minimum class size of 20, and sample interval of 10. The two classes were visually interpreted into vegetation, and sand. A quality check was done with random points using the Create Accuracy Assessment Points (n=200) and then the Compute Confusion Matrix Tool. For 2017-10-01 the overall accuracy (± 95% CI) was 0.89±0.04, 2019-09-19 was 0.88±0.04, and 2021-04-04 was 0.89±0.04. Person who carried out this activity:
    Jin-Si R. Over
    U.S. Geological Survey, Woods Hole Coastal and Marine Science Center
    Geographer
    U.S. Geological Survey
    Woods Hole, MA

    508-548-8700 x2297 (voice)
    jover@usgs.gov
  3. What similar or related data should the user be aware of?
    Over, Jin-Si R., and Sherwood, Christopher R., 2025, Outwash events inhibit vegetation recovery and prolong coastal vulnerability: Journal of Geophysical Research: Earth Surfaces Volume 130, Issue 6, American Geophysical Union, online.

    Online Links:

    Other_Citation_Details:
    This publication is the primary journal article these data support.
    Over, Jin-Si R., Ritchie, Andrew C., Kranenburg, Christine J., Brown, Jenna A., Buscombe, Daniel D., Noble, Tommy, Sherwood, Christopher R., Warrick, Jonathan A., and Wernette, Phillipe A., 2021, Processing coastal imagery with Agisoft Metashape Professional Edition, version 1.6—Structure from motion workflow documentation: Open-File Report 2021-1039, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    This publication includes the general methodology for processing imagery in Metashape to produce DEMs and ortho products.
    Sherwood, Christopher R., Ritchie, Andrew C., Over, Jin-Si R., Kranenburg, Christine J., Warrick, Jonathan A., Brown, Jenna A., Wright, C. Wayne, Aretxabaleta, Alfredo L., Zeigler, Sara L., Wernette, Phillipe A., Buscombe, Daniel D., and Hegermiller, Christie A., 2023, Sound‐side inundation and seaward erosion of a barrier Island during Hurricane landfall: Journal of Geophysical Research: Earth Surface Volume 128, Issue 1, American Geophysical Union, online.

    Online Links:

    Other_Citation_Details:
    This publication includes the general methodology for differencing elevation models to produce the Hurricane Dorian washout extents.
    Kilheffer, Chelby R., Underwood, H. Brian, Raphael, Jordan, Ries, Lindsay, Farrell, Shannon, and Leopold, Donald J., 2019, Deer do not affect short-term rates of vegetation recovery in overwash fans on Fire Island after Hurricane Sandy: Ecology and Evolution Volume 9, Issue 20, American Wiley Library, online.

    Online Links:

    Other_Citation_Details: This publication includes the Fire Island washover extents.
    Congalton, Russell G., and Green, Kass, 2019, Assessing the Accuracy of Remotely Sensed Data: Principles and Practices: eBook Third Edition, CRC Press, Boca Raton.

    Online Links:

    Other_Citation_Details:
    This publication includes the basis for landcover classification statistics.
    Oloffson, Pontus, Foody, Giles M., Herold, Martin, Stehman, Stephen V., Woodcock, Curtis E., and Wulder, Michael A., 2014, Good practices for estimating area and assessing accuracy of land change: Remote Sensing of Enviornment Volume 148, Elsevier, online.

    Online Links:

    Other_Citation_Details:
    This publication includes the basis for reporting classification accuracies.

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

  1. How well have the observations been checked?
    Classification accuracy is assessed using stratified (proportional to area of class) randomly generated points and a confusion matrix of unsupervised classification verses expert interpretation and higher resolution reference imagery. The number of random points was determined following Olofsson et al. (2014) based on an estimated user accuracy of 0.85 for all classes and a targeted standard overall error accuracy of 0.03. The Bolivar Peninsula site had 100 due to the smaller areas of study. All classifications have an overall accuracy assessment value greater than 0.80, which represents strong agreement between classification and reference data (Congalton and Green). See processing steps for accuracy values of the classifications.
  2. How accurate are the geographic locations?
    Polygon boundaries of ponds, washout, and washover are based on human digitization and the accuracy scales on the resolution of the imagery and orthomosaics. True boundaries of the features are not expected to be off by more than 1 meter.
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    North Core Banks (NCB) was classified at two scales, at the island platform level and within the washover (Hurricane Florence, n=89) and washout (Hurricane Dorian, n=83) extents over six imagery time steps. San Jose Island (SJI) was classified within washout (Hurricane Harvey, n=9) extents over five imagery time steps. The Bolivar Peninsula (BP) was classified within two washout (Hurricane Ike) regions of interest (ROI) over five imagery time steps. Fire Island (FI) was classified within washover (Hurricane Sandy, n=9) over three imagery time steps.
  5. How consistent are the relationships among the observations, including topology?
    Classifications are limited to the polygon extents within the GeoPackage. A total of seven SQLite Data Feature Classes are in the GeoPackage that contain polygons categorized by date, hurricane, and location.

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 (CC0-1.0) 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

    1-888-275-8747 (voice)
    sciencebase@usgs.gov
  2. What's the catalog number I need to order this data set? The GeoPackage provides the extents to which hurricane outwash and overwash affected various coasts and are the geographic extent of the landcover classification results. These data support the journal article "Outwash events inhibit vegetation recovery and prolong coastal vulnerability".
  3. What legal disclaimers am I supposed to read?
    Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Although these data have been processed successfully on a computer system at the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. 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.
  4. How can I download or order the data?
  5. What hardware or software do I need in order to use the data set?
    The GeoPackage requires use of GIS software such as QGIS or ArcGIS

Who wrote the metadata?

Dates:
Last modified: 11-Jun-2025
Metadata author:
Jin-Si R. Over
U.S. Geological Survey, Woods Hole Coastal and Marine Science Center
Geographer
U.S. Geological Survey
Woods Hole, MA

508-548-8700 x2297 (voice)
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.
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/whcmsc/SB_data_release/DR_P1PGG57F/Over_and_Sherwood_Supp_metadata.faq.html>
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