Julia L. Heslin
Rachel E. Henderson
Kathryn M. Weber
Emily A. Himmelstoss
20211119
2018 Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis
1
vector digital data
data release
DOI:10.5066/P9AZYW74
Woods Hole Coastal and Marine Science Center, Woods Hole, MA
U.S. Geological Survey, Coastal and Marine Geology Program
https://doi.org/10.5066/P9AZYW74
https://www.sciencebase.gov/catalog/item/613f7a90d34e1449c5d35c9e
Julia L. Heslin
Rachel E. Henderson
Emily A. Himmelstoss
2021
A GIS Compilation of Vector Shorelines for Puerto Rico from 2015 to 2018
1
vector digital data
data release
DOI:10.5066/P9AZYW74
Reston, VA
U.S. Geological Survey
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.
https://doi.org/10.5066/P9AZYW74
https://www.sciencebase.gov/catalog/item/610abe37d34ef8d70568937a
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.
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.
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.
20180703
20180728
ground condition
None planned
-67.2715
-65.2441
18.5195
17.9267
ISO 19115 Topic Category
geoscientificInformation
oceans
environment
None
USGS
U.S. Geological Survey
Coastal and Marine Geology Program
Woods Hole Coastal and Marine Science Center
WHCMSC
Puerto Rico Shoreline Change
University of Puerto Rico
University of Puerto Rico Graduate School of Planning
Coastal Research and Planning Institute of Puerto Rico
DSAS
Digital Shoreline Analysis System
Shoreline
Shoreline Change
Mean High Water
MHW
USGS thesaurus
coastal processes
geospatial datasets
USGS Metadata Identifier
USGS:613f7a90d34e1449c5d35c9e
None
United States
Atlantic Coast
Caribbean
Puerto Rico
Vieques
Culebra
None
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.
U.S. Geological Survey
Rachel E. Henderson
mailing and physical address
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700
rehenderson@contractor.usgs.gov
https://www.sciencebase.gov/catalog/file/get/613f7a90d34e1449c5d35c9e?name=PR_2018_Lidar_Shoreline.jpg
Map of the USACE 2018 MHW shoreline (shown in green) extracted from lidar data, with the extent of lidar coverage highlighted in red.
JPEG
Version 6.2 (Build 9200) ; Esri ArcGIS 10.6.0.8321
Kathryn M. Weber
Jeffrey H. List
Karen L.M. Morgan
2005
An operational mean high water datum for determination of shoreline position from topographic lidar data
document
Open-File Report
2005-1027
Reston, VA
U.S. Geological Survey
https://doi.org/10.3133/ofr20051027
https://pubs.usgs.gov/of/2005/1027/
Emily A. Himmelstoss
Amy S. Farris
Rachel E. Henderson
Meredith G. Kratzmann
Ayhan Ergul
Ouya Zhang
Jessica L. Zichichi
20181230
Digital Shoreline Analysis System (version 5.0): U.S. Geological Survey software
5
application/service
software release
version 5.0
Reston, VA
U.S. Geological Survey
https://doi.org/10.3133/ofr20181179
https://code.usgs.gov/cch/dsas
Amy S. Farris
Kathryn M. Weber
Kara S. Doran
Jeffrey H. List
2018
Comparing Methods Used by the U.S. Geological Survey Coastal and Marine Geology Program for Deriving Shoreline Position from Lidar Data
document
Open-File Report
2018-1121
Reston, VA
U.S. Geological Survey
https://doi.org/10.3133/ofr20181121
https://pubs.usgs.gov/of/2018/1121/
Julia L. Heslin
Rachel E. Henderson
Emily A. Himmelstoss
20211101
Historical Shorelines for Puerto Rico from 1901 to 1987
vector ditital data
Woods Hole Coastal and Marine Science Center, Woods Hole, MA
U.S. Geological Survey, Coastal and Marine Geology Program
https://doi.org/10.5066/P9CLXCEG
https://www.sciencebase.gov/catalog/item/60cb7627d34e86b938a3a1b0
Loderay Bracero-Marrero
Maritza Barreto-Orta
Nias Hernández-Montcourt
Ruben Maldonado-González
20211101
A GIS compilation of Vector Shorelines and Shoreline Classification for Puerto Rico from 1970 and 2010
vector ditital data
data release
https://doi.org/10.5066/P9SEUAHC
Woods Hole Coastal and Marine Science Center, Woods Hole, MA
U.S. Geological Survey, Coastal and Marine Geology Program
https://doi.org/10.5066/P9SEUAHC
https://www.sciencebase.gov/catalog/item/610ae914d34ef8d70568fba9
Julia L. Heslin
Rachel E. Henderson
Emily A. Himmelstoss
2021
Puerto Rico Shoreline Change: A GIS Compilation of Shorelines, Baselines, Intersects, and Change Rates using the Digital Shoreline Analysis System version 5.1
vector ditital data
Woods Hole Coastal and Marine Science Center, Woods Hole, MA
U.S. Geological Survey, Coastal and Marine Geology Program
https://doi.org/10.5066/P9FNRRN0
https://www.sciencebase.gov/catalog/item/61255b87d34e40dd9c03f390
The attributes are based on the requirements of the Digital Shoreline Analysis System (DSAS) software, please refer to cross reference for citation.
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.
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.
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.
NOAA
20201203
vertical Datum transformation (Vdatum) version 4.2.1
raster digital data
Charleston, SC
NOAA Office for Coastal Management (OCM)
https://vdatum.noaa.gov/
online
20211201
ground condition
vdatum
used to define MHW elevation for Puerto Rico.
Office for Coastal Management (OCM) Partners
NOAA Office for Coastal Management
20190702
2018 USACE FEMA Topobathy Lidar DEM: Main Island, Culebra, and Vieques, Puerto Rico
raster digital data
Charleston, SC
NOAA Office for Coastal Management (OCM)
https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=8571
https://chs.coast.noaa.gov/htdata/raster2/elevation/USACE_PR_Topobathy_DEM_2018_8571/
online
20180630
20180728
ground condition
2018 DEM
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.
Office for Coastal Management (OCM) Partners
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
tabular digital data
Charleston, SC
NOAA Office for Coastal Management (OCM)
https://chs.coast.noaa.gov/htdata/lidar2_z/geoid18/data/8560/
online
20180630
20180728
ground condition
2018 point cloud data
The bare earth point cloud data in LAS format were used to extract shorelines using the profile method described in the process steps.
USACE NCMP and FEMA
20190702
JALBTCX 2018 Flight Lines: Dates Flown
vector digital data
Charleston, SC
USACE
https://usgs.maps.arcgis.com/home/item.html?id=4e70d40f9c8340b58c58935e99b0d960
online
20180630
20180728
ground condition
2018 lidar flight line information
The flight line data was used to extract the date for contour shoreline segments.
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.
20200101
Rachel E. Henderson
U.S. Geological Survey
Researcher VII
mailing and physical
384 Woods Hole Road
Woods Hole
MA
02540
508-548-8700
rehenderson@contractor.usgs.gov
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.
vdatum
20200201
Rachel E. Henderson
U.S. Geological Survey
Researcher VII
mailing and physical
384 Woods Hole Road
Woods Hole
MA
02540
508-548-8700
rehenderson@contractor.usgs.gov
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.
2018 DEM
20200401
PR MHW Contours
Julia L. Heslin
U.S. Geological Survey
Geographer
mailing and physical
384 Woods Hole Road
Woods Hole
MA
02540
508-457-2262
jheslin@usgs.gov
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.
PR MHW Contours
20200501
PR Smoothed Contour
Julia L. Heslin
U.S. Geological Survey
Geographer
mailing and physical
384 Woods Hole Road
Woods Hole
MA
02540
508-457-2262
jheslin@usgs.gov
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.
PR Smoothed Contour
2018 lidar flight line information
20200601
PR Contour with DATE
Julia L. Heslin
U.S. Geological Survey
Geographer
mailing and physical
384 Woods Hole Road
Woods Hole
MA
02540
508-457-2262
jheslin@usgs.gov
Contour Shoreline attributes: Additional attributes are added UNCY (see Horizontal Positional Accuracy Report), PROXY (MHW), AGENCY, TYPE (lidar), METHOD (contour).
PR Contour with DATE
20200701
PR Contour with ATTRIBUTES
Julia L. Heslin
U.S. Geological Survey
Geographer
mailing and physical
384 Woods Hole Road
Woods Hole
MA
02540
508-457-2262
jheslin@usgs.gov
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).
PR Contour with ATTRIBUTES
20200801
PR Contour Shoreline
Rachel E. Henderson
U.S. Geological Survey
Researcher VII
mailing and physical
384 Woods Hole Road
Woods Hole
MA
02540
508-548-8700
rehenderson@contractor.usgs.gov
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.
2018 point cloud data
20200901
PR Profile Shoreline
Kathryn M. Weber
U.S. Geological Survey
Oceanographer
mailing and physical
384 Woods Hole Road
Woods Hole
MA
02540
508-457-2351
kweber@usgs.gov
Combined the Profile and Contour Shorelines and updated attributes for profile segments (PROXY, AGENCY, TYPE, METHOD).
PR Profile Shoreline
PR Contour Shoreline
20201001
PR MHW Shoreline
Rachel E. Henderson
U.S. Geological Survey
Researcher VII
mailing and physical
384 Woods Hole Road
Woods Hole
MA
02540
508-548-8700
rehenderson@contractor.usgs.gov
Final coordinate transformation from "NAD_1983_NSRS2007_StatePlane_Puerto_Rico_Virgin_Isls_FIPS_5200" to "GCS_WGS_1984".
PR MHW Shoreline
20201101
PR_2018_USACE_MHW_Shoreline
Rachel E. Henderson
U.S. Geological Survey
Researcher VII
mailing and physical
384 Woods Hole Road
Woods Hole
MA
02540
508-548-8700
rehenderson@contractor.usgs.gov
Vector
String
2758
0.0197395052
0.0264490611
Decimal seconds
WGS_1984
WGS_84
6378137.0
298.257223563
PR_2018_USACE_MHW_Shoreline.shp
The mean high water (MHW) shoreline for the Puerto Rican coast used in shoreline change analysis.
U.S. Geological Survey
FID
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Feature geometry.
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.
U.S. Geological Survey
0.13
0.13
DSAS_DATE
Date of shoreline position; date of survey as indicated on source material.
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).
U.S. Geological Survey
0.95
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.
U.S. Geological Survey
MHW
The average Mean high water (MHW) for Puerto Rico, as described in process steps
Producer defined
AGENCY
The agency that provided the source data to create the shoreline
U.S. Geological Survey
USACE FEMA
The United States Army Corps of Engineers and Federal Emergency Management Agency
U.S. Geological Survey
TYPE
The type of source data used to create the shoreline
U.S. Geological Survey
Lidar
Light detection and ranging elevation data
Producer defined
METHOD
Method of shoreline extraction from lidar - contour or profile. See process steps for details.
U.S. Geological Survey
Profile
Shorelines were extracted using the profile method (Farris and others, 2018)
U.S. Geological Survey
Contour
Shorelines were extracted using the contour method (Farris and others, 2018)
U.S. Geological Survey
U.S. Geological Survey - ScienceBase
mailing and physical address
Federal Center, Building 810, MS 302
Denver
CO
80225
USA
1-888-275-8747
sciencebase@usgs.gov
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
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.
Shapefile
ArcGIS 10.6
Esri polyline shapefile
Dataset contains the shapefile, browse graphic, and CSDGM metadata.
11
https://doi.org/10.5066/P9AZYW74
https://www.sciencebase.gov/catalog/file/get/613f7a90d34e1449c5d35c9e
https://www.sciencebase.gov/catalog/item/613f7a90d34e1449c5d35c9e
The first link is to the USGS publication page, the second link downloads all the data on the landing page, and the third link is to the dataset landing page.
None
These data are available in a polyline shapefile format. The user must have software to read and process the data components of a shapefile.
20211119
Rachel E. Henderson
U.S. Geological Survey
mailing and physical address
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700
rehenderson@contractor.usgs.gov
FGDC Content Standards for Digital Geospatial Metadata
FGDC-STD-001-1998
local time