Coastal Land-Cover Data Derived from Landsat Satellite Imagery, Delaware Bay, New Jersey to Shinnecock Bay, New York, 2008-2022

Frequently anticipated questions:

• What does this data set describe?
  1. How might this data set be cited?
  2. What geographic area does the data set cover?
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
  5. What is the general form of this data set?
  6. How does the data set represent geographic features?
  7. How does the data set describe geographic features?
• Who produced the data set?
  1. Who are the originators of the data set?
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
• Why was the data set created?
• How was the data set created?
  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
  3. What similar or related data should the user be aware of?
• How reliable are the data; what problems remain in the data set?
  1. How well have the observations been checked?
  2. How accurate are the geographic locations?
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
  5. How consistent are the relationships among the data, including topology?
• How can someone get a copy of the data set?
  1. Are there legal restrictions on access or use of the data?
  2. Who distributes the data?
  3. What's the catalog number I need to order this data set?
  4. What legal disclaimers am I supposed to read?
  5. How can I download or order the data?
• Who wrote the metadata?

What does this data set describe?

1. How might this data set be cited?
   Bernier, Julie C., and Nick, Sydney K., 20240307, Coastal Land-Cover Data Derived from Landsat Satellite Imagery, Delaware Bay, New Jersey to Shinnecock Bay, New York, 2008-2022:.

   This is part of the following larger work.
   Bernier, Julie C., Nick, Sydney K., and Miselis, Jennifer L., 20240307, Coastal Land-Cover and Feature Datasets Derived from Landsat Satellite Imagery, Delaware Bay, New Jersey to Shinnecock Bay, New York: U.S. Geological Survey data release doi:10.5066/P13HX6Y8, U.S. Geological Survey - St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.

   Online Links:

   • https://doi.org/10.5066/P13HX6Y8

2. What geographic area does the data set cover?

   West_Bounding_Coordinate: -75.051991
   East_Bounding_Coordinate: -72.410495
   North_Bounding_Coordinate: 40.907999
   South_Bounding_Coordinate: 38.915257
   

3. What does it look like?

   LocMap_nfwf_1332_nj.png, LocMap_nfwf_1332_ny.png, LocMap_nfwf_1333.png, LocMap_nfwf_1433.png (PNG)

   A location map in Portable Network Graphics (PNG, .png) file format is included in each of the land cover zip files. These maps provide additional context for the landcover raster datasets coverage in the study area (New York and New Jersey). The regional area of interest is symbolized in a red dashed line and a scene-specific area of interest is symbolized in a light gray dashed line.

4. Does the data set describe conditions during a particular time period?

   Beginning_Date: 16-Apr-2008

   Ending_Date: 26-Nov-2022

   Currentness_Reference:

   Ground condition

5. What is the general form of this data set?

   Geospatial_Data_Presentation_Form: raster 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 Raster 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: 1.0
      Longitude_of_Central_Meridian: -75.0
      Latitude_of_Projection_Origin: 0
      False_Easting: 500000.0
      False_Northing: 0.0
      

      Planar coordinates are encoded using row and column
      Abscissae (x-coordinates) are specified to the nearest 30
      Ordinates (y-coordinates) are specified to the nearest 30
      Planar coordinates are specified in Meters
      The horizontal datum used is D WGS 1984.
      The ellipsoid used is WGS 1984.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.25722.
      
7. How does the data set describe geographic features?

   nfwf_1332_ny_landcover.zip, nfwf_1332_nj_landcover.zip, nfwf_1333_landcover.zip, nfwf_1433_nj_landcover.zip

   Zip archive containing 143 thematic land-cover raster datasets in ERDAS IMAGINE (.img) format for the WRS-2 path 13 row 32 New York (nfwf_1332_ny), WRS-2 path 13 row 32 New Jersey (nfwf_1332_nj), WRS-2 path 13 row 33 (nfwf_1333), and WRS-2 path 14 row 33 (nfwf_1433) AOIs. An AOI location map in PNG format is also included in each zip file. (Source: USGS)

   OID

   Internal feature number (Source: Esri) Sequential unique whole numbers that are automatically generated

   Value

   Land-cover class number (Source: USGS)

   Value	Definition
   0	Out - pixels outside of analysis extent
   1	Water - pixels classified as water
   3	Bare earth (sand) - pixels classified as bare earth (sand) land cover
   4	Vegetated - pixels classified as vegetated land cover
   11	Unclassed - pixels that were not classified as water, sand, or vegetated. Visual analysis indicates that most of the class 11 unclassed pixels represent intertidal areas, but this cannot be fully resolved using thresholding at the regional AOI scale.
   12	Unclassed - pixels that were not classified as water, sand, or vegetated. Visual analysis indicates that most of the class 12 unclassed pixels represent either built (urban), dune vegetation, or back-dune scrub vegetation, but this cannot be fully resolved using thresholding at the regional AOI scale.

   Values of 2, 5 through 10, and 13 through 255 are not used to define a land-cover class but are stored by default in the 8-bit raster attribute table.

   Count (Esri ArcGIS) or Histogram (Erdas Imagine)

   Number of pixels per land-cover class (Source: Hexagon Geospatial) Number of pixels per land-cover class

   Class_Name

   Land-cover type (Source: USGS)

   Value	Definition
   Out	Pixels outside of analysis extent (symbolized in black)
   Water	Pixels classified as water (symbolized in dark blue)
   Bare earth (sand)	Pixels classified as bare earth (sand) land cover (symbolized in dark brown)
   Vegetated	Pixels classified as vegetated land cover (symbolized in dark green)
   Unclassed	Pixels that were not classified as water, sand, or vegetated. Visual analysis indicates that most of the class 11 unclassed pixels represent intertidal areas and most of the class 12 unclassed pixels represent either built (urban), dune vegetation, or back-dune scrub vegetation, but this cannot be fully resolved using thresholding at the regional AOI scale (symbolized in light blue and light pink).

   Red

   Red value for RGB color map (Source: Hexagon Geospatial) Red value for RGB colormap

   Green

   Green value for RGB color map (Source: Hexagon Geospatial) Green value for RGB colormap

   Blue

   Blue value for RGB color map (Source: Hexagon Geospatial) Blue value for RGB colormap

   Opacity

   Opacity (on or off) of land-cover class (Source: Hexagon Geospatial) Opacity (on or off) of land-cover class

   nfwf_imagery.zip

   Zip archive containing Microsoft Excel (.xlsx) and comma-separated values (.csv) files describing source imagery, scene-specific AOI, and tidal water level and tidal stage at selected National Ocean Service (NOS) Center for Operational Oceanographic Products and Services (CO-OPS) tide gauges for each of 143 thematic land-cover raster datasets. Gauge locations are shown on the location maps included with each land-cover zip archive. (Source: USGS)

   FileName

   File name of classed land-cover raster (Source: USGS) Character string

   SceneID

   Landsat Collection 2, Level 2 source data downloaded from EROS ESPA (Source: USGS) Landsat source imagery data identifier

   ImageDate

   Source image-acquisition date (Source: USGS) Source image acquisition date written as DD-MON-YYYY (2-digit day, 3-letter month, 4-digit year)

   DecYear

   Source image-acquisition date, in decimal years (Source: USGS)

   Range of values
   Minimum:	2008.290
   Maximum:	2022.904
   Units:	Decimal year
   Resolution:	0.001

   AOI

   Scene-specific area of interest (Source: USGS)

   Value	Definition
   nfwf_1332_ny	WRS-2 path 13 row 32 New York AOI
   nfwf_1332_nj	WRS-2 path 13 row 32 New Jersey AOI
   nfwf_1333	WRS-2 path 13 row 33 (New Jersey) AOI
   nfwf_1433	WRS-2 path 14 row 33 (New Jersey) AOI

   CapeMayWL_mMSL

   Water level at the Cape May, New Jersey tide gauge (NOS CO-OPS station #8536110) at the time of image acquisition, in meters relative to mean sea level (MSL)). Applies only to WRS-2 path 14 row 33 (New Jersey) AOI. A dash is used to indicate a no data value. (Source: USGS)

   Range of values
   Minimum:	-0.751
   Maximum:	0.865
   Units:	Pixels
   Resolution:	0.001

   CapeMay_TidalStage

   Tidal stage at the Cape May, New Jersey tide gauge (NOS CO-OPS station #8536110) at the time of image acquisition). Applies only to WRS-2 path 14 row 33 (New Jersey) AOI. A dash is used to indicate a no data value. (Source: USGS)

   Value	Definition
   low tide	Tidal stage within +/- 1 hour of low tide
   high tide	Tidal stage within +/- 1 hour of high tide
   rising	Tidal stage rising between low and high tide
   falling	Tidal stage falling between high and low tide

   AtlanticCityWL_mMSL

   Water level at the Atlantic City, New Jersey tide gauge (NOS CO-OPS station #8534720) at the time of image acquisition, in meters relative to mean sea level (MSL). Applies only to WRS-2 path 13 row 33 (New Jersey) AOI. A dash is used to indicate a no data value. (Source: USGS)

   Range of values
   Minimum:	-0.850
   Maximum:	0.904
   Units:	Pixels
   Resolution:	0.001

   AtlanticCity_TidalStage

   Tidal stage at the Atlantic City, New Jersey tide gauge (NOS CO-OPS station #8534720) at the time of image acquisition. Applies only to WRS-2 path 13 row 33 (New Jersey) AOI. A dash is used to indicate a no data value. (Source: USGS)

   Value	Definition
   low tide	Tidal stage within +/- 1 hour of low tide
   high tide	Tidal stage within +/- 1 hour of high tide
   rising	Tidal stage rising between low and high tide
   falling	Tidal stage falling between high and low tide

   SandyHookWL_mMSL

   Water level at the Sandy Hook, New Jersey tide gauge (NOS CO-OPS station #8531680) at the time of image acquisition, in meters relative to mean sea level (MSL). Applies only to WRS-2 path 13 row 32 ( New York and New Jersey) AOIs. A dash is used to indicate a no data value. (Source: USGS)

   Range of values
   Minimum:	-0.869
   Maximum:	1.063
   Units:	Pixels
   Resolution:	0.001

   SandyHook_TidalStage

   Tidal stage at the Sandy Hook, New Jersey tide gauge (NOS CO-OPS station #8531680) at the time of image acquisition. Applies only to WRS-2 path 13 row 32 ( New York and New Jersey) AOIs. A dash is used to indicate a no data value. (Source: USGS)

   Value	Definition
   low tide	Tidal stage within +/- 1 hour of low tide
   high tide	Tidal stage within +/- 1 hour of high tide
   rising	Tidal stage rising between low and high tide
   falling	Tidal stage falling between high and low tide
   falling (p)	Predicted tidal stage falling between high and low tide (verified water-level data not available)

   MontaukWL_mMSL

   Water level at the Montauk, New York tide gauge (NOS CO-OPS station #8510560) at the time of image acquisition, in meters relative to mean sea level (MSL). Applies only to WRS-2 path 13 row 32 (New York) AOI. A dash is used to indicate a no data value. (Source: USGS)

   Range of values
   Minimum:	-0.204
   Maximum:	0.544
   Units:	Pixels
   Resolution:	0.001

   Montauk_TidalStage

   Tidal stage at the Montauk, New York tide gauge (NOS CO-OPS station #8510560) at the time of image acquisition. Applies only to WRS-2 path 13 row 32 (New York) AOI. A dash is used to indicate a no data value. (Source: USGS)

   Value	Definition
   low tide	Tidal stage within +/- 1 hour of low tide
   high tide	Tidal stage within +/- 1 hour of high tide
   rising	Tidal stage rising between low and high tide
   falling	Tidal stage falling between high and low tide

Who produced the data set?

1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
   • Julie C. Bernier
   • Sydney K. Nick
2. Who also contributed to the data set?
   U.S. Geological Survey, Coastal and Marine Hazards and Resources Program, St. Petersburg Coastal and Marine Science Center
3. To whom should users address questions about the data?
   U.S. Geological Survey

   Attn: Julie C. Bernier

   Geologist

   600 4th Street South

   St. Petersburg, FL
   

   USA

   727-502-8000 (voice)

   jbernier@usgs.gov

Why was the data set created?

How was the data set created?

1. From what previous works were the data drawn?
2. How were the data generated, processed, and modified?

   Date: 2023 (process 1 of 5)

   The regional AOI, which was derived from the National Oceanic and Atmospheric Administration (NOAA) US Coastal Zone Management Act Boundary, was subset into four scene-specific AOIs for processing and analysis: WRS-2 path 13 row 32 New York (nfwf_1332_ny), WRS-2 path 13 row 32 New Jersey (nfwf_1332_nj), WRS-2 path 13 row 33 (nfwf_1333), and WRS-2 path 14 row 33 (nfwf_1433). Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: Julie C. Bernier

   Geologist

   600 4th Street South

   St. Petersburg, FL
   

   USA

   727-502-8000 (voice)

   jbernier@usgs.gov

   Date: 2023 (process 2 of 5)

   For each image acquisition date, Collection-2, Level-2 surface reflectance (SR; reflective bands), surface temperature (ST; thermal infrared [TIR] bands), and SR-derived NDVI images were downloaded from the EROS ESPA On Demand Interface (https://espa.cr.usgs.gov/). Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: Julie C. Bernier

   Geologist

   600 4th Street South

   St. Petersburg, FL
   

   USA

   727-502-8000 (voice)

   jbernier@usgs.gov

   Date: 2023 (process 3 of 5)

   All images were batch-processed using Spatial Model Editor in ERDAS IMAGINE. The SR and ST bands were stacked to create 7- (TM) or 8- (OLI) band multispectral images and clipped to the scene-specific AOI. From these composite images, two additional spectral indices, mNDWI (Xu, 2006) and NBLI (Li and others, 2017), were calculated. Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: Julie C. Bernier

   Geologist

   600 4th Street South

   St. Petersburg, FL
   

   USA

   727-502-8000 (voice)

   jbernier@usgs.gov

   Date: 2023 (process 4 of 5)

   Land-cover classification was modified from the workflow described by Bernier and others (2021) using multilevel (2 thresholds per image) automatic thresholding of spectral indices and applying a rule-based classification scheme. First, Otsu's method (Otsu, 1979) for automatic histogram thresholding was applied to mNDWI images to create a binary "land"-water raster for each image acquisition date. Second, water area was masked from NBLI and NDVI images, and Otsu's method was applied to the masked images to create binary bare earth-"unclassed" and vegetated-"unclassed" rasters, respectively. The following rule-based classification was then applied, where T1 and T2 represent the first and second multi-Otsu thresholds, respectively, for each spectral index: If mNDWI > T2 then class (1) = water If NBLI > T2 then class (3) = bare earth (sand) If T1 < NBLI < T2 and UVVR = NoData then class (12) = unclassed If (T1 < NBLI < T2 and NDVI > T1 and UVVR > 0) or (NBLI < T1 and NDVI < T1) then class (4) = vegetated If NBLI < T1 and NDVI < T1 then class (11) = unclassed Where UVVR is the 2014-2018 composite Unvegetated to Vegetated Ratio for the U.S. Atlantic Coast (Couvillion and others, 2021) subset to the regional AOI. Finally, the binary land-cover images were converted to thematic rasters, merged, single-pixel "clumps" were removed using a 3x3 majority filter, and a standard colormap was applied to create a final land-cover raster dataset for each image acquisition date. The resulting land-cover rasters use the naming convention YYYYMMDD_lt05_AOI_lcr_ce.img (Landsat 5) or YYYYMMDD_lc08_AOI_lcr_ce.img (Landsat 8), where YYYYMMDD denotes the image-acquisition date (4-digit year, 2-digit month, 2-digit day) and AOI denotes the scene-specific AOI. All steps were batch-processed using the Image Processing toolbox in MATLAB (Otsu thresholding and binary image creation) or Spatial Model Editor in ERDAS IMAGINE (spectral index masking and generation of classed land-cover rasters). Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: Julie C. Bernier

   Geologist

   600 4th Street South

   St. Petersburg, FL
   

   USA

   727-502-8000 (voice)

   jbernier@usgs.gov

   Data sources produced in this process:

   • YYYYMMDD_lt05_AOI_lcr_ce.img
   • YYYYMMDD_lc08_AOI_lcr_ce.img
   • YYYYMMDD_lt05_AOI_lcr_ce_cl.img
   • YYYYMMDD_lc08_AOI_lcr_ce_cl.img

   Date: 2024 (process 5 of 5)

   For 35 datasets, thresholding resulted in misclassification of some nearshore water areas as "land" after mNDWI thresholding. Visual analysis showed that most misclassed open-water pixels correspond to areas of breaking waves, and misclassed extents were manually cleaned from the final datasets by selecting and re-classing the pixels in ERDAS IMAGINE. The cleaned land-cover rasters use the naming convention YYYYMMDD_lt05_AOI_lcr_ce_cl.img (Landsat 5) or YYYYMMDD_lc08_AOI_lcr_ce_cl.img (Landsat 8), where YYYYMMDD denotes the image-acquisition date and AOI denotes the scene-specific AOI. Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: Julie C. Bernier

   Geologist

   600 4th Street South

   St. Petersburg, FL
   

   USA

   727-502-8000 (voice)

   jbernier@usgs.gov

   Data sources produced in this process:

   • YYYYMMDD_lt05_AOI_lcr_ce_cl.img
   • YYYYMMDD_lc08_AOI_lcr_ce_cl.img

3. What similar or related data should the user be aware of?
   Bernier, Julie C., Miselis, Jennifer L., and Plant, Nathaniel G., 20210921, Satellite-Derived Barrier Response and Recovery Following Natural and Anthropogenic Perturbations, Northern Chandeleur Islands, Louisiana: Remote Sensing 13(18), 3778; Special Issue "New Insights into Ecosystem Monitoring Using Geospatial Techniques".

   Online Links:

   • https://doi.org/10.3390/rs13183779

   Xu, Hanqiu, 20070222, Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery: International Journal of Remote Sensing Volume 27, Issue 14.

   Online Links:

   • https://doi.org/10.1080/01431160600589179

   Other_Citation_Details: Pages 3025-3033
   

   Li, Hui, Wang, Cuizhen, Zhong, Cheng, Su, Aijun, Xiong, Chengren, Wang, Jinge, and Liu, Junqi, 20170307, Mapping Urban Bare Land Automatically from Landsat Imagery with a Simple Index: Remote Sensing 9(3), 249.

   Online Links:

   • https://doi.org/10.3390/rs9030249

   Otsu, Nobuyuki, 197901, A Threshold Selection Method from Gray-Level Histograms: IEEE Transactions on Systems, Man and Cybernetics Volume 9, Issue 1.

   Online Links:

   • https://doi.org/10.1109/TSMC.1979.4310076

   Other_Citation_Details: Pages 62-66
   

   Couvillion, Brady R., Ganju, Neil K., and Defne, Zafer, 20210205, An Unvegetated to Vegetated Ratio (UVVR) for Coastal Wetlands of the Conterminous United States (2014-2018): U.S. Geological Survey data release doi:10.5066/P97DQXZP, U.S. Geological Survey, Woods Hole, MA.

   Online Links:

   • https://doi.org/10.5066/P97DQXZP

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

1. How well have the observations been checked?
   Due to the large spatial extent of this analysis and a lack of ground-truth datasets with similar temporal resolution, regional-scale classification accuracy was not quantitatively assessed. Using a similar methodology and workflow, Bernier and others (2021) reported classification accuracies (>=70%) that were comparable to accuracies reported for the National Land Cover Database (NLCD). Visual comparison of the classed land-cover rasters derived in this study with available NLCD data showed good agreement, except in some densely populated (Ocean City Beach on Pecks Beach Island, Atlantic City on Absecon Island, and Beach Haven and Long Beach on Long Beach Island, NJ) or modified (frequent beach scraping at Wildwoods on 5 Mile Beach, NJ) locations, where built (urban) areas landward of the beach were misclassed as sand.
2. How accurate are the geographic locations?
   Geodetic accuracy of Landsat data products depend on the accuracy of the ground control points and the resolution of the digital elevation model (DEM) used. All Level-2 science products are derived from Level-1 Tier-1 Precision and Terrain (L1TP) corrected data and meet pre-defined image-to-image georegistration tolerances of <= 12-meter (m) radial root mean square error (RMSE).
3. How accurate are the heights or depths?
   
4. Where are the gaps in the data? What is missing?
   54 Landsat TM and 95 OLI images (Worldwide Reference System 2 [WRS-2] path 13 row 32, WRS-2 path 13 row 33, and WRS-2 path 14 row 33) acquired between April 2008 and November 2022 that were cloud- and snow- or ice-free over the regional area of interest (AOI) were analyzed.
5. How consistent are the relationships among the observations, including topology?
   For each image-acquisition date, Landsat Collection 2, Level-2 science products were downloaded from the USGS Earth Resources Observation and Science (EROS) Center Science Processing Architecture (ESPA) On Demand Interface (https://espa.cr.usgs.gov/).

How can someone get a copy of the data set?

1. Who distributes the data set? (Distributor 1 of 1)
   
   U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center

   Attn: USGS SPCMSC Data Management

   600 4th Street South

   St. Petersburg, FL
   

   USA

   727-502-8000 (voice)

   gs-g-spcmsc_data_inquiries@usgs.gov
2. What's the catalog number I need to order this data set? YYYYMMDD_lt05_AOI_lcr_ce.img, YYYYMMDD_lc08_AOI_lcr_ce.img, YYYYMMDD_lt05_AOI_lcr_ce_cl.img, YYYYMMDD_lc08_AOI_lcr_ce_cl.img
3. What legal disclaimers am I supposed to read?
   This publication was prepared by an agency of the United States Government. Although these data have been processed successfully on a computer system at the U.S. Geological Survey, no warranty expressed or implied is made regarding the display or utility of the data on any other system, or for general or scientific purposes, nor shall the act of distribution imply any such warranty. The U.S. Geological Survey shall not be held liable for improper or incorrect use of the data described and (or) contained herein. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof.
4. How can I download or order the data?
   • Availability in digital form:

     Data format:

     Download files contain ERDAS IMAGINE (.img) land-cover rasters, PNG location maps, Microsoft Excel (.xlsx) spreadsheets, and comma-separated values (.csv) text files. in format ERDAS IMAGINE, PNG, comma-delimited text, Microsoft Excel format

     Network links:

     https://coastal.er.usgs.gov/data-release/doi-P13HX6Y8/data/nfwf_1332_ny_landcover.zip https://coastal.er.usgs.gov/data-release/doi-P13HX6Y8/data/nfwf_1332_nj_landcover.zip https://coastal.er.usgs.gov/data-release/doi-P13HX6Y8/data/nfwf_1333_landcover.zip https://coastal.er.usgs.gov/data-release/doi-P13HX6Y8/data/nfwf_1433_landcover.zip https://coastal.er.usgs.gov/data-release/doi-P13HX6Y8/data/nfwf_imagery.zip

   • Cost to order the data: None

5. What hardware or software do I need in order to use the data set?
   Raster datasets were created using ERDAS IMAGINE 2023 and can be opened using ERDAS IMAGINE 2020 or higher, Esri ArcGIS version 10.0 or higher or Esri ArcGIS Pro version 3.1 or higher; these data may also be viewed using free Google Earth Pro or QGIS software.

Who wrote the metadata?

Dates:

Last modified: 07-Mar-2024

Metadata author:

U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center

Attn: USGS SPCMSC Data Management

600 4th Street South

St. Petersburg, FL

USA

727-502-8000 (voice)

gs-g-spcmsc_data_inquiries@usgs.gov

Metadata standard:

Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)