Identification_Information:
  Citation:
    Citation_Information:
      Originator: Julie C. Bernier
      Originator: Sydney K. Nick
      Originator: Breanna N. Williams
      Publication_Date: 20251203
      Title: Coastal Features Extracted from Landsat Satellite Imagery, Sabine Pass to Bay Coquette, Louisiana, 2013-2024
      Geospatial_Data_Presentation_Form: vector digital data
      Larger_Work_Citation:
        Citation_Information:
          Originator: Sydney K. Nick
          Originator: Julie C. Bernier
          Originator: Breanna N. Williams
          Originator: Jennifer L. Miselis
          Publication_Date: 20251203
          Title: Coastal Land-Cover and Feature Datasets Derived from Landsat Satellite Imagery, Sabine Pass to Bay Coquette, Louisiana
          Series_Information:
            Series_Name: U.S. Geological Survey data release
            Issue_Identification: doi:10.5066/P1MSCTUB
          Publication_Information:
            Publication_Place: St. Petersburg, Florida
            Publisher: U.S. Geological Survey - St. Petersburg Coastal and Marine Science Center
          Online_Linkage: https://doi.org/10.5066/P1MSCTUB
  Description:
    Abstract: This data release serves as an archive of coastal land-cover and feature datasets derived from Landsat satellite imagery from Sabine Pass to Bay Coquette, Louisiana (LA). A total of 179 images acquired between 2013 and 2024 were analyzed. Water, bare earth (sand), and vegetated land-cover classes were mapped using (1) successive thresholding and masking of the modified normalized difference water index (mNDWI), the normalized difference bare land index (NBLI), and the normalized difference vegetation index (NDVI) and (2) applying a rule-based classification modified from the workflow described by Bernier and others (2021). Vector shoreline and sand feature extents were extracted for each image by contouring the spectral indices using the calculated threshold values. Funded by the Extending Government Funding and Delivering Emergency Assistance Act (Public Law 117-43) enacted on September 30, 2021, these data support assessments of changes that occurred along the Louisiana coast following the passage of Hurricanes Laura, Delta, and Zeta in 2020 and Hurricane Ida in 2021. 
    Purpose: Dissemination of thematic raster data representing 179 land-cover datasets derived from 139 Landsat 8 and 40 Landsat 9 Operational Land Imager (OLI) images from coastal Louisiana, USA.
    Supplemental_Information: Information about the Landsat missions, sensor and band specifications, data products, and data access can be found at https://www.usgs.gov/landsat-missions.
  Time_Period_of_Content:
    Time_Period_Information:
      Range_of_Dates/Times:
        Beginning_Date: 20130420
        Ending_Date: 20241230
    Currentness_Reference: ground condition
  Status:
    Progress: Complete
    Maintenance_and_Update_Frequency: None planned
  Spatial_Domain:
    Bounding_Coordinates:
      West_Bounding_Coordinate: -89.502445
      East_Bounding_Coordinate: -93.852531
      North_Bounding_Coordinate: 29.800980
      South_Bounding_Coordinate: 29.029450
  Keywords:
    Theme:
      Theme_Keyword_Thesaurus: USGS Metadata Identifier
      Theme_Keyword: USGS:018c127f-9402-4070-ac38-c726b8c7c871
    Theme:
      Theme_Keyword_Thesaurus: ISO 19115 Topic Category
      Theme_Keyword: geoscientificInformation
      Theme_Keyword: imageryBaseMapsEarthCover
    Theme:
      Theme_Keyword_Thesaurus: USGS Thesaurus
      Theme_Keyword: geomorphology
      Theme_Keyword: geospatial datasets
      Theme_Keyword: image collections
      Theme_Keyword: multispectral imaging
      Theme_Keyword: coastal ecosystems
      Theme_Keyword: land use and land cover
      Theme_Keyword: contouring
    Theme:
      Theme_Keyword_Thesaurus: None
      Theme_Keyword: Landsat
      Theme_Keyword: barrier island
      Theme_Keyword: spectral indices
      Theme_Keyword: Otsu thresholding
      Theme_Keyword: shoreline
      Theme_Keyword: sand
    Place:  
      Place_Keyword_Thesaurus: Geographic Names Information System (GNIS)
      Place_Keyword: Louisiana
      Place_Keyword: Gulf of America	
      Place_Keyword: Sabine Pass
      Place_Keyword: Calcasieu Pass
      Place_Keyword: Headquarters Canal
      Place_Keyword: Freshwater Bayou Canal
      Place_Keyword: Marsh Island
      Place_Keyword: Point au Fer Island
      Place_Keyword: Caillou Boca
      Place_Keyword: Raccoon Point
      Place_Keyword: Bay Coquette
    Place:
      Place_Keyword_Thesaurus: None
      Place_Keyword: Gulf of Mexico
  Access_Constraints: No access constraints. Please see 'Distribution Information' for details. 
  Use_Constraints: These data are marked with a Creative Commons CC0 1.0 Universal License. These data are in the public domain and do not have any use constraints. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations
  Point_of_Contact:
    Contact_Information:
      Contact_Organization_Primary:
        Contact_Organization: U.S. Geological Survey
        Contact_Person: Julie C. Bernier
      Contact_Position: Geologist
      Contact_Address:
        Address_Type: Mailing and physical
        Address: 600 4th Street South
        City: St. Petersburg
        State_or_Province: FL
        Postal_Code: 33701
        Country: USA
      Contact_Voice_Telephone: 727-502-8000
      Contact_Electronic_Mail_Address: jbernier@usgs.gov
  Data_Set_Credit: U.S. Geological Survey, Coastal and Marine Hazards and Resources Program, St. Petersburg Coastal and Marine Science Center. Funding and (or) support for this study were provided as part of the Extending Government Funding and Delivering Emergency Assistance Act (Public Law 117-43), enacted on September 30, 2021. This document was improved by scientific and metadata reviews by Kathryn Weber and Tess Rivenbark-Terrano (USGS SPCMSC).
  Native_Data_Set_Environment: Windows 11 Enterprise version 23H2 (22631.4890); Microsoft Excel for Microsoft 365 MSO (Version 2408 Build 16.0.17928.20538); Esri ArcGIS Pro 3.2.2; ERDAS IMAGINE 2023 Version 16.8.0 Build 2100; MATLAB R2022a Update 8 (9.12.0.2529717)
  Cross_Reference:
    Citation_Information:
      Originator: Julie C. Bernier
      Originator: Jennifer L. Miselis
      Originator: Nathaniel G. Plant
      Publication_Date: 20210921
      Title: Satellite-Derived Barrier Response and Recovery Following Natural and Anthropogenic Perturbations, Northern Chandeleur Islands, Louisiana
      Series_Information:
        Series_Name: Remote Sensing
        Issue_Identification: 13(18), 3778; Special Issue "New Insights into Ecosystem Monitoring Using Geospatial Techniques"
      Online_Linkage: https://doi.org/10.3390/rs13183779
  Cross_Reference:
    Citation_Information:
      Originator: Hanqiu Xu
      Publication_Date: 2006
      Title: Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery
      Series_Information:
        Series_Name: International Journal of Remote Sensing
        Issue_Identification: Volume 27, Issue 14
      Other_Citation_Details: Pages 3025-3033
      Online_Linkage: https://doi.org/10.1080/01431160600589179
  Cross_Reference:
    Citation_Information:
      Originator: Hui Li
      Originator: Cuizhen Wang
      Originator: Cheng Zhong
      Originator: Aijun Su
      Originator: Chengren Xiong
      Originator: Jinge Wang
      Originator: Junqi Liu
      Publication_Date: 20170307
      Title: Mapping Urban Bare Land Automatically from Landsat Imagery with a Simple Index
      Series_Information:
        Series_Name: Remote Sensing
        Issue_Identification: 9(3), 249
      Online_Linkage: https://doi.org/10.3390/rs9030249
  Cross_Reference:
    Citation_Information:
      Originator: Nobuyuki Otsu
      Publication_Date: 197901
      Title: A Threshold Selection Method from Gray-Level Histograms
      Series_Information:
        Series_Name: IEEE Transactions on Systems, Man and Cybernetics
        Issue_Identification: Volume 9, Issue 1
      Other_Citation_Details: Pages 62-66
      Online_Linkage: https://doi.org/10.1109/TSMC.1979.4310076
  Cross_Reference:
    Citation_Information:
      Originator: Nicholas M. Enwright
      Originator: William M. SooHoo
      Originator: Jason Dugas
      Originator: Craig P. Conzelmann
      Originator: Claudia Laurenzano
      Originator: Darin M. Lee
      Originator: Kelly Mouton
      Originator: Spencer J. Stelly
      Publication_Date: 20201030
      Title: Louisiana Barrier Island Comprehensive Monitoring Program: Mapping Habitats in Beach, Dune, and Intertidal Environments Along the Louisiana Gulf of Mexico Shoreline, 2008 and 2015–16
      Series_Information:
        Series_Name: U.S. Geological Survey Open-File Report
        Issue_Identification: 2020-1030, 57p
      Online_Linkage: https://doi.org/10.3133/ofr20201030
Data_Quality_Information:
  Attribute_Accuracy:
    Attribute_Accuracy_Report: 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.
  Logical_Consistency_Report: 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/).
  Completeness_Report: 139 Landsat 8 and 40 Landsat 9 OLI images (Worldwide Reference System 2 [WRS-2] path 22 row 40, WRS-2 path 23 row 40, and WRS-2 path 24 row 39) acquired between April 2013 and December 2025 were analyzed. Due to the large geographic extent of each image, and to maximize the number of images analyzed, 37 images were clipped to either the eastern or western part of the scene-specific area of interest (AOI) to exclude cloud cover.
  Positional_Accuracy:
    Horizontal_Positional_Accuracy:
      Horizontal_Positional_Accuracy_Report: 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). The positional accuracy of the satellite-derived features was not systematically evaluated in this study; however, recent analyses of satellite-derived shoreline (SDS) positions extracted using similar methods to those presented here report offsets of 1/3 to 1/2-pixel (10 to 15 m) seaward of measured in-situ shoreline positions. Compared with methods that extract shoreline position from precise elevation measurements (for example, light detection and ranging [lidar] or global positioning system [GPS] surveys), SDS positions are not based on a vertical datum (for example, mean sea level or mean high water); instead, SDS represent instantaneous waterlines at time of image acquisition and may include intertidal areas.
  Lineage:
    Process_Step:
      Process_Description: The regional AOI, which was derived from the State of Louisiana’s Barrier Island Comprehensive Monitoring (BICM) Program habitat mapping extents (Enwright and others, 2020), was subset into three scene-specific AOIs for processing and analysis: WRS-2 path 22 row 40 (dr22_2240), WRS-2 path 23 row 40 (dr22_2340), and WRS-2 path 24 row 39 (dr22_2439).
      Process_Date: 2024
      Process_Contact:
        Contact_Information:
          Contact_Organization_Primary:
            Contact_Organization: U.S. Geological Survey
            Contact_Person: Julie C. Bernier
          Contact_Position: Geologist
          Contact_Address:
            Address_Type: Mailing and physical
            Address: 600 4th Street South
            City: St. Petersburg
            State_or_Province: FL
            Postal_Code: 33701
            Country: USA
          Contact_Voice_Telephone: 727-502-8000
          Contact_Electronic_Mail_Address: jbernier@usgs.gov
    Process_Step:
      Process_Description: 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/).
      Process_Date: 2025
      Process_Contact:
        Contact_Information:
          Contact_Organization_Primary:
            Contact_Organization: U.S. Geological Survey
            Contact_Person: Sydney K. Nick
          Contact_Position: Geographer
          Contact_Address:
            Address_Type: Mailing and physical
            Address: 600 4th Street South
            City: St. Petersburg
            State_or_Province: FL
            Postal_Code: 33701
            Country: USA
          Contact_Voice_Telephone: 727-502-8000
          Contact_Electronic_Mail_Address: snick@usgs.gov
    Process_Step:
      Process_Description: All images were batch-processed using Spatial Model Editor in ERDAS IMAGINE. The SR bands were stacked to create 8-band multispectral images and clipped to the scene-specific AOI. From these composite images and the corresponding ST images, two additional spectral indices, mNDWI (Xu, 2006) and NBLI (Li and others, 2017), were calculated.
      Process_Date: 2025
      Process_Contact:
        Contact_Information:
          Contact_Organization_Primary:
            Contact_Organization: U.S. Geological Survey
            Contact_Person: Sydney K. Nick
          Contact_Position: Geographer
          Contact_Address:
            Address_Type: Mailing and physical
            Address: 600 4th Street South
            City: St. Petersburg
            State_or_Province: FL
            Postal_Code: 33701
            Country: USA
          Contact_Voice_Telephone: 727-502-8000
          Contact_Electronic_Mail_Address: snick@usgs.gov
    Process_Step:
      Process_Description:
        Land-cover classification was modified from the workflow described by Bernier and others (2021) using single (mNDWI), multilevel (2 thresholds per image; NBLI), or iterative (NDVI) 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 and urban areas (derived from the BICM “structure” class [Enwright and others, 2020]) were 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. 
        For the WRS-2 path 23 row 40 (dr22_2340) scene-specific AOI only, the downloaded ST images included 2 large areas of missing data east of Freshwater Bayou Canal, which are the result of missing Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) input data (see https://www.usgs.gov/landsat-missions/landsat-collection-2-surface-temperature-data-gaps-due-missing-aster-ged for more information) necessary for ST product generation. Without ST data, NBLI could not be calculated for these pixels and any land-cover classification relying on NBLI input is invalid. Therefore, a mask was created from the ST “NoData” pixels and included in the land-cover classification.
        The following rule-based classification was then applied with each successive step applied to any unclassed pixels from the previous steps, where T represents the single Otsu threshold, T1 and T2 represent the first and second multi-Otsu thresholds, respectively, and Ti represents the second iteration of Otsu thresholding for each spectral index:
        If mNDWI > T then class (1) = water
        If ST = NoData then class (2) = land (undifferentiated)
        If NBLI > T2 then class (3) = bare earth (sand)
        If NDVI > Ti or (NDVI < Ti and NBLI < T1) then class (4) = vegetated
        If T1 < NBLI < T2 and NDVI < Ti then class (11) = intertidal
        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_lc##_AOI_lcr_ce.img, where YYYYMMDD denotes the image-acquisition date (4-digit year, 2-digit month, 2-digit day), lc## denotes Landsat 8 (lc08) or Landsat 9 (lc09) image source, AOI denotes the scene-specific AOI, and lcr_ce are process step abbreviations where lcr indicates the "raw" land cover files that were created by thresholding the spectral indices were merged following the rule-based classification and ce indicates that single-pixel "clumps" were removed. 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).
      Process_Date: 2025
      Source_Produced_Citation_Abbreviation: YYYYMMDD_lc08_AOI_lcr_ce.img
      Source_Produced_Citation_Abbreviation: YYYYMMDD_lc09_AOI_lcr_ce.img
      Process_Contact:
        Contact_Information:
          Contact_Organization_Primary:
            Contact_Organization: U.S. Geological Survey
            Contact_Person: Julie C. Bernier
          Contact_Position: Geologist
          Contact_Address:
            Address_Type: Mailing and physical
            Address: 600 4th Street South
            City: St. Petersburg
            State_or_Province: FL
            Postal_Code: 33701
            Country: USA
          Contact_Voice_Telephone: 727-502-8000
          Contact_Electronic_Mail_Address: jbernier@usgs.gov
    Process_Step:
      Process_Description: Vector shoreline (representing the boundary between open-water areas and adjacent non-water land cover pixels, including intertidal areas) and the sand extents were extracted by contouring the mNDWI and masked NBLI images using the calculated Otsu thresholds. Shoreline vectors were manually cleaned to remove interior water bodies and contours representing extents of less than 4 connected pixels in the landcover rasters. The resulting shorelines include only the seaward shoreline for mainland land areas or the sea and back-barrier shorelines for barrier islands; however, interior shorelines (for example, along fluvial or tidal inlets or complex wetland shorelines) that are connected to the sea shoreline were not manually clipped and removed. Sand vectors were manually cleaned to remove interior mainland (non-beach) areas and contours representing sand extents of less than 4 connected pixels in the landcover rasters. The resulting shapefiles (one per image acquisition date) were merged into 2 shapefiles (one each for shoreline and sand features) for each scene-specific AOI. For the 37 datasets that were clipped to either the eastern or western part of the scene-specific AOI to exclude cloud cover, the vectors sand and shoreline files were also clipped to the same extent. The resulting sand (sandext) and shoreline (shrln) vector shapefiles use the naming convention AOI_shrln.shp or AOI_sandext.shp, where AOI denotes the scene-specific AOI. Contouring was batch-processed using Python 3 Jupyter Notebooks in ArcGIS Pro.
      Process_Date: 2025
      Process_Contact:
        Contact_Information:
          Contact_Organization_Primary:
            Contact_Organization: U.S. Geological Survey
            Contact_Person: Sydney K. Nick
          Contact_Position: Geographer
          Contact_Address:
            Address_Type: Mailing and physical
            Address: 600 4th Street South
            City: St. Petersburg
            State_or_Province: FL
            Postal_Code: 33701
            Country: USA
          Contact_Voice_Telephone: 727-502-8000
          Contact_Electronic_Mail_Address: snick@usgs.gov
Spatial_Data_Organization_Information:
  Direct_Spatial_Reference_Method: Vector
Spatial_Reference_Information:
  Horizontal_Coordinate_System_Definition:
    Planar:
      Grid_Coordinate_System:
        Grid_Coordinate_System_Name: Universal Transverse Mercator
        Universal_Transverse_Mercator:
          UTM_Zone_Number: 15
          Transverse_Mercator:
            Scale_Factor_at_Central_Meridian: 1.0
            Longitude_of_Central_Meridian: -93.0
            Latitude_of_Projection_Origin: 0
            False_Easting: 500000.0
            False_Northing: 0.0
      Planar_Coordinate_Information:
        Planar_Coordinate_Encoding_Method: row and column
        Coordinate_Representation:
          Abscissa_Resolution: 30
          Ordinate_Resolution: 30
        Planar_Distance_Units: Meters
    Geodetic_Model:
      Horizontal_Datum_Name: D WGS 1984
      Ellipsoid_Name: WGS 1984
      Semi-major_Axis: 6378137.0
      Denominator_of_Flattening_Ratio: 298.25722
Entity_and_Attribute_Information: 
  Detailed_Description:
    Entity_Type:
      Entity_Type_Label: la_features.zip
      Entity_Type_Definition: Zip archive containing vector shoreline (dr22_p22r40_shrln.shp, dr22_p23r40_shrln.shp, dr22_p24r39_shrln.shp) and sand (dr22_p22r40_sandext.shp, dr22_p23r40_sandext.shp, dr22_p24r39_sandext.shp) feature extents corresponding to each of 179 thematic land-cover raster datasets in Esri shapefile (.shp) format.
      Entity_Type_Definition_Source: USGS
    Attribute:
      Attribute_Label: FID
      Attribute_Definition: Internal feature number
      Attribute_Definition_Source: Esri
      Attribute_Domain_Values:
        Unrepresentable_Domain: Sequential unique whole numbers that are automatically generated
    Attribute:
      Attribute_Label: Shape*
      Attribute_Definition: Feature geometry
      Attribute_Definition_Source: Esri
      Attribute_Domain_Values:
        Unrepresentable_Domain: Coordinates defining the features
    Attribute:
      Attribute_Label: IMG_DATE
      Attribute_Definition: Source image acquisition date
      Attribute_Definition_Source: USGS
      Attribute_Domain_Values:
        Unrepresentable_Domain: Source image acquisition date written as DD-MON-YYYY (2-digit day, month abbreviation, 4-digit year)
    Attribute:
      Attribute_Label: DEC_YEAR
      Attribute_Definition: Source image-acquisition date, in decimal years
      Attribute_Definition_Source: USGS
      Attribute_Domain_Values:
        Range_Domain:
          Range_Domain_Minimum: 2013.301
          Range_Domain_Maximum: 2024.997
          Attribute_Units_of_Measure: Decimal year
          Attribute_Measurement_Resolution: 0.001
    Attribute:
      Attribute_Label: SOURCE
      Attribute_Definition: Image source (Landsat 8 or Landsat 9)
      Attribute_Definition_Source: USGS
      Attribute_Domain_Values:
        Enumerated_Domain:
          Enumerated_Domain_Value: LC08
          Enumerated_Domain_Value_Definition: Landsat 8
          Enumerated_Domain_Value_Definition_Source: USGS
      Attribute_Domain_Values:
        Enumerated_Domain:
          Enumerated_Domain_Value: LC09
          Enumerated_Domain_Value_Definition: Landsat 9
          Enumerated_Domain_Value_Definition_Source: USGS
Distribution_Information:
  Distributor:
    Contact_Information:
      Contact_Organization_Primary:
        Contact_Organization: U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center
        Contact_Person: USGS SPCMSC Data Management
      Contact_Address:
        Address_Type: Mailing and physical
        Address: 600 4th Street South
        City: St. Petersburg
        State_or_Province: FL
        Postal_Code: 33701
        Country: USA
      Contact_Voice_Telephone: 727-502-8000
      Contact_Electronic_Mail_Address: gs-g-spcmsc_data_inquiries@usgs.gov
  Resource_Description: dr22_p22r40_shrln.shp, dr22_p23r40_shrln.shp, dr22_p24r39_shrln.shp, dr22_p22r40_sandext.shp, dr22_p23r40_sandext.shp, dr22_p24r39_sandext.shp
  Distribution_Liability: 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.
  Standard_Order_Process:
    Digital_Form:
      Digital_Transfer_Information:
        Format_Name: Shapefile
        Format_Information_Content: Download files contain Esri vector sand- and shoreline shapefiles (.shp)
      Digital_Transfer_Option:
        Online_Option:
          Computer_Contact_Information:
            Network_Address:
              Network_Resource_Name: https://coastal.er.usgs.gov/data-release/doi-P1MSCTUB/data/la_features.zip
    Fees: None
  Technical_Prerequisites: Vector datasets were created using Esri ArcGIS Pro version 3.2.1 and can be opened using 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.
Metadata_Reference_Information:
  Metadata_Date: 20251203
  Metadata_Contact:
    Contact_Information:
      Contact_Organization_Primary:
        Contact_Organization: U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center
        Contact_Person: USGS SPCMSC Data Management
      Contact_Address:
        Address_Type: Mailing and physical
        Address: 600 4th Street South
        City: St. Petersburg
        State_or_Province: FL
        Postal_Code: 33701
        Country: USA
      Contact_Voice_Telephone: 727-502-8000
      Contact_Electronic_Mail_Address: gs-g-spcmsc_data_inquiries@usgs.gov
  Metadata_Standard_Name: Content Standard for Digital Geospatial Metadata
  Metadata_Standard_Version: FGDC-STD-001-1998
