Vectorized Marsh Shorelines derived from WorldView imagery for the Grand Bay National Estuarine Research Reserve in Mississippi from 2013-2020

Metadata also available as - [Outline] - [Parseable text] - [XML]

Frequently anticipated questions:

What does this data set describe?

Title:
Vectorized Marsh Shorelines derived from WorldView imagery for the Grand Bay National Estuarine Research Reserve in Mississippi from 2013-2020
Abstract:
Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into coastal management, including shoreline monitoring and change analysis. Geospatial shoreline data were created from a semi-automated methodology using WorldView (WV) satellite data between 2013 and 2020. The data were compared to contemporaneous field-surveyed Real-time Kinematic (RTK) Global Positioning System (GPS) data collected by the Grand Bay National Estuarine Research Reserve (GBNERR) and digitized shorelines from U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) orthophotos. Field data for shoreline monitoring sites was also collected to aid interpretation of results. This data release contains digital vector shorelines, shoreline change calculations for all three remote sensing data sets, and field surveyed data. The data will aid managers and decision-makers in the adoption of high-resolution satellite imagery into shoreline monitoring activities, which will increase the spatial scale of shoreline change monitoring, provide rapid response to evaluate impacts of coastal erosion, and reduce cost of labor-intensive practices. For further information regarding data collection and/or processing methods, refer to the associated journal article (Smith and others, 2021).
  1. How might this data set be cited?
    Terrano, Joseph F., and Smith, Kathryn E.L., 20210723, Vectorized Marsh Shorelines derived from WorldView imagery for the Grand Bay National Estuarine Research Reserve in Mississippi from 2013-2020:.

    This is part of the following larger work.

    Terrano, Joseph F., Smith, Kathryn E.L., Pitchford, Jonathan L., Archer, Michael, and Brochard, Michael, 20210723, Shorelines from High-resolution WorldView Satellite Imagery, Real-time Kinematic Global Positioning Data, and Aerial Imagery for 2013 to 2020 for Study Sites Within Grand Bay National Estuarine Research Reserve, Mississippi: U.S. Geological Survey data release doi:10.5066/P9W8TNQM, U.S. Geological Survey - St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -88.482027
    East_Bounding_Coordinate: -88.373059
    North_Bounding_Coordinate: 30.423355
    South_Bounding_Coordinate: 30.320389
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 17-Dec-2013
    Ending_Date: 17-Nov-2020
    Currentness_Reference:
    ground condition
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: Vector Digital Data Set (Polyline)
  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):
      • String (2693)
    2. What coordinate system is used to represent geographic features?
      Grid_Coordinate_System_Name: Universal Transverse Mercator
      Universal_Transverse_Mercator:
      UTM_Zone_Number: 16
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.9996
      Longitude_of_Central_Meridian: -87.0
      Latitude_of_Projection_Origin: 0.0
      False_Easting: 500000.0
      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 Meter
      The horizontal datum used is D_North_American_1983.
      The ellipsoid used is GRS_1980.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.257222101.
  7. How does the data set describe geographic features?
    Shorelines_WV_2013_2020.shp
    Attribute table containing attribute information associated with the 2013 to 2020 Grand Bay, MS vectorized marsh shorelines. (Source: USGS)
    Date_
    Date imagery was collected for the Mississippi and Alabama coast using the "MM/DD/YYYY HH:MM:SS" format. Additional information can be found in the "Year" field. The HH:MM:SS was set at 3:00:00 PM for all shorelines as a general placeholder. (Source: USGS)
    Range of values
    Minimum:12/17/2013 3:00:00PM
    Maximum:11/17/2020 3:00:00PM
    Year
    4-digit year in which the imagery was collected. (Source: USGS)
    Range of values
    Minimum:2013
    Maximum:2020
    Units:Year
    Accuracy
    A value representing the shoreline position uncertainty associated with the imagery type which was used in the shoreline change statistical computations reported by Hapke and others (2011). See the cross reference section of this metadata for more information. As stated above, several factors may influence the accuracy and uncertainty of shoreline position for vegetated shorelines, such as water level. Water level at the time of imagery collection is largely unknown for most historical imagery, therefore USGS staff cannot account for shoreline positional errors associated with water level. Published uncertainty estimates in Hapke and others (2011) are for sandy shorelines but were used for these shorelines. These values should be regarded as less conservative than errors that may account for uncertainty in digitization of vegetated shorelines from aerial imagery. (Source: USGS)
    ValueDefinition
    3.2Uncertainty of the shoreline position in meters.
    Source
    An identifier for the source of the vector shoreline data. (Source: USGS)
    ValueDefinition
    Earth ExplorerImagery downloaded from Earth Explorer.
    Maxar TechnologiesImagery downloaded from Maxar Technologies.
    Orig_Name
    The original name of the downloaded image file. (Source: USGS) A text string detailing the date and time the WorldView images were collected in the WV#YYYYMMDDhhmmss format. "#" represents the WorldView sensor number, "YYYY" represents the 4-digit year, "MM" represents the 2-digit year, "DD" represents the 2-digit year, "hh" represents the 2-digit hour, "mm" represents the 2-digit minute, and "ss" represents the 2-digit second.
    Download
    The web link for the imagery download. (Source: USGS) A text string describing the web address of the imagery.
    Notes
    Any data documentation notes. (Source: USGS) A text string describing the notation.
    Shape_Leng
    System-generated attribute field, which was automatically created by ArcGIS to indicate the feature length. (Source: ESRI)
    Range of values
    Minimum:5.139035
    Maximum:152081.222182
    Units:Meters
    Id
    Automatically generated number from AMBUR program. (Source: AMBUR) Sequential, unique whole numbers that are automatically generated by AMBUR. Attribute is required by AMBUR program.
    Type
    An identifier for the source of the vector shoreline data. (Source: USGS)
    ValueDefinition
    WorldViewShorelines were derived from WorldView imagery.
    Entity_and_Attribute_Overview:
    The entity and attribute information provided here describes the tabular data associated with the dataset. Please review the detailed descriptions that are provided (the individual attribute descriptions) for information on the values that appear as fields/table entries of the dataset.
    Entity_and_Attribute_Detail_Citation:
    The entity and attribute information were generated by the individual and/or agency identified as the originator of the dataset. Please review the rest of the metadata record for additional details and information. For details on AMBUR fields and analysis requirements, see Jackson (2010).

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Joseph F. Terrano
    • Kathryn E.L. Smith
  2. Who also contributed to the data set?
    Acknowledgment of the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, as a data source would be appreciated in products developed from these data, and such acknowledgment as is standard for citation and legal practices. Sharing of new data layers developed directly from these data would also be appreciated by the U.S. Geological Survey staff. Users should be aware that comparisons with other datasets for the same area from other time periods may be inaccurate due to inconsistencies resulting from changes in photointerpretation, mapping conventions, and digital processes over time. These data are not legal documents and are not to be used as such. For access and pricing for imagery please contact Maxar Technologies.
  3. To whom should users address questions about the data?
    U.S. Geological Survey St Petersburg Coastal and Marine Science Center
    Attn: Joseph F. Terrano
    Researcher III
    600 4th Street South
    St. Petersburg, FL

    727-502-8047 (voice)
    727-502-8182 (FAX)
    jterrano@contractor.usgs.gov

Why was the data set created?

This dataset contains shorelines classified from WV2 and WV3 imagery. The purpose of these data is for the calculation of shoreline change for marsh shorelines of the GBNERR from 2013-2020.

How was the data set created?

  1. From what previous works were the data drawn?
    Shorelines_WV_2013_2020.shp (source 1 of 1)
    Joseph F. Terrano and Kathryn E.L. Smith, 20210723, WorldView Shorelines of the Grand Bay National Estuarine Research Reserve from 2013 to 2020: U.S. Geological Survey, St Petersburg, Florida.

    Online Links:

    Other_Citation_Details:
    Shorelines derived from WorldView 2 and 3. Not all dates have complete study area coverage.
    Type_of_Source_Media: digital data
    Source_Contribution:
    Shorelines derived from WV2 and WV3 imagery and published as part of this study (https://doi.org/10.5066/P9W8TNQM).
  2. How were the data generated, processed, and modified?
    Date: 2021 (process 1 of 4)
    Worldview 2 and WorldView 3 imagery were downloaded from EarthExplorer and Maxar’s G-EGD for dates between 2013 and 2020. A total of eleven dated images were selected that provided either complete or partially complete coverage of the study area and included at least one image from each year from 2013 to 2020. Images were radiometrically and atmospherically corrected and then pansharpened using ERDAS IMAGINE 2020 (version 16.6.0) to obtain measures of ground reflectance. The output image was reprojected into the common projection system of Universal Transverse Mercator World Geodetic System of 1984 datum (UTM zone 16N, WGS 1984). To improve comparisons between WVS and AIS, images were co-registered to high-resolution aerial imagery (NAIP) using the AutoSync-workstation in ERDAS Image pixels. First, an NAIP image mosaic was created for an extent larger than the WV image coverage. Ground control points coincident on both images were used to adjust the WV image to the corresponding location on the NAIP. Control points with an error value greater than 1 were removed. The co-registration of the WV imagery improved the spatial accuracy of the WV imagery and allowed for the direct comparison of WV and NAIP-derived shoreline data. Person who carried out this activity:
    Joseph F. Terrano
    Researcher III
    600 4th Street South
    St.Petersburg, FL
    USA

    727-502-8047 (voice)
    jterrano@contractor.usgs.gov
    Data sources used in this process:
    • High resolution satellite imagery derived shorelines for 2013-2020.
    Date: 2021 (process 2 of 4)
    To generate vector shorelines from WV images, we followed a similar methodology described by Maglione (2014). All WV images were classified into land-water rasters using tools within ArcGIS. First, normalized difference vegetation index (NDVI) was calculated using WV band 5 in the visible red spectrum (RED) and band 7 in the near-infrared spectrum (NIR1) using the following formula: NDVI=(NIR1−RED)/(NIR1+RED). Vegetation is classified as high values (above 0.2), water represents low values (usually less than -0.2), and soil somewhere in between -0.2 and 0.2. We discovered the value of 0.21 provided an adequate representation of the shoreline (wetland-water boundary) and use that value to reclassify the NDVI to a land-water raster. The land-water raster was processed to reduce isolated pixels by using expand-shrink procedure. The resulting image classified vegetated shorelines, however some shorelines within the study area were composed of sandy beach composed of bright, sand and shells. To improve the shoreline classification for beach shorelines, we selected a threshold using band 8 (NIR2), which showed high reflectance for the beach and urban areas (we used a value of 5000), and created a new land classification that was merged with the vegetated land class to create a binomial land-water raster. Person who carried out this activity:
    Joseph F. Terrano
    Researcher III
    600 4th Street South
    St.Petersburg, FL
    USA

    727-502-8047 (voice)
    jterrano@contractor.usgs.gov
    Date: 2021 (process 3 of 4)
    Within ArcMap, the classification boundaries were smoothed to remove any extraneous cells missed in the expand and shrink steps. The raster was then converted into polygons and the polygons were converted into lines. The lines, however, still contained the ridged cell edges, so the lines were smoothed using the Polynomial Approximation with Exponential Kernel (PAEK) algorithm and a 2-meter smoothing filter. Shorelines not in the study area or shorelines improperly classified (such as nearshore sand shoals) were removed or edited. Shorelines were projected into the North American Datum of 1983 Universal Transverse Mercator Zone 16N (NAD83 UTM 16N). Person who carried out this activity:
    Joseph F. Terrano
    Researcher III
    600 4th Street South
    St.Petersburg, FL
    USA

    727-502-8047 (voice)
    jterrano@contractor.usgs.gov
    Date: 2021 (process 4 of 4)
    Shorelines were compiled from all available data sources as both previously published shorelines or ones created for this study. Regardless of the data source, shorelines were edited in ArcMAP so that only the desired shorelines were included in the final dataset. Once shorelines were edited and checked, all dated shorelines were merged into a single dataset. Attributes were edited to include information regarding the date and source of the original data. Compiled shorelines were processed using the AMBUR statistical package for R (version 4.0.4) tool to add required missing attributes. AMBUR performs shoreline change analysis on vector digital shorelines. All necessary attribute fields must be present in order to run various AMBUR functions; the following fields are required for boundaries: "Id", "DATE_", "ACCURACY", "SHORE_LOC", "CLASS_1", "CLASS_2", "CLASS_3", and "GROUP". In order to determine if all the required fields were present in the merged boundary datasets, an AMBUR sub-routine (ambur.check) was used to check all shoreline shapefiles for missing attribute fields. For more information about the AMBUR shoreline requirements see the AMBUR user manual (Jackson, 2010). Some fields created by AMBUR ("SHORE_LOC", "CLASS_1", "CLASS_2", "CLASS_3", and "GROUP") are required and have null values as placeholders, thus they should not be used for any other analysis ourtide of AMBUR. Null fields were left in the results as they are required by AMBUR and are needed to replicate our study. Users are advised to review the data to determine if it is suitable for their studies. Person who carried out this activity:
    Joseph F. Terrano
    Researcher III
    600 4th Street South
    St.Petersburg, FL
    USA

    727-502-8047 (voice)
    jterrano@contractor.usgs.gov
  3. What similar or related data should the user be aware of?
    Hapke, C.J., Himmelstoss, E.A., Kratzmann, M.G., List, J.H. and Thieler, E.R., 2011, National assessment of shoreline change: Historical shoreline change along the New England and Mid-Atlantic coasts: U.S. Geological Survey Open-File Report 2010-1118, U.S. Geological Survey, Reston, VA.

    Online Links:

    Jackson, C.W., Jr., 2010, Basic User Guide for the AMBUR package for R, version 1.0a: Unknown, Unknown.

    Online Links:

    Other_Citation_Details:
    User guide includes requirements for shorelines that are to be run through Analyzing Moving Boundaries Using R (AMBUR).
    Maglione, P., Parente, C. and Vallario, A., 2014, Coastline extraction using high resolution WorldView-2 satellite imagery: European Journal of Remote Sensing, United Kingdom.

    Online Links:

    Other_Citation_Details: Defines an "apparent shoreline" on page 177.
    U.S. Geological Survey, 2021, EarthExplorer: U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Repository used to acquire remotely sensed imagery (NAIP and WV). Commercial satellite imagery (such as WV) is only available to qualified Federal users at no cost and must contact the USGS Earth Resources Observation & Science Center (EROS) for requirements.
    Technologies, Maxar, 2021, Global Enhanced GEOINT Delivery (G-EGD): Maxar Technologies (formerly DigitalGlobe Inc.), Westminster, CO.

    Online Links:

    Other_Citation_Details:
    Commercial satellite imagery repository. For access requirements please contact Maxar Technologies.
    Smith, K.E.L., Terrano, J.F., Pitchford, J.L., Archer, M., 2021, Coastal wetland shoreline change monitoring: A comparison of shorelines from high-resolution WorldView satellite imagery, aerial imagery, and field surveys: Special Issue; New Insights into Ecosystem Monitoring Using Geospatial Techniques Unknown, MDPI; Remote Sensing, Basel, Switzerland.

    Online Links:

    • Unknown

    Other_Citation_Details:
    Associated journal article with additional methodology, data analysis, and results.

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

  1. How well have the observations been checked?
    No formal attribute accuracy tests were conducted.
  2. How accurate are the geographic locations?
    A formal accuracy assessment of the horizontal positional information in the dataset has not been conducted. Elevation and water levels were not addressed in this study. For additional information on data collection techniques see the source metadata.
  3. How accurate are the heights or depths?
    Several factors may influence the accuracy and uncertainty of shoreline position for vegetated shorelines, such as water level. Water level at the time of imagery collection was not taken into account when deriving shorelines. Published general uncertainty estimates for shorelines were used for all shorelines in this study based on the data source (satellite derived, aerial imagery, GPS). WV imagery classifications were checked along study area shorelines to ensure the land/water classification was correct. WV shorelines cover extensive amounts of Grand Bay and not all shorelines beyond the transects were checked for detailed accuracy. The classification also has potential variations in shoreline positions from other published data due to image interpretation differences.
  4. Where are the gaps in the data? What is missing?
    Dataset is considered complete for the information presented. Some dated shorelines do not have complete coverage over the entire study area. GPS shorelines were only collected at specific sites and do not cover the entire study area. NAIP shorelines were digitized to match GPS site locations and do not represent full shorelines. WV data was subject to image availability and not all dates cover the entire study area. Users are advised to read the rest of the metadata record carefully for additional details.
  5. How consistent are the relationships among the observations, including topology?
    Vector shoreline features and attributes were checked for completeness and accuracy within ArcGIS.

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:
The U.S. Geological Survey requests to be acknowledged as originator of the data in future products or derivative research. This metadata record should be reviewed in its entirety to ensure specific data are suitable for other studies. WorldView imagery remains the property of Maxar Technologies (Maxar, 2012) and is not published in this data release. Aerial imagery from Earth Explorer is publically avaliable and free to doenload (Earth Explorer, 2021)
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey St Petersburg Coastal and Marine Science Center
    Attn: Joseph F. Terrano
    Researcher III
    600 4th Street South
    St. Petersburg, FL

    727-502-8047 (voice)
    727-502-8182 (FAX)
    jterrano@contractor.usgs.gov
  2. What's the catalog number I need to order this data set? Shorelines_WV_2013_2020.shp
  3. What legal disclaimers am I supposed to read?
    This digital 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, 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?

Who wrote the metadata?

Dates:
Last modified: 21-Jul-2021
Metadata author:
U.S. Geological Survey St Petersburg Coastal and Marine Science Center
Attn: Joseph F. Terrano
Researcher III
600 4th Street South
St. Petersburg, FL

727-502-8047 (voice)
727-502-8182 (FAX)
jterrano@contractor.usgs.gov
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/spcmsc/Shorelines_WV_2013_2020_metadata.faq.html>
Generated by mp version 2.9.50 on Tue Sep 21 18:18:52 2021