Shorelines, shorepoints, and transects with rates for the Point Aux Chenes and Grand Bay Estuaries in Mississippi and Alabama from 1848 to 2023

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Frequently anticipated questions:

What does this data set describe?

Title:
Shorelines, shorepoints, and transects with rates for the Point Aux Chenes and Grand Bay Estuaries in Mississippi and Alabama from 1848 to 2023
Abstract:
This dataset represents a compilation of vector shorelines, shorepoints, and transects with rates for the Point Aux Chenes and Grand Bay estuaries in Mississippi and Alabama from 1848 to 2023. Shoreline data were obtained from multiple data sources, including the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the Grand Bay National Estuarine Research Reserve (GNDNERR), and the Mississippi Office of Geology (MOG). All shoreline data types have uncertainty associated with delineating the shoreline location, particularly with vegetated coastlines. For this study, the "apparent shoreline" was mapped for all data sources. The "apparent shoreline" is defined as "where the actual shoreline is obscured by marsh, mangrove, cypress, or other type of marine vegetation, the outer edge of the vegetation is mapped (Shalowitz, 1964). In the case of aerial imagery, vegetation-water boundary was digitized (Smith and others, 2021). Field surveys identified the edge of the dominant vegetation or the eroding scarp line (Smith and others, 2021). WorldView satellite imagery was classified using the normalized difference vegetation index (NDVI) (Maglione and others, 2014; Smith and others, 2021). Regardless of the source, all shorelines were merged into a single file to generate shorepoints and transects, in order to conduct shoreline change analyses. Datasets were compiled and analyzed using the R package Analyzing Moving Boundaries Using R (AMBUR) program (Jackson, 2010). This data release contains shorelines from 1848-2023 along with transects with rates of change joined to the data table, and shorepoints. Several shorelines were specifically digitized for use with transects in this study or have limited spatial resolution and are described in the attribute table or in this metadata record. This data release is an expansion of a previously published 1848-2017 shoreline change data release (Terrano and others, 2018).
  1. How might this data set be cited?
    Terrano, Joseph F., Smith, Kathryn E.L., Pitchford, Jonathan, and Archer, Michael, 20241113, Shorelines, shorepoints, and transects with rates for the Point Aux Chenes and Grand Bay Estuaries in Mississippi and Alabama from 1848 to 2023:.

    This is part of the following larger work.

    Terrano, Joseph F., Smith, Kathryn E.L., Pitchford, Jonathan, and Jenkins, Robert L. III, 20241113, Estuarine Shoreline, Upland Boundary, and Marsh Habitat Change Analyses for the Point Aux Chenes and Grand Bay Estuary Systems, Mississippi and Alabama: U.S. Geological Survey data release doi:10.5066/P1HZES2R, U.S. Geological Survey, St. Petersburg, FL.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -88.522752
    East_Bounding_Coordinate: -88.293545
    North_Bounding_Coordinate: 30.425254
    South_Bounding_Coordinate: 30.316464
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date:
    Ending_Date: 31-Jan-2023
    Currentness_Reference:
    ground condition
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: vector digital data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      This is a Vector data set.
    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_1848_2023.shp, Shoreline_shorepoints_1848_2023.shp
    Attribute table associated with the 1848 to 2023 Grand Bay MS/AL vectorized marsh shorelines and shorepoints shapefiles. This is not the complete list of attributes for these datasets. For the remaining attributes and their definitions, please refer to the accompanying data dictionary, AMBUR_Transect_Attributes.docx, included with this data download (Shoreline_change_analysis.zip). (Source: USGS)
    Region
    An identifier for the general location of the vector shorepoint data. This field is only present in Shoreline_shorepoints_1848_2023.shp. (Source: USGS)
    ValueDefinition
    Point Aux ChenesData is within the Point Aux Chenes area.
    Middle BayData is within the Middle Bay area.
    Grand BayData is within the Grand Bay area.
    South RigoletsData is within the South Rigolets area.
    Date_
    Date imagery or shoreline was collected 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. "Date_" is the required field name used by AMBUR. (Source: USGS)
    Range of values
    Minimum:01/01/1848 3:00:00 PM
    Maximum:01/31/2023 3:00:00 PM
    Year
    4-digit year in which the imagery was collected. (Source: USGS)
    Range of values
    Minimum:1848
    Maximum:2023
    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). As stated previously, 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. Error values are less conservative than errors that may account for uncertainty in digitization of vegetated shorelines from aerial imagery or satellite imagery. The 2017 USGS GPS shoreline accuracy was calculated based on the average positional error of the GPS points for each line segment. The MOG and GNDNERR GPS data was assigned a 5-meter uncertainty value based on reported values in the MOG source metadata. The 2010 and 2012 uncertainty values were computed as the square root of the sum of squares of the image resolution, image uncertainty, and the maximum digitization error of 1 meter. For additional information, see the source metadata. (Source: USGS)
    Range of values
    Minimum:0.0054
    Maximum:10.8
    Units:meters
    Source
    An identifier for the source of the vector shoreline data. (Source: USGS)
    ValueDefinition
    GNDNERRData collected by the Grand Bay National Estuarine Research Reserve.
    MS Office of GeologyMississippi Office of Geology digitized shorelines.
    NOAANOAA digitized topographic sheet (t-sheet) shorelines.
    USGSData collected or digitized by the USGS Coastal and Marine Science Center- St. Petersburg, FL.
    Orig_Name
    The original name of the downloaded file. (Source: USGS) A text string describing the name of the file as it was downloaded from the original source or created by the USGS.
    Download
    The web link for the source of the original data. (Source: USGS) A text string describing the web address for the original source of the imagery or shoreline.
    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 (ArcMap or ArcGIS Pro) to indicate the shoreline length (shoreline file only). (Source: ESRI)
    Range of values
    Minimum:0.013884
    Maximum:129069.641286
    Entity_and_Attribute_Overview:
    Shoreline_change_analysis.zip: All remaining attribute information not presented in the above section for the shorelines (Shorelines_1848_2023.shp) and shorepoints (Shoreline_shorepoints_1848_2023.shp) and all entity and attribute information for the transects (Transects_with_rates_1848_2023.shp) were generated by AMBUR (Jackson, 2010). These attributes are defined in the accompanying data dictionary, AMBUR_Transect_Attributes.docx, included with this data download (Shoreline_change_analysis.zip). Unless otherwise noted, no data values are left blank. All distance units are in meters and time units are in years. Therefore, rates of change are presented in meters per year (m/yr). AMBUR produces numerous fields during the analysis, most of which are not relevant to the final dataset. These blank fields were not removed to provide consistency with other published data and to provide users all the necessary information to reproduce results. Transects that intersected two or fewer shorelines only calculated net shoreline movement (NSM) and end point rate (EPR) statistics.
    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.

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
    • Jonathan Pitchford
    • Michael Archer
  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. These data are not legal documents and are not to be used as such. WorldView imagery was accessed through a special use agreement with Maxar Technologies (Maxar, 2022).
  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
    Physical Scientist
    600 4th Street South
    St. Petersburg, FL

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

Why was the data set created?

The purpose of these data is to examine the shoreline change rates for estuarine shorelines for the Point Aux Chenes and Grand Bay estuaries in Mississippi and Alabama from 1848 to 2023.

How was the data set created?

  1. From what previous works were the data drawn?
    Shorelines (1848-2017) (source 1 of 3)
    Terrano, J.F., Smith, K.E.L., Pichford, J., McIlwain, J., and Archer, M., 20180926, Shoreline Change Analysis for the Grand Bay National Estuarine Research Reserve, Mississippi Alabama: 1848 to 2017: U.S. Geological Survey, St. Petersburg, Florida.

    Online Links:

    Other_Citation_Details: Provides shorelines for Grand Bay from 1848-2017.
    Type_of_Source_Media: digital data
    Source_Contribution:
    Shorelines previously published within the Grand Bay region from 1848-2017.
    EarthExplorer imagery (source 2 of 3)
    EarthExplorer, 2023, EarthExplorer Imagery: U.S. Geological Survey, Reston, VA.

    Online Links:

    Type_of_Source_Media: digital data
    Source_Contribution:
    Repository used to acquire remotely sensed imagery such as 1) modern high resolution National Agricultural Imagery Program (NAIP) or 2) historical imagery (such as 1942 black and white images).
    WorldView 2022 imagery (source 3 of 3)
    Maxar, 2022, Global Enhanced GEOINT Delivery (G-EGD): Maxar Technologies (formerly DigitalGlobe Inc.), Westminster, CO.

    Online Links:

    Type_of_Source_Media: digital data
    Source_Contribution:
    Commercial satellite (WorldView) imagery repository. WorldView 2 satellite imagery (image ID number WV220220511164242) was obtained through the National Aeronautics and Space Administration (NASA) Commercial Smallsat Data Acquisition (CSDA) program. For access requirements, contact Maxar Technologies.
  2. How were the data generated, processed, and modified?
    Date: 2018 (process 1 of 5)
    Shorelines for 1848-2017 were downloaded from the Terrano and others (2018) data release as shapefiles (.shp) that were projected into the North American Datum of 1983 Universal Transverse Mercator zone 16 North (NAD83 UTM 16N). These shorelines were already in the necessary format for the shoreline change analysis and were not modified for use in this study. Since these shorelines originated from several internet sources or were created by the USGS, please refer to Terrano and others (2018) for data sources, processing steps, and attribute accuracy reports related to these shorelines. Person who carried out this activity:
    Joseph F. Terrano
    Physical Scientist
    600 4th Street South
    St. Petersburg, FL
    USA

    727-502-8047 (voice)
    jterrano@usgs.gov
    Data sources used in this process:
    • Terrano and others (2018)
    Date: 2023 (process 2 of 5)
    From 2013 to 2023, coastal managers surveyed shoreline positions using Real-time Kinematic (RTK) GPS at eleven locations in GNDNERR. Shorelines from 2013-2017 were previously published in Terrano and others (2018). Shorelines from 2018-2023 were collected as part of this study using similar methods to the 2013-2017 data. GPS data were collected using a Trimble R8 Model 3 Global Navigation Satellite System (GNSS) and TSC3 data collector from 2013 to 2018, or a Trimble R10 GNSS system and TSC3 data collector from 2018 to 2020. Each was attached onto a 2 m graphite rod with a mounted foot to obtain both horizontal and vertical shoreline position. The positional accuracy of Trimble R8 Model 3 GPS points was ± 10 millimeters (mm) + 1 parts per million (ppm) root mean square (RMS) horizontal error and ± 20 mm + 1 ppm RMS vertical error. The horizontal error of the Trimble R10 GPS points was ± 8 mm + 0.5 ppm RMS and vertical error was ± 15 mm + 0.5 ppm RMS. The points were collected roughly 5 to 10 meters apart along the vegetation-water boundary, which typically represented the top of an erosional scarp. In instances where an erosional scarp was not visible, the most suitable shoreline position based on dense shoreline vegetation was mapped. Shorelines were mapped at GNDNERR quarterly erosion sites or at USGS study sites and do not have full study area coverage. GPS points were then converted into a shapefile. The points were converted into vector shorelines using the XTools Pro (v.17) "polylines from points" tool. The location between each point was interpolated, so the specific shoreline location between each point may not represent the actual shoreline position. Person who carried out this activity:
    Joseph F. Terrano
    Physical Scientist
    600 4th Street South
    St. Petersburg, FL
    USA

    727-502-8047 (voice)
    jterrano@usgs.gov
    Data sources used in this process:
    • Shorelines from 1848-2017 published in Terrano and others (2018)
    Data sources produced in this process:
    • Vectorized GPS point-based shorelines for 2013-2023
    Date: 2023 (process 3 of 5)
    WorldView 2 imagery from 20220511 (YYYYMMDD, image ID number WV220220511164242) was downloaded from Maxar’s G-EGD. The 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 World Geodetic System of 1984 Universal Transverse Mercator zone 16 North coordinate system (WGS84 UTM zone 16N). The image was then 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. A methodology similar to that described by Maglione and others (2014) was used to generate vector shorelines from WorldView (WV) images. All WV images were classified into land-water rasters using tools within ArcGIS Pro. Then, 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). High values (above 0.2) are classified as vegetation, low values (less than -0.2) as water, and in between values (-0.2 to 0.2) as soil. A value of 0.21 provides an adequate representation of the shoreline (wetland-water boundary) and that value was used 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. Due to the high reflectance of beach and urban areas a second classification using band 8 (NIR2) with a threshold value of 5000 was used. Values above 5000 were considered urban or beach. The beach/urban classification was merged with the vegetated land classification to create a binomial land-water raster. In 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 polylines. To smooth the ridged cell edges, the lines were smoothed using the Polynomial Approximation with Exponential Kernel (PAEK) algorithm at a 2-meter smoothing filter. A final quality control was conducted and any shorelines that were not in the study area or shorelines improperly classified (such as nearshore sand shoals) were removed or manually edited. A second USGS GIS user then conducted a second quality control check and updates were made as necessary. Shorelines were projected into NAD83 UTM 16N. The shoreline was run through the Arc Pro "Generalize" tool set to a filter of 1 meter to reduce the number of shoreline vertices. Person who carried out this activity:
    Joseph F. Terrano
    Physical Scientist
    600 4th Street South
    St. Petersburg, FL
    USA

    727-502-8047 (voice)
    jterrano@usgs.gov
    Data sources used in this process:
    • Maxar WorldView 2 satellite imagery from 2022.
    Data sources produced in this process:
    • High resolution satellite imagery derived shorelines for 2022
    Date: 2024 (process 4 of 5)
    The vectorized shorelines that were produced in the previous process steps were compiled in ArcMap. These vectorized shorelines were manually 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 shapefile for inclusion in this data release, Shorelines_1848_2023.shp. Attributes were edited to include information regarding the date and source of the original data. The compiled shorelines were processed using the Analyzing Moving Boundaries Using R (AMBUR) statistical package for R (version 4.0.4) to add required missing attributes and calculate shoreline change rates. AMBUR performs shoreline change analysis on vector digital shorelines (Jackson, 2010). 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. During the shoreline change analysis, AMBUR also creates shorepoints. A shorepoint was created at each transect and shoreline intersect point. Several transects intersected shorelines that doubled back or intersected both sides of an island. In these instances, multiple shorepoints were created for the same date on the same transect. To remove the duplicate points, the shorepoint file was then run through an R code to remove all shorepoints after the first intersection for each date. 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. Several islands within the study area were not used in the shoreline change analysis as they were too far offshore but were retained in the shoreline data set. Null fields were left in the attribute table as they are required by AMBUR and are needed to replicate this study. Person who carried out this activity:
    Joseph F. Terrano
    Physical Scientist
    600 4th Street South
    St. Petersburg, FL
    USA

    727-502-8047 (voice)
    jterrano@usgs.gov
    Data sources used in this process:
    • Terrano and others (2018) - 1848-2017 shorelines
    • Vectorized GPS point-based shorelines for 2013-2023
    • High resolution satellite imagery derived shorelines for 2022
    Data sources produced in this process:
    • Shorelines_1848_2023.shp
    • Shorepoints_1848_2023.shp
    Date: 2024 (process 5 of 5)
    Transects were generated by buffering the shoreline dataset produced in the previous step to create inner (land-based) and outer (water-based) baselines. The baselines form the start and end point for shoreline-perpendicular transects. Baselines were input into the AMBUR statistical package for R (using R version 4.0.4). AMBUR has several tools, which utilize shoreline parallel baselines to generate transects that are generally perpendicular to the shoreline. Transects were constructed at a sampling distance of 50 meters. Length varied from 1000 to 3000 meters, depending on location, and was selected to cover all dated shorelines. Once transects were created, the "Filter Transects" tool was used to adjust and even out the spread of transects. Where shorelines experience sharp bends, such as in small bays and narrow spits, transects may fall at a non-perpendicular angle. Small islands located within 50 meters of the main island boundary were considered a part of the barrier island system and were included in the analyses. Final transects were checked and edited in ArcGIS Pro, if necessary, in order to improve analysis results and improve shoreline coverage. Transects were manually edited to reduce errors in the analyses. Shoreline points and final statistical analyses were completed in AMBUR to generate the shoreline change rates. The following analysis parameters were used: first intersection (if transect intersects the same shoreline more than once, then by default it selected the first intersection), confidence level 95 (confidence level for the linear regression statistics), unit label m (the units of measure for the map is for Universal Transverse Mercator and in meters), analysis type is advanced (advanced includes additional statistics for a robust linear regression), and time unit for rates is yr (utilizes years for calculating rates of shoreline change). For more information on the AMBUR program, refer to Jackson (2010). Person who carried out this activity:
    Joseph F. Terrano
    Physical Scientist
    600 4th Street South
    St. Petersburg, FL
    USA

    727-502-8047 (voice)
    jterrano@usgs.gov
    Data sources used in this process:
    • Shorelines_1848_2023.shp
    • Shorepoints_1848_2023.shp
    Data sources produced in this process:
    • Transects_with_rates_1848_2023.shp
  3. What similar or related data should the user be aware of?
    Shalowitz, Aaron L., 1964, Shore and Sea Boundaries: U.S. Government Printing Office, Washington D.C..

    Online Links:

    Other_Citation_Details: Defines an "apparent shoreline" on page 177.
    Smith, Kathryn E.L., Terrano, Joseph F., Pitchford, Jonathan L., and Archer, Michael J., 2021, Coastal Wetland Shoreline Change Monitoring: A Comparison of Shorelines from High-Resolution WorldView Satellite Imagery, Aerial Imagery, and Field Surveys: Remote sensing Volume 13, Issue 15 (New Insights into Ecosystem Monitoring Using Geospatial Techniques), MDPI, St. Petersburg, Florida.

    Online Links:

    Other_Citation_Details: Smith and others (2021)
    Jackson, C.W., Jr., 2010, Basic User Guide for the AMBUR package for R: Chester W. Jackson Jr., Online.

    Online Links:

    Other_Citation_Details:
    User guide includes requirements for shorelines that are to be run through AMBUR
    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:

    Maglione, P., Parente, C. and Vallario, A., 20140204, Coastline extraction using high resolution WorldView-2 satellite imagery: European Journal of Remote Sensing Volume 47, Issue 1, Taylor & Francis Group, London, United Kingdom.

    Online Links:

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

  1. How well have the observations been checked?
    Shoreline change rates are influenced by availability and accuracy of shoreline data. Analyses of highly dynamic areas are particularly challenging, including 1) areas near inlets, where there are excessively dynamic depositional/erosional sand bars that may appear/disappear rapidly, and 2) tidal creeks, where the land/water line is hard to distinguish due to sporadic vegetation lines. 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.
  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 is largely unknown for most historical imagery, therefore USGS staff cannot account for shoreline positional errors associated with water level. Published uncertainty estimates for sandy shorelines were used for all shorelines in this study, with the exception of 1993, 1995, 1999, 2001, 2010, 2012, and 2017. Shorelines in this study, with the exception of the dates above, are less conservative than errors that may account for uncertainty in digitization of vegetated shorelines from aerial imagery or satellite imagery. For additional information on data collection techniques or imagery information, please refer to the source agency or source metadata.
  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 (for example, the 2017 shorelines were collected using global positioning system (GPS) and are only available for select study areas). This was acceptable as the analysis method accounts for the available dates only. In addition, select shoreline dates (1942, 1975, 1986, 1992, 2004, 2006, and 2014) were created using a point intersection of shoreline and transect, and are intended for use only with the transects also published in this data release. The 2022 WorldView shoreline was generalized using a 1-meter (m) filter to reduce the number of shoreline vertices. The generalization was acceptable because it only changed some shoreline positions by sub-meter distances. Islands not used in the shoreline change analysis were added back into the final published dataset because they were used to create the raster dataset also published in this data release. AMBUR produces numerous fields during the analysis, most of which are not relevant to the final dataset. Therefore, blank fields are considered acceptable because they have no impact on the final result. These blank fields were not removed to provide consistency with other published data and to provide users all the necessary information to reproduce results. 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 features and attributes were checked for completeness and accuracy. Linework is generated by the "Construct transects" and "Filter transects" algorithm in the AMBUR program at a perpendicular angle to the shorelines. In areas where shorelines experience sharp bends, such as in small bays and narrow spits, the filter algorithm often created transects that were not perpendicular to the shoreline. If necessary, transects were manually edited so they crossed the shorelines in a perpendicular direction.

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. Some shoreline data were developed to calculate long and short-term shoreline change rates for specific locations and may not be suitable for studies using different transects. Aerial imagery from Earth Explorer is publicly available and free to download (Earth Explorer, 2023). WorldView imagery remains the property of Maxar Technologies and was accessed through a special use agreement with Maxar Technologies (Maxar, 2022).
  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
    Saint Petersburg, FL
    United States

    727-502-8000 (voice)
    gs-g-spcmsc_data_inquiries@usgs.gov
  2. What's the catalog number I need to order this data set? Shorelines_1848_2023.shp, Shoreline_shorepoints_1848_2023.shp, and Transects_with_rates_1848_2023.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: 13-Nov-2024
Metadata author:
U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center
Attn: USGS SPCMSC Data Management
600 4th Street South
Saint Petersburg, FL
United States

727-502-8000 (voice)
gs-g-spcmsc_data_inquiries@usgs.gov
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/spcmsc/Shoreline_change_analysis_1848_2023_metadata.faq.html>
Generated by mp version 2.9.51 on Wed Nov 13 11:36:15 2024