Transects with Shoreline Change Rates for the Grand Bay National Estuarine Research Reserve in Mississippi and Alabama from 1848 to 2017
This dataset contains shoreline change rates for the Grand Bay National Estuarine Research Reserve from 1848 to 2017. Shoreline data were obtained from multiple data sources, including the U.S. Geological Survey (USGS), National Oceanic and Atmospheric Administration (NOAA), the Grand Bay National Estuarine Research Reserve(GBNERR), and the Mississippi Office of Geology (MOG). Datasets were compiled and analyzed using the R package Analyzing Moving Boundaries Using R (AMBUR) program. Rates of shoreline change can be used for evaluating living shoreline resources, decision-making for future resource planning, and restoration of both protected and open-ocean shorelines.
Terrano, Joseph F., and Smith, Kathryn E.L., 20180911, Transects with Shoreline Change Rates for the Grand Bay National Estuarine Research Reserve in Mississippi and Alabama from 1848 to 2017: U.S. Geological Survey Data Release doi:10.5066/P9JMA8WK, U.S. Geological Survey, St. Petersburg, FL.
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.
The entity and attributes in these datasets are compiled and generated by the AMBUR program given the input shoreline dataset and transects. No data values are left blank. All distance units are in meters and time units are in years. Therefore, rates of change would be in meters per year. AMBUR produces an attribute table with over 50 fields, most of which are not used in this analysis, so extra fields were removed from the attribute table. The statistics that this analysis focuses on are the NSM, EPR, LRR, LRR R squared, WLR, and WLR R squared. For attribute definitions, see p. 37 of: Jackson, C.W., Jr. (2010)(also included in Transects_with_Rates.zip).
Please review the rest of the metadata record for additional details and information. For details on AMBUR programming code, statistical analyses, and attributes, see the AMBUR project on the R-Forge web site (http://ambur.r-forge.r-project.org/) and the documentation: Jackson, C.W., Jr., 2010.
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.
Joseph F. Terrano, Kathryn E.L. Smith, Jonathan Pitchford, Julius McIlwain, and Michael Archer, 20180911, Vectorized Marsh Shorelines for the Grand Bay National Estuarine Research Reserve in Mississippi and Alabama from 1848 to 2017: U.S. Geological Survey, St Petersburg, FL.
Transects were generated by buffering the available shoreline datasets 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 (version 3.4.3). 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. Please see the shoreline dataset, Shorelines_1848_2017.zip, to determine the estuarine shoreline analyzed. Final transects were checked and edited in ArcGIS (Version 10.5.1), 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). More information on the AMBUR program can be obtained from Jackson, C.W., Jr. (2010).
Person who carried out this activity:
Joseph F. Terrano
U.S. Geological Survey
600 4th St S
St Petersburg, FL
Date: 13-Oct-2020 (process 2 of 2)
Added keywords section with USGS persistent identifier as theme keyword.
Person who carried out this activity:
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.
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, 2017 shorelines were collected using a GPS system and are only available for select study areas); however, this was acceptable as the analysis method accounts for the available dates only. Users are advised to read the rest of the metadata record carefully for additional details.
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 and are generally perpendicular to the shorelines. However, where shorelines experience sharp bends, such as in small bays and narrow spits, the filter algorithm can create transects that are not perpendicular to the shoreline.
The U.S. Geological Survey requests to be acknowledged as originator of the data in future products or derivative research. 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 creek shorelines where the vegetation/water line is not easily distinguished. Transects were modified so they crossed the shorelines in a perpendicular direction, but some small peninsulas were difficult to determine a perpendicular direction. Users of this data should examine the variables and values closely to determine if the analyses are appropriate for their intended purpose.
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.