Transects with linear regression rates of change for GPS, Worldview, and aerial image shorelines for the Grand Bay National Estuarine Research Reserve in Mississippi from 2013-2020

For methods used to derive shorelines please refer to the GPS, AI, or WorldView shoreline metadata records in this data release. 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 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 10 meters. Length varied depending on location, and so a length longer than the largest shoreline distance to ensure transects covered 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. Please see the shoreline datasets to determine the estuarine shorelines analyzed. Final transects were checked and edited, if necessary, in ArcGIS (version 10.5.1) in order to improve analysis results and improve shoreline coverage. Transects were manually edited to reduce errors in the analyses or to provide a more perpendicular intersection with the shorelines. 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 meters (the units of measure for the map is for Universal Transverse Mercator; in meters), analysis type is advanced (advanced includes additional statistics for a robust linear regression), and time unit for rates is year (utilizes years for calculating rates of shoreline change). More information on the AMBUR program can be obtained from Jackson (2010). AMBUR was run three separate times (once using WV shorelines, once using AI shorelines, and once using GPS shorelines) to calculate the rates of change for each shoreline type. Transects not covering study area shorelines or transects with less than three dates were removed. All fields except the transect number, min and max date, number of dates, elapsed years, and LRR fields were deleted.

Within ArcMap, the WV, AI, and GPS attribute tables were merged together. Fields were renamed so each data type had a unique identifier ("_w" for WV shorelines, "_g" for GPS shorelines, "_a" for AI shorelines). Lastly, a "site" field was added. The table was checked for errors or null values.