Quantitative/qualitative analyses of fetch data for the coast were completed for most barrier island and backbarrier areas where data permitted based on previous shoreline change location from AMBUR shoreline analyses. Comparisons of fetch data vs shoreline change data were conducted and some trends can be ascertained. Statistical significance was not found in regression analyses; however, this may be in part due to data limitations. Future updates of the shoreline dataset for Georgia will greatly assist by employing new digitizing techniques and having a uniform shoreline for a given date/year instead of “modern” shoreline consisting of multiple years spanning a decade, making up one continuous shoreline. Hence, why the fetch analyses are more accurate around the barrier islands and backbarriers because those shorelines in the original AMBUR shoreline change dataset contain identical dates and have higher accuracy. Four primary functions were written for the fetch tool in R: ambur.fetch.radial.transects, ambur.fetch.capture, ambur.fetch.addmaxlines, and ambur.fetch.analysis. The ambur.fetch.radial.transects function allows the user to chose transect point locations (GIS shapefile) from an existing AMBUR shoreline change analysis. The user defines the number of transects to construct that radiate out in 360 degrees at each location in 5 degree increments. Next, the user employs the ambur.fetch.capture function to intersect the fetch transects with the most recent shoreline. The ambur.fetch.addmaxlines function is then used to add locations where transects did not intersect the shoreline and represents areas of maximum or “infinite” fetch. Finally, the ambur.fetch.analysis function is used to analyze the fetch data and generates point and polyline shapefiles with fetch statistics such as standard deviation, mean, and max fetch distance. Subsequently, rankings are assigned from "very low" to "very hgh" for both the maximum and average fetch statistics.