Description: 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.
Copyright Text: 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.
Description: This dataset represents a compilation of vector shorelines in the Grand Bay National Estuarine Research Reserve (Mississippi and Alabama) from 1848 to 2017. 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 (GBNERR), 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. Field-surveys identified the edge of the dominate vegetation or the eroding scarp line. Shorelines were obtained from the original provider, or digitized, and merged into a single file, in order to conduct shoreline change analyses. 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. This data release contains shorelines from 1848-2017 along with transects with rates of change joined to the data table. This metadata record should be reviewed in its entirety to ensure specific data is suitable for other studies as some shorelines were specifically digitized for use with transects in this study. Shorelines from 1942, 1975, 1986, 1992, 2004, 2006, 2014 have limited spatial resolution. All shorelines labeled GBNERR in the Source field of the attribute table, and 2016 and 2017 GPS shorelines from the USGS, are previously unpublished data sets.
Copyright Text: 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.