Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into coastal management, including shoreline monitoring and change analysis. Geospatial shoreline data were created from a semi-automated methodology using WorldView (WV) satellite data between 2013 and 2020. The data were compared to contemporaneous field-surveyed Real-time Kinematic (RTK) Global Position System (GPS) data collected by the Grand Bay National Estuarine Research Reserve and digitized shorelines from U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) orthophotos. Field data for shoreline monitoring sites was also collected to aid interpretation of results. This data release contains digital vector shorelines, shoreline change calculations for all three remote sensing data sets, and field surveyed data. The data will aid managers and decision-makers in the adoption of high-resolution satellite imagery into shoreline monitoring activities, which will increase the spatial scale of shoreline change monitoring, provide rapid response to evaluate impacts of coastal erosion, and reduce cost of labor-intensive practices. For further information regarding data collection and/or processing methods, refer to the associated journal article (Smith and others, 2021).

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.

To better understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites (Sites 5, 6, 7, and 8) along the Point Aux Chenes Bay shoreline of the Grand Bay National Estuarine Research Reserve (GNDNERR), Mississippi. These datasets were collected to serve as baseline data prior to the installation of a living shoreline (a subtidal sill). Each site consisted of five plots located along a transect perpendicular to the marsh-estuary shoreline at 5-meter (m) increments (5, 10, 15, 20, and 25 m from the shoreline). Each plot contained six net sedimentation tiles (NST) that were secured flush to the marsh surface using polyvinyl chloride (PVC) pipe. NST are an inexpensive and simple tool to assess short- and long-term deposition that can be deployed in highly dynamic environments without the compaction associated with traditional coring methods. The NST were deployed for three month sampling periods, measuring sediment deposition from July 2018 to January 2020, with one set of NST being deployed for six months. Sediment deposited on the NST were processed to determine physical characteristics, such as deposition thickness, volume, wet weight/dry weight, grain size, and organic content (loss-on-ignition [LOI]). For select sampling periods, ancillary data (water level, elevation, and wave data) are also provided in this data release. Data were collected during USGS Field Activities Numbers (FAN) 2018-332-FA (18CCT01), 2018-358-FA (18CCT10), 2019-303-FA (19CCT01, 19CCT02, 19CCT03, and 19CCT04, respectively), and 2020-301-FA (20CCT01). Additional survey and data details are available from the U.S. Geological Survey Coastal and Marine Geoscience Data System (CMGDS) at, https://cmgds.marine.usgs.gov/. Data collected between 2016 and 2017 from a related NST study in the GNDNERR (Middle Bay and North Rigolets) can be found at https://doi.org/10.5066/P9BFR2US. Please read the full metadata for details on data collection, dataset variables, and data quality.

Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into coastal management, including shoreline monitoring and change analysis. Geospatial shoreline data were created from a semi-automated methodology using WorldView (WV) satellite data between 2013 and 2020. The data were compared to contemporaneous field-surveyed Real-time Kinematic (RTK) Global Positioning System (GPS) data collected by the Grand Bay National Estuarine Research Reserve (GBNERR) and digitized shorelines from U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) orthophotos. Field data for shoreline monitoring sites was also collected to aid interpretation of results. This data release contains digital vector shorelines, shoreline change calculations for all three remote sensing data sets, and field surveyed data. The data will aid managers and decision-makers in the adoption of high-resolution satellite imagery into shoreline monitoring activities, which will increase the spatial scale of shoreline change monitoring, provide rapid response to evaluate impacts of coastal erosion, and reduce cost of labor-intensive practices. For further information regarding data collection and/or processing methods, refer to the associated journal article (Smith and others, 2021)

Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into coastal management, including shoreline monitoring and change analysis. Geospatial shoreline data were created from a semi-automated methodology using WorldView (WV) satellite data between 2013 and 2020. The data were compared to contemporaneous field-surveyed Real-time Kinematic (RTK) Global Positioning System (GPS) data collected by the Grand Bay National Estuarine Research Reserve (GBNERR) and digitized shorelines from U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) orthophotos. Field data for shoreline monitoring sites was also collected to aid interpretation of results. This data release contains digital vector shorelines, shoreline change calculations for all three remote sensing data sets, and field surveyed data. The data will aid managers and decision-makers in the adoption of high-resolution satellite imagery into shoreline monitoring activities, which will increase the spatial scale of shoreline change monitoring, provide rapid response to evaluate impacts of coastal erosion, and reduce cost of labor-intensive practices. For further information regarding data collection and/or processing methods, refer to the associated journal article (Smith and others, 2021).

To understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites in the Grand Bay National Estuarine Research Reserve, Mississippi (GNDNERR). Each site consisted of four plots located along a transect perpendicular to the marsh-estuary shoreline at 5-meter (m) increments (5, 10, 15, and 20 m from the shoreline). Each plot contained four net sedimentation tiles (NST) that were secured flush to the marsh surface using polyvinyl chloride (PVC) pipe. NST are an inexpensive and simple tool to assess short- and long-term deposition that can be deployed in highly dynamic environments without the compaction associated with traditional coring methods. The NST were deployed for three months, measuring quarterly sediment deposition for one year from October 2016 to October 2017. In addition, three NST were deployed at the 10-m plot on October 5th prior to the landfall of Hurricane Nate (October 8, 2017) and retrieved after 12 days, providing measurements of storm deposition. Sediment deposited on the NST were processed to determine physical characteristics, such as deposition thickness, volume, wet weight/dry weight, and organic content (loss-on-ignition [LOI]). When available, additional data collected at each site including water level, elevation, and turbidity data are provided in this data release. Data were collected during Field Activities Numbers (FAN) 2017-303-FA, 2017-315-FA, 2017-333-FA, 2017-346-FA, and 2017-363-FA (also known as subFANs 17CCT01, 17CCT02, 17CCT03, 17CCT04, and 17CCT05, respectively). Additional survey and data details are available from the U.S. Geological Survey Coastal and Marine Geoscience Data System (CMGDS) at, https://cmgds.marine.usgs.gov/. Please read the full metadata for details on data collection, data set variables, and data quality.

To understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites in the Grand Bay National Estuarine Research Reserve, Mississippi (GNDNERR). Each site consisted of four plots located along a transect perpendicular to the marsh-estuary shoreline at 5-meter (m) increments (5, 10, 15, and 20 m from the shoreline). Each plot contained four net sedimentation tiles (NST) that were secured flush to the marsh surface using polyvinyl chloride (PVC) pipe. NST are an inexpensive and simple tool to assess short- and long-term deposition that can be deployed in highly dynamic environments without the compaction associated with traditional coring methods. The NST were deployed for three months, measuring quarterly sediment deposition for one year from October 2016 to October 2017. In addition, three NST were deployed at the 10-m plot on October 5th prior to the landfall of Hurricane Nate (October 8, 2017) and retrieved after 12 days, providing measurements of storm deposition. Sediment deposited on the NST were processed to determine physical characteristics, such as deposition thickness, volume, wet weight/dry weight, and organic content (loss-on-ignition [LOI]). When available, additional data collected at each site including water level, elevation, and turbidity data are provided in this data release. Data were collected during Field Activities Numbers (FAN) 2017-303-FA, 2017-315-FA, 2017-333-FA, 2017-346-FA, and 2017-363-FA (also known as subFANs 17CCT01, 17CCT02, 17CCT03, 17CCT04, and 17CCT05, respectively). Additional survey and data details are available from the U.S. Geological Survey Coastal and Marine Geoscience Data System (CMGDS) at, https://cmgds.marine.usgs.gov/. Please read the full metadata for details on data collection, data set variables, and data quality.

This dataset represents a compilation of waves, fetch, and associated shoreline change rates from the Point Aux Chenes and Grand Bay estuaries (Mississippi and Alabama) for historical, modern, and long-term time periods.

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).

To understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites in the Grand Bay National Estuarine Research Reserve, Mississippi (GNDNERR). Each site consisted of four plots located along a transect perpendicular to the marsh-estuary shoreline at 5-meter (m) increments (5, 10, 15, and 20 m from the shoreline). Each plot contained four net sedimentation tiles (NST) that were secured flush to the marsh surface using polyvinyl chloride (PVC) pipe. NST are an inexpensive and simple tool to assess short- and long-term deposition that can be deployed in highly dynamic environments without the compaction associated with traditional coring methods. The NST were deployed for three months, measuring quarterly sediment deposition for one year from October 2016 to October 2017. In addition, three NST were deployed at the 10-m plot on October 5th prior to the landfall of Hurricane Nate (October 8, 2017) and retrieved after 12 days, providing measurements of storm deposition. Sediment deposited on the NST were processed to determine physical characteristics, such as deposition thickness, volume, wet weight/dry weight, and organic content (loss-on-ignition [LOI]). When available, additional data collected at each site including water level, elevation, and turbidity data are provided in this data release. Data were collected during Field Activities Numbers (FAN) 2017-303-FA, 2017-315-FA, 2017-333-FA, 2017-346-FA, and 2017-363-FA (also known as subFANs 17CCT01, 17CCT02, 17CCT03, 17CCT04, and 17CCT05, respectively). Additional survey and data details are available from the U.S. Geological Survey Coastal and Marine Geoscience Data System (CMGDS) at, https://cmgds.marine.usgs.gov/. Please read the full metadata for details on data collection, dataset variables, and data quality.