In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining this geologic framework and identifying the transport pathways and sinks of sediment, geoscientists are developing conceptual models of the present-day physical processes shaping the South Carolina coast. The primary objectives of this research effort are: 1) to provide a regional synthesis of the shallow geologic framework underlying the coastal upland, shoreface and inner continental shelf, and define its role in coastal evolution and modern beach behavior; 2) to identify and model the physical processes affecting coastal ocean circulation and sediment transport, and to define their role in shaping the modern shoreline; and 3) to identify sediment sources and transport pathways; leading to construction of a regional sediment budget.

In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining this geologic framework and identifying the transport pathways and sinks of sediment, geoscientists are developing conceptual models of the present-day physical processes shaping the South Carolina coast. The primary objectives of this research effort are: 1) to provide a regional synthesis of the shallow geologic framework underlying the coastal upland, shoreface and inner continental shelf, and define its role in coastal evolution and modern beach behavior; 2) to identify and model the physical processes affecting coastal ocean circulation and sediment transport, and to define their role in shaping the modern shoreline; and 3) to identify sediment sources and transport pathways; leading to construction of a regional sediment budget.

In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining this geologic framework and identifying the transport pathways and sinks of sediment, geoscientists are developing conceptual models of the present-day physical processes shaping the South Carolina coast. The primary objectives of this research effort are: 1) to provide a regional synthesis of the shallow geologic framework underlying the coastal upland, shoreface and inner continental shelf, and define its role in coastal evolution and modern beach behavior; 2) to identify and model the physical processes affecting coastal ocean circulation and sediment transport, and to define their role in shaping the modern shoreline; and 3) to identify sediment sources and transport pathways; leading to construction of a regional sediment budget.

This dataset contains surface sediment grain size distributions derived from manual point counts of in situ seafloor images obtained with an underwater camera system in the lower Columbia River, Washington and Oregon, in 2021. The distributions derived from manual point counts were compared with results from an automated image processing technique to calibrate and validate the automated method used to quantify surface sediment grain size distributions in objective images. The surface sediment grain size distribution data derived from manual point counts are provided in comma-separated text format (point_count_distributions.csv) and should be compared with grain size distributions for the same set of images (dgs_calibration_validation.csv) derived from automated image processing that can be found in the "Surface sediment grain size distributions derived from automated image processing of in situ seafloor images from the lower Columbia River, Washington and Oregon, 2021" portion of the overall data release.

This dataset contains surface sediment grain size distributions derived from manual point counts of in situ seafloor images obtained with an underwater camera system in the lower Columbia River, Washington and Oregon, in 2021. The distributions derived from manual point counts were compared with results from an automated image processing technique to calibrate and validate the automated method used to quantify surface sediment grain size distributions in objective images. The surface sediment grain size distribution data derived from manual point counts are provided in comma-separated text format (point_count_distributions.csv) and should be compared with grain size distributions for the same set of images (dgs_calibration_validation.csv) derived from automated image processing that can be found in the "Surface sediment grain size distributions derived from automated image processing of in situ seafloor images from the lower Columbia River, Washington and Oregon, 2021" portion of the overall data release.

This dataset contains surface sediment grain size distributions derived from manual point counts of in situ seafloor images obtained with an underwater camera system in the lower Columbia River, Washington and Oregon, in 2021. The distributions derived from manual point counts were compared with results from an automated image processing technique to calibrate and validate the automated method used to quantify surface sediment grain size distributions in objective images. The surface sediment grain size distribution data derived from manual point counts are provided in comma-separated text format (point_count_distributions.csv) and should be compared with grain size distributions for the same set of images (dgs_calibration_validation.csv) derived from automated image processing that can be found in the "Surface sediment grain size distributions derived from automated image processing of in situ seafloor images from the lower Columbia River, Washington and Oregon, 2021" portion of the overall data release.

As part of the Barrier Island Evolution Research (BIER) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected sediment samples from the northern Chandeleur Islands in July 2013. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to understand better the depositional and erosional processes that drive the morphologic evolution of barrier islands over annual to interannual timescales (1 to 5 years). Between June 2010 and April 2011, in response to the Deepwater Horizon oil spill, the State of Louisiana constructed a sand berm extending more than 14 kilometers (km) along the northern Chandeleur Islands platform. The construction of the berm provided a unique opportunity for scientists to investigate how this new sediment source interacts with and affects the morphologic evolution of the barrier-island system. Data collected from this study can be used to describe differences in the physical characteristics and spatial distribution of sediments both along the axis of the berm and also along transects across the berm and onto the adjacent barrier island. Comparison of these data with data from prior sampling efforts can provide information about sediment interactions and movement between the berm and the natural island platform, improving insight into short-term morphologic change and processes in this barrier-island system. This data series serves as an archive of sediment data collected in July 2013 from the Chandeleur Islands sand berm and adjacent barrier-island environments. Data products, including descriptive core logs, core photographs and x-radiographs, results of sediment grain-size analyses, sample location maps, and Geographic Information System (GIS) data files with accompanying formal Federal Geographic Data Committee (FDGC) metadata, can be downloaded from https://pubs.usgs.gov/ds/894/ds894_data.html.

As part of the Barrier Island Evolution Research (BIER) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected sediment samples from the northern Chandeleur Islands in July 2013. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to understand better the depositional and erosional processes that drive the morphologic evolution of barrier islands over annual to interannual timescales (1 to 5 years). Between June 2010 and April 2011, in response to the Deepwater Horizon oil spill, the State of Louisiana constructed a sand berm extending more than 14 kilometers (km) along the northern Chandeleur Islands platform. The construction of the berm provided a unique opportunity for scientists to investigate how this new sediment source interacts with and affects the morphologic evolution of the barrier-island system. Data collected from this study can be used to describe differences in the physical characteristics and spatial distribution of sediments both along the axis of the berm and also along transects across the berm and onto the adjacent barrier island. Comparison of these data with data from prior sampling efforts can provide information about sediment interactions and movement between the berm and the natural island platform, improving insight into short-term morphologic change and processes in this barrier-island system. This data series serves as an archive of sediment data collected in July 2013 from the Chandeleur Islands sand berm and adjacent barrier-island environments. Data products, including descriptive core logs, core photographs and x-radiographs, results of sediment grain-size analyses, sample location maps, and Geographic Information System (GIS) data files with accompanying formal Federal Geographic Data Committee (FDGC) metadata, can be downloaded from https://pubs.usgs.gov/ds/894/ds894_data.html.

This data release serves as an archive of sediment physical properties and grain-size data for surficial samples collected offshore of Assateague Island, Maryland and Virginia, for comparison with surficial estuarine and subaerial sedimentological samples collected and assessed following Hurricane Sandy (Ellis and others, 2015 (http://doi.org/10.3133/ofr20151219); Smith and others, 2015 (http://doi.org/10.3133/ofr20151169); Bernier and others, 2016 (https://pubs.usgs.gov/ds/0999/)). The sediment samples were collected by scientists from the U.S. Geological Survey (USGS) office in Woods Hole, Massachusetts while aboard the motor vessel (M/V) Scarlett Isabella as part of a larger effort to map the inner continental shelf (Pendleton and others, 2016 (http://doi.org/10.5066/F7MW2F60)). Following field work, the sediment samples were shipped to the USGS Coastal and Marine Science Center in St. Petersburg, Florida, where they were renamed for consistency with a previously existing naming scheme and processed for bulk density, loss on ignition (LOI), and grain-size. The grain-size subsamples were processed on a Coulter LS200 particle-size analyzer for consistency regarding methods and output statistics with related data sets from Chincoteague Bay and Assateague Island. For more information regarding sample collection and site information or the related data sets, refer to USGS data release Pendleton and others, 2016 (https://doi.org/10.5066/F7MW2F60); for more information regarding processing methods refer to USGS Open-File Report 2015–1219 (http://doi.org/10.3133/ofr20151219). Downloadable data are available as Excel spreadsheets (.xlsx), comma-separated values text files (.csv), and formal Federal Geographic Data Committee (FGDC) metadata.

This data release serves as an archive of sediment physical properties and grain-size data for surficial samples collected offshore of Assateague Island, Maryland and Virginia, for comparison with surficial estuarine and subaerial sedimentological samples collected and assessed following Hurricane Sandy (Ellis and others, 2015 (http://doi.org/10.3133/ofr20151219); Smith and others, 2015 (http://doi.org/10.3133/ofr20151169); Bernier and others, 2016 (https://pubs.usgs.gov/ds/0999/)). The sediment samples were collected by scientists from the U.S. Geological Survey (USGS) office in Woods Hole, Massachusetts while aboard the motor vessel (M/V) Scarlett Isabella as part of a larger effort to map the inner continental shelf (Pendleton and others, 2016 (http://doi.org/10.5066/F7MW2F60)). Following field work, the sediment samples were shipped to the USGS Coastal and Marine Science Center in St. Petersburg, Florida, where they were renamed for consistency with a previously existing naming scheme and processed for bulk density, loss on ignition (LOI), and grain-size. The grain-size subsamples were processed on a Coulter LS200 particle-size analyzer for consistency regarding methods and output statistics with related data sets from Chincoteague Bay and Assateague Island. For more information regarding sample collection and site information or the related data sets, refer to USGS data release Pendleton and others, 2016 (https://doi.org/10.5066/F7MW2F60); for more information regarding processing methods refer to USGS Open-File Report 2015–1219 (http://doi.org/10.3133/ofr20151219). Downloadable data are available as Excel spreadsheets (.xlsx), comma-separated values text files (.csv), and formal Federal Geographic Data Committee (FGDC) metadata.