Puerto Rico is a Caribbean Island with a population of about 3.2 million people who are exposed to natural hazards including earthquakes and submarine landslides that can generate tsunamis. Previous work has shown seismicity offshore Puerto Rico especially between the coastline and the Puerto Rico Trench north of the island. The Puerto Rico Seismic Network maintains the local seismic network to record earthquakes, but these earthquake locations rely on seismic instruments that are all located on land. As ...

On June 12, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20180612.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On May 08, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20180508.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On September 01, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220901.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson ...

On August 03, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220803.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ...

On August 02, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220802.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ...

On July 13, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220713.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ...

On July 12, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220712.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ...

On June 24, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220624.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ...

On June 23, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220623.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ...

On June 22, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220622.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ...

On May 20, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220520.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ...

On May 19, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220519.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and ...

On September 09, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210909.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, ...

On September 08, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210908.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, ...

On August 11, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210811.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On August 10, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210810.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On July 21, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210721.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On July 20, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210720.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On June 16, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210616.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On June 15, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210615.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On May 26, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210526.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On May 25, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210525.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On June 26, 2020, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20200626.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On June 25, 2020, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20200625.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On September 11, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190911.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, ...

On September 10, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190910.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, ...

On August 21, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190821.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On August 20, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190820.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On July 17, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190717.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On July 16, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190716.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On June 19, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190619.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On June 18, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190618.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On May 31, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190531.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On May 30, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190530.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On August 08, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20180808.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On July 18, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20180718.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On June 13, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20180613.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On May 09, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20180509.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On July 20, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220720.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On July 19, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220719.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On June 15, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220615.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On June 14, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220614.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On May 25, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220525.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On May 24, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220524.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On August 04, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210804.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On August 03, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210803.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On July 14, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210714.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On July 13, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210713.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On June 23, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210623.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On June 22, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210622.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On May 19, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210519.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On May 18, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210518.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On June 17, 2020, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20200617.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On June 16, 2020, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20200616.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On August 28, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190828.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On August 27, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190827.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; ...

On July 24, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190724.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On July 23, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190723.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On June 26, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190626.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On June 25, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190625.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On May 21, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190521.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On May 20, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190520.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On July 22, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220722.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On July 21, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220721.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On June 17, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220617.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On June 16, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220616.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On May 27, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220527.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On May 26, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220526.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On August 06, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210806.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On August 05, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210805.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On July 16, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210716.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On July 15, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210715.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On June 25, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210625.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On June 24, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210624.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On May 21, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210521.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On May 20, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210520.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On July 26, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190726.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On July 25, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190725.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On June 28, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190628.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On June 27, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190627.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On May 23, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190523.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On May 22, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190522.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and ...

On August 07, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20180807.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

On July 17, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20180717.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown ...

From November 8-13, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Boca Chica Key, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a line dataset of field activity number (FAN) 2022-334-FA chirp tracklines.

From November 8-13, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Boca Chica Key, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-334-FA chirp subbottom profile start of trackline ...

From November 8-13, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Boca Chica Key, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-334-FA chirp subbottom profile 1,000-shot-interval ...

As part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey at the nearshore ledge offshore of Boca Chica Key, Florida (FL) November 8-13, 2022. The objective of the project was to collect bathymetric maps and conduct a geologic assessment of the nearshore ledge off Boca Chica Key in support ...

From September 27 through October 5, 2019, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of the Rockaway Peninsula, New York. This shapefile represents a line dataset of field activity number (FAN) 2019-333-FA chirp tracklines.

From September 27 through October 5, 2019, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of the Rockaway Peninsula, New York. This shapefile represents a point dataset of field activity number (FAN) 2019-333-FA chirp subbottom profile start of trackline locations.

From September 27 through October 5, 2019, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of the Rockaway Peninsula, New York. This shapefile represents a point dataset of field activity number (FAN) 2019-333-FA chirp subbottom profile 1,000-shot-interval locations.

From September 27 through October 5, 2019, researchers from the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate shoreface morphology and geology near the Rockaway Peninsula, New York. The Coastal Sediment Availability and Flux project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. This publication serves as an ...

From August 9 to 14, 2019, researchers from the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate shoreface morphology and geology near Cedar Island, Virginia. The Coastal Sediment Availability and Flux project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. This publication serves as an archive of high-resolution ...

In June/December 2021 and July 2022, the U.S. Geological Survey (USGS) and U.S. Army Corps of Engineers, Engineer Research and Development Center (USACE-ERDC) conducted repeat, nearshore geologic assessments, including bathymetric mapping, near Duck, North Carolina (NC). This work was performed in support of efforts to map the shoreface, characterize stratigraphy, and investigate changes in seafloor elevations near the USACE Field Research Facility and to measure the co-evolution of the morphology and ...

In June/December 2021 and July 2022, the U.S. Geological Survey (USGS) and U.S. Army Corps of Engineers, Engineer Research and Development Center (USACE-ERDC) conducted repeat, nearshore geologic assessments, including bathymetric mapping, near Duck, North Carolina (NC). This work was performed in support of efforts to map the shoreface, characterize stratigraphy, and investigate changes in seafloor elevations near the USACE Field Research Facility and to measure the co-evolution of the morphology and ...

This data set contains the sea floor topographic contours, sun-illuminated topographic imagery, and backscatter intensity generated from a multibeam sonar survey of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts, an area of approximately 1100 square nautical miles. The Stellwagen Bank NMS Mapping Project is designed to provide detailed maps of the Stellwagen Bank region's environments and habitats and the first complete multibeam topographic and sea floor characterization ...

In October 2012, Hurricane Sandy made landfall in the Northeastern U.S., affecting ecosystems and communities of 12 states. In response, the National Fish and Wildlife Federation (NFWF) and the U.S. Department of Interior (DOI) implemented the Hurricane Sandy Coastal Resiliency Program, which funded various projects designed to reduce future impacts of coastal hazards. These projects included marsh, beach, and dune restoration, aquatic connectivity, and living shoreline installation, among others. To ...

From April 29 through May 2, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Seven Mile Island, New Jersey. Geophysical data were collected as part of the Coastal Sediment Availability and Flux project. This shapefile represents a line dataset of field activity number (FAN) 2022-309-FA chirp tracklines.

From April 29 through May 2, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Seven Mile Island, New Jersey. Geophysical data were collected as part of the Coastal Sediment Availability and Flux project. This shapefile represents a point dataset of field activity number (FAN) 2022-309-FA chirp subbottom profile start of trackline locations.

From April 29 through May 2, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Seven Mile Island, New Jersey. Geophysical data were collected as part of the Coastal Sediment Availability and Flux project. This shapefile represents a point dataset of field activity number (FAN) 2022-309-FA chirp subbottom profile 1,000-shot-interval locations.

From April 29 through May 2, 2022, researchers from the U.S. Geological Survey (USGS) conducted a nearshore geophysical survey to map the shoreface and inner shelf, as well as characterizing stratigraphy near Seven Mile Island, New Jersey (NJ). The Coastal Sediment Availability and Flux project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. ...

Seabeach amaranth (Amaranthus pumilus) is a federally threatened plant species that was once prevalent on beaches of the U.S. mid-Atlantic coast. For much of the 20th century, seabeach amaranth was absent and thought to be extinct along this coast presumably due to development and recreational pressure. Few plants were observed over much of the 20th century and the species was federally listed as endangered in 1993. To re-establish a population, the Natural Resources staff at Assateague Island National ...

From June 2 through 9, 2021, the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and determine Holocene stratigraphy near Santa Rosa Island, Florida (FL). Santa_Rosa_Island_2021_SBES_xyz.zip is a xyz point file dataset of field activity number (FAN) 2021-322-FA single-beam bathymetry (SBB) data collected concurrently with subbottom data to provide a current seafloor ...

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 ...

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 ...

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 ...

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC) in St. Petersburg, Florida, conducted a bathymetric survey of Point Aux Chenes Bay and a small portion of Grand Bay, Mississippi/Alabama, from March 3-6, 2021. Efforts were supported by the Estuarine and MaRsh Geology project (EMRG), and the data described will provide baseline bathymetric information for future research investigating wetland/marsh evolution, sediment transport, and recent and long-term ...

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 ...

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 ...

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 ...

Scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center collected 303 surface sediment samples from Dauphin Island, Alabama, and the surrounding water bodies in August 2015. These sediments were processed to determine physical characteristics such as organic content, bulk density, and grain-size. The environments where the sediments were collected include high and low salt marshes, over-wash deposits, dunes, beaches, sheltered bays, and open water. Sampling by the USGS ...

Scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center collected 303 surface sediment samples from Dauphin Island, Alabama, and the surrounding water bodies in August 2015. These sediments were processed to determine physical characteristics such as organic content, bulk density, and grain-size. The environments where the sediments were collected include high and low salt marshes, over-wash deposits, dunes, beaches, sheltered bays, and open water. Sampling by the USGS ...

Scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center collected 303 surface sediment samples from Dauphin Island, Alabama, and the surrounding water bodies in August 2015. These sediments were processed to determine physical characteristics such as organic content, bulk density, and grain-size. The environments where the sediments were collected include high and low salt marshes, over-wash deposits, dunes, beaches, sheltered bays, and open water. Sampling by the USGS ...

Scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center collected 303 surface sediment samples from Dauphin Island, Alabama, and the surrounding water bodies in August 2015. These sediments were processed to determine physical characteristics such as organic content, bulk density, and grain-size. The environments where the sediments were collected include high and low salt marshes, over-wash deposits, dunes, beaches, sheltered bays, and open water. Sampling by the USGS ...

From June 2 through 9, 2021, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and determine Holocene stratigraphy near Santa Rosa Island, Florida (FL). This shapefile represents a line dataset of field activity number (FAN) 2021-322-FA chirp tracklines collected inshore and offshore of Pensacola Beach, FL.

From June 2 through 9, 2021, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and determine Holocene stratigraphy near Santa Rosa Island, Florida (FL). This shapefile represents a point dataset of field activity number (FAN) 2021-322-FA chirp subbottom profile start of trackline locations collected inshore and offshore of Pensacola Beach, FL.

From June 2 through 9, 2021, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and determine Holocene stratigraphy near Santa Rosa Island, Florida (FL). This shapefile represents a point dataset of field activity number (FAN) 2021-322-FA chirp subbottom profile 1,000-shot-interval locations collected inshore and offshore of Pensacola Beach, FL.

From June 2 through 9, 2021, researchers from the U.S. Geological Survey (USGS) conducted an inshore and offshore geophysical survey to map the shoreface and determine Holocene stratigraphy near Pensacola Beach, Florida (FL). The Coastal Resource Evaluation for Management Applications (CREMA) project objective includes the investigation of nearshore geologic controls on surface morphology. This publication serves as an archive of high-resolution chirp subbottom trace data, survey trackline map, navigation ...

From August 16 to 21, 2018, the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate the geologic controls on barrier island evolution and medium-term and interannual sediment transport along the sand berm constructed in 2011 (offshore, at the northern end of the Chandeleur Islands, Louisiana) as mitigation of the Deepwater Horizon oil spill. This investigation is part of a broader USGS project, which seeks to better understand barrier island evolution over medium time scales (months ...

June 2–10 and July 2, 2017, the U.S. Geological Survey (USGS) conducted geophysical surveys offshore of the Louisiana Chenier Plain to document the changing morphology of the coastal environment. Data were collected under the Barrier Island Coastal Monitoring (BICM) program, an ongoing collaboration between the State of Louisiana Coastal Protection and Restoration Authority (CPRA), the University of New Orleans (UNO) Pontchartrain Institute for Environmental Sciences (PIES), and the USGS. Project ...

From August 7 to 16, 2017, the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate the geologic controls on barrier island evolution and medium-term and interannual sediment transport along the sand berm constructed in 2011 (offshore, at the northern end of the Chandeleur Islands, Louisiana) as mitigation of the Deepwater Horizon oil spill. This investigation is part of a broader USGS project, which seeks to better understand barrier island evolution over medium time scales (months ...

From June 10 to 19, 2016, the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate the geologic controls on barrier island evolution and medium-term and interannual sediment transport along the sand berm constructed in 2011 (offshore, at the northern end of the Chandeleur Islands, Louisiana) as mitigation of the Deepwater Horizon oil spill. This investigation is part of a broader USGS project, which seeks to better understand barrier island evolution over medium time scales (months to ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Little Dauphin Island, Alabama (AL) under different storm scenarios and restoration alternatives as described in Passeri and others (2025). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent elevations (topography and bathymetry). The XBeach model setup requires the input of topographic and bathymetric elevations at each grid cell. ...

Using the Delft3D 4 Suite (Lesser and others, 2004), sediment transport and morphologic change was simulated at Little Dauphin Island, Alabama (AL) for 5-year simulations of restoration alternatives as described in Passeri and others (2025). The two-dimensional Delft3D model can be applied to coastal systems to solve for time-dependent bed level elevations. The Delft3D model setup requires the input of bathymetric elevations at each grid cell. Model inputs and outputs in the form of elevation at each grid ...

Using the Delft3D 4 Suite (Lesser and others, 2004), sediment transport and morphologic change was simulated at Little Dauphin Island, Alabama (AL) for 5-year simulations of restoration alternatives as described in Passeri and others (2025). The two-dimensional Delft3D model can be applied to coastal systems to solve for time-dependent bed level elevations. The Delft3D model setup requires the input of bathymetric elevations at each grid cell. Model inputs and outputs in the form of elevation at each grid ...

Using the Delft3D 4 Suite (Lesser and others, 2004), sediment transport and morphologic change was simulated at Little Dauphin Island, Alabama (AL) for 5-year simulations of restoration alternatives as described in Passeri and others (2025). The two-dimensional Delft3D model can be applied to coastal systems to solve for time-dependent bed level elevations. The Delft3D model setup requires the input of bathymetric elevations at each grid cell. Model inputs and outputs in the form of elevation at each grid ...

Using the Delft3D 4 Suite (Lesser and others, 2004), sediment transport and morphologic change was simulated at Little Dauphin Island, Alabama (AL) for 5-year simulations of restoration alternatives as described in Passeri and others (2025). The two-dimensional Delft3D model can be applied to coastal systems to solve for time-dependent bed level elevations. The Delft3D model setup requires the input of bathymetric elevations at each grid cell. Model inputs and outputs in the form of elevation at each grid ...

Using the Delft3D 4 Suite (Lesser and others, 2004), sediment transport and morphologic change was simulated at Little Dauphin Island, Alabama (AL) for 5-year simulations of restoration alternatives as described in Passeri and others (2025). The two-dimensional Delft3D model can be applied to coastal systems to solve for time-dependent bed level elevations. The Delft3D model setup requires the input of bathymetric elevations at each grid cell. Model inputs and outputs in the form of elevation at each grid ...

This dataset represents a compilation of vector upland boundary lines, upland boundary points, and transects with rates for the Point Aux Chenes and Grand Bay estuaries (Mississippi and Alabama) for 1848, 1957/1958 (henceforth referred to as 1957), and 2019/2022 (henceforth referred to as 2022). Upland data were obtained from multiple data sources, including the National Oceanic and Atmospheric Administration (NOAA) topographic sheets (t-sheets) and WorldView 2 satellite imagery. Regardless of the source, ...

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 ...

As a part of the Barrier Island Comprehensive Monitoring Program (BICM), scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore single-beam bathymetry survey along the Chenier Plain, Louisiana from Marsh Island to Sabine Pass. The goal of the BICM program is to provide long-term data on Louisiana's coastline and use this data to plan, design, evaluate, and maintain current and future barrier island restoration projects. The data described in ...

As a part of the Barrier Island Comprehensive Monitoring Program (BICM), scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore single-beam bathymetry survey along the Chenier Plain, Louisiana from Marsh Island to Sabine Pass. The goal of the BICM program is to provide long-term data on Louisiana’s coastline and use this data to plan, design, evaluate, and maintain current and future barrier island restoration projects. The data described ...

As a part of the Barrier Island Comprehensive Monitoring Program (BICM), scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore single-beam bathymetry survey along the Chenier Plain, Louisiana from Marsh Island to Sabine Pass. The goal of the BICM program is to provide long-term data on Louisiana's coastline and use this data to plan, design, evaluate, and maintain current and future barrier island restoration projects. The data described in ...

For more than 25 years, the U.S. Geological Survey Gas Hydrates Project has compiled and maintained an internal database of locations where the existence of gas hydrate has been confirmed or inferred in research studies. The existence of gas hydrate was considered confirmed when gas hydrate was recovered by researchers or videotaped from a vehicle (such as a submersible or remotely operated vehicle) near the sea floor. The existence of gas hydrate was considered inferred when seismic data, borehole logs, or ...

As part of the 2022 Disaster Supplemental project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey to map the shoreface and inner shelf, as well as characterize stratigraphy near the Chandeleur Islands, Louisiana (LA) in June and August 2023. The purpose of this study was to conduct a morphologic and geologic assessment of the impacts of the 2020 and 2021 hurricane seasons within part of the Breton National ...

As part of the 2022 Disaster Supplemental project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey to map the shoreface and inner shelf, as well as characterize stratigraphy near the Chandeleur Islands, Louisiana (LA) in June and August 2023. The purpose of this study was to conduct a morphologic and geologic assessment of the impacts of the 2020 and 2021 hurricane seasons within part of the Breton National ...

From June 20-30, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport near Panama City, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a line dataset of field activity number (FAN) 2022-312-FA chirp tracklines.

From June 20-30, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport near Panama City, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-312-FA chirp subbottom profile start of trackline locations.

From June 20-30, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport near Panama City, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-312-FA chirp subbottom profile 1,000-shot-interval locations.

As part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey to map back-barrier and lagoonal areas, as well as characterizing stratigraphy near Panama City, Florida (FL) in June 2022. The purpose of this study was to conduct a geologic assessment (including bathymetric mapping) of the environs ...

On August 5, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Breton Island, Louisiana (LA). Geophysical data were collected as part of the Breton Island Post Construction Monitoring project. This shapefile represents a line dataset of field activity number (FAN) 2022-328-FA chirp tracklines.

On August 5, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Breton Island, Louisiana (LA). Geophysical data were collected as part of the Breton Island Post Construction Monitoring project. This shapefile represents a point dataset of field activity number (FAN) 2022-328-FA chirp subbottom profile start of trackline locations.

On August 5, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Breton Island, Louisiana (LA). Geophysical data were collected as part of the Breton Island Post Construction Monitoring project. This shapefile represents a point dataset of field activity number (FAN) 2022-328-FA chirp subbottom profile 1,000-shot-interval locations.

On August 5, 2022, researchers from the U.S. Geological Survey (USGS) conducted an offshore geophysical survey to map the shoreface and determine Holocene stratigraphy near Breton Island, Louisiana (LA). The Breton Island Post Construction Monitoring project objective includes the investigation of nearshore geologic controls on surface morphology in addition to mapping the seafloor to evaluate coastal change. This publication (Forde and others, 2023) serves as an archive of high-resolution chirp subbottom ...

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, Mississippi (GNDNERR). 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 ...

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 ...

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 ...

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 ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

From September 16 through 23, 2015, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Dauphin Island, Alabama. Geophysical data were collected as part of the Alabama Barrier Island Restoration Feasibility Study. This shapefile represents a line dataset of field activity number (FAN) 2015-330-FA chirp tracklines.

From September 16 through 23, 2015, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Dauphin Island, Alabama. Geophysical data were collected as part of the Alabama Barrier Island Restoration Feasibility Study. This shapefile represents a point dataset of field activity number (FAN) 2015-330-FA chirp subbottom profile start of trackline locations.

From September 16 through 23, 2015, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Dauphin Island, Alabama. Geophysical data were collected as part of the Alabama Barrier Island Restoration Feasibility Study. This shapefile represents a point dataset of field activity number (FAN) 2015-330-FA chirp subbottom profile 1,000-shot-interval locations.

From September 16 through 23, 2015, researchers from the U.S. Geological Survey (USGS) conducted an offshore geophysical survey to map the shoreface and determine Holocene stratigraphy near Dauphin Island, Alabama (AL). The Alabama Barrier Island Restoration Feasibility Study project objective includes the investigation of nearshore geologic controls on surface morphology. This publication serves as an archive of high-resolution chirp subbottom trace data, survey trackline map, navigation files, geographic ...