Chirp seismic reflection data from the Edgetech 512i collected in Little Egg Inlet and offshore the southern end of Long Beach Island, NJ, during USGS field activity 2018-001-FA (shotpoints point shapefile, survey trackline shapefile, PNG profile images, and SEG-Y trace data).
Dates
Publication Date
2021-04-22
Start Date
2018-05-31
End Date
2018-06-10
Citation
Ackerman, S.D., Barnhardt, W.A., Worley, C.R., Nichols, A.R., Baldwin, W.E., and Evert, S., 2021, High-resolution geophysical and geological data collected in Little Egg Inlet and offshore the southern end of Long Beach Island, NJ, during USGS Field Activities 2018-001-FA and 2018-049-FA: U.S. Geological Survey data release, https://doi.org/10.5066/P9C3J33K.
Summary
The natural resiliency of the New Jersey barrier island system, and the efficacy of management efforts to reduce vulnerability, depends on the ability of the system to recover and maintain equilibrium in response to storms and persistent coastal change. This resiliency is largely dependent on the availability of sand in the beach system. In an effort to better understand the system's sand budget and processes in which this system evolves, high-resolution geophysical mapping of the sea floor in Little Egg Inlet and along the southern end of Long Beach Island near Beach Haven, New Jersey was conducted from May 31 to June 10, 2018, followed by a sea floor sampling survey conducted from October 22 to 23, 2018, as part of a collaborative [...]
Summary
The natural resiliency of the New Jersey barrier island system, and the efficacy of management efforts to reduce vulnerability, depends on the ability of the system to recover and maintain equilibrium in response to storms and persistent coastal change. This resiliency is largely dependent on the availability of sand in the beach system. In an effort to better understand the system's sand budget and processes in which this system evolves, high-resolution geophysical mapping of the sea floor in Little Egg Inlet and along the southern end of Long Beach Island near Beach Haven, New Jersey was conducted from May 31 to June 10, 2018, followed by a sea floor sampling survey conducted from October 22 to 23, 2018, as part of a collaborative effort between the U.S. Geological Survey and Stockton University. Multibeam echo sounder bathymetry and backscatter data were collected along 741 kilometers of tracklines (approximately 200 square kilometers) of the coastal sea floor to regionally define its depth and morphology, as well as the type and distribution of sea-floor sediments. Six hundred ninety-two kilometers of seismic-reflection profile data were also collected to define the thickness and structure of sediment deposits in the inlet and offshore. These new data will help inform future management decisions that affect the natural and recreational resources of the area around and offshore of Little Egg Inlet. These mapping surveys provide high-quality data needed to build scientific knowledge of the evolution and behavior of the New Jersey barrier island system.
This dataset contains shotpoint and trackline navigation, profile images, and raw SEG-Y trace data for 692 km of EdgeTech 512i chirp seismic-reflection data collected by the U.S. Geological Survey during USGS field activity 2018-001-FA off southern Long Beach Island, New Jersey. Images of each seismic profile were generated in order to provide portable and easily viewable alternatives to the SEG-Y versions of the data. Each profile image can be hotlinked to its corresponding trackline navigation contained within the Esri polyline shapefile '2018-001-FA_SB512i_Tracklines.shp'. Shotpoint index and tick marks along the top of the PNG images correlate to the positions of 500 shot intervals within the Esri point shapefile '2018-001-FA_SB512i_Shot500.shp'. This information allows for spatial correlation of chirp seismic-reflection profiles images with other geophysical and sample data for investigating sea-floor morphology and stratigraphy in the area.
Preview Image
Image of seismic profile and shot point location from survey 2018-001-FA.