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Data

Explore data releases published by the USGS St. Petersburg Coastal and Marine Science Center below. 

Filter Total Items: 347

Lidar-derived Beach Morphology (Dune Crest, Dune Toe, and Shoreline) for U.S. Sandy Coastlines

The U.S. Geological Survey (USGS) National Assessment of Coastal Change Hazards (NACCH) project aims to identify areas of the nation's coastline that are most vulnerable to extreme storms and long-term shoreline change. These assessments require coastal elevation data across diverse geographic regions and covering a time span of many years. The datasets published here, organized by individual fiel

Archive of Chirp Subbottom Profile Data Collected in 2019 From Cedar Island, Virginia

As part of the Coastal Sediment Availability and Flux Project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore geophysical survey to map the shoreface of Cedar Island, Virginia (VA) in August of 2019. The objective of the project is to improve the understanding of barrier island geomorphic evolution and the sediment fluxes th

Idealized Antecedent Topography Sensitivity Study: Initial Baseline and Modified Profiles Modeled with XBeach

The one-dimensional model inputs of idealized topography and bathymetry values for simulation of synthetic storm evolution with XBeach, as described in Mickey and others (2020) are provided here. The idealized topography and bathymetry were derived from LiDAR data from Dauphin Island, AL, USA over the timespan of 2005 to 2015. For further information regarding model input generation of topography

Time Series of Structure-from-Motion Products-Orthomosaics, Digital Elevation Models, and Point Clouds: Madeira Beach, Florida, July 2017 to June 2018

Aerial imagery acquired with a small unmanned aircraft system (sUAS), in conjunction with surveyed ground control points (GCP) visible in the imagery, can be processed with structure-from-motion (SfM) photogrammetry techniques to produce high-resolution orthomosaics, three-dimensional (3D) point clouds and digital elevation models (DEMs). This dataset, prepared by the U.S. Geological Survey (USGS)

Coastal Multibeam Bathymetry Data Collected in 2019 off of Santa Rosa Island, Florida

The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC), collected multibeam bathymetry data off the coast of Santa Rosa Island, Florida in June of 2019. The data was collected as part of the USGS Resource Evaluation for Management Applications (CREMA) project. This USGS Data Release includes the resulting processed elevation point data (XYZ) as derived from a 1-m

Coastal Bathymetry and Backscatter Data Collected in August 2019 from Cedar Island, Virginia

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida (USGS SPCSMC), conducted a geophysical survey of Cedar Island, Virginia, August 2019. During this study, multibeam bathymetry and backscatter data were collected aboard the R/V Sallenger, while single-beam bathymetry were collected aboard a towed seismic sled. Efforts were support

Time Series of Aerial Imagery from Small Unmanned Aircraft Systems and Associated Ground Control Points: Madeira Beach, Florida, July 2017 to June 2018

Aerial imagery acquired with a small unmanned aircraft system (sUAS), in conjunction with surveyed ground control points (GCP) visible in the imagery, can be processed with structure-from-motion (SfM) photogrammetry techniques to produce high-resolution orthomosaics, three-dimensional (3D) point clouds and digital elevation models (DEMs). This dataset, prepared by the U.S. Geological Survey (USGS)

Multibeam Bathymetry Data Collected in 2018 offshore of Cedar Key, Florida

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a multibeam bathymetry survey of a selected area offshore Cedar Key, Florida (FL) for the Florida Big Bend Pilot Study funded by USGS and the National Oceanic Atmospheric Administration (NOAA). The study involves federal, state, and local agencies who are taking a comprehensive approach to investi

Southeast Florida and Florida Keys: Antibiotic Resistance in Association with Ocean Outfalls and the Antibiotic Treatment of Diseased Corals

The purpose of these datasets was to define which samples contained antibiotic resistance genes (screened antibiotic resistance gene targets) and the number of detectable targets per sample (sediment, coral mucus and water). These data were determined from samples collected in Southeast Florida and the Florida Keys, in support of the Southeast Florida Coral Reef Initiative.

Multibeam Bathymetry Data Collected in 2019 from Grand Bay and Point Aux Chenes Bay Alabama/Mississippi

The U.S Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted an ellipsoidally referenced survey using a multibeam echosounder within Grand Bay and Point Aux Chenes Bay, Alabama/Mississippi May 7-10, 2019. The survey is a part of the Estuarine and Marsh Geology Research Project (EMRG) which focuses on evaluating the linkage between marsh shoreline metrics and

Sediment Radiochemical Data from Georgia, Massachusetts and Virginia Coastal Marshes

This data release is an archive of sedimentary laboratory analytical data produced by scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC) for sediment cores and surface samples collected from coastal marshes in Georgia (GA), Virginia (VA), and Massachusetts (MA). Collaborators from USGS Patuxent Wildlife Research Center (PWRC) and the Virginia

Historical Bathymetry in the Mississippi-Alabama Coastal Region: Bathymetric Soundings, Gridded Digital Elevation Model, and Hydrographic Sheets

Hydrographic sheets (H-sheets) produced by the National Ocean Service (NOS) during the 1800s provide historic sounding (water depth) measurements of coastal areas. The data can be vectorized into a geographic information system (GIS), adjusted to a modern vertical datum, and converted into a digital elevation model to provide an interpretation of the historic seafloor elevation. These data were pr