Data
The Coastal and Marine Hazards and Resources Program is an innovator in mapping, field studies, data collection, and laboratory analyses, whose expertise is sought by other governmental agencies, educational institutions, and private companies. In turn, we seek collaborative research and development opportunities with similar groups.
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Filter Total Items: 851
Time-series measurements of oceanographic and seabed response data collected in Cape Cod Bay, Barnstable, MA, March 10 to April 7, 2021 Time-series measurements of oceanographic and seabed response data collected in Cape Cod Bay, Barnstable, MA, March 10 to April 7, 2021
To assess cross-shore sediment transport prediction techniques in coastal models for a wave-dominated sandy coast, the U.S. Geological Survey Woods Hole Coastal and Marine Science Center collected data to measure wave-induced and mean current water velocities near the seabed and the response of the seabed to these forces. A four-legged bottom landing frame (quadpod) containing...
Projections of vegetated area and vegetated plain elevation in Chesapeake Bay salt marsh units Projections of vegetated area and vegetated plain elevation in Chesapeake Bay salt marsh units
Projections of vegetated area and vegetated plain elevation for salt marsh units within the Chesapeake Bay (CB) salt marsh complex are calculated using geospatial information for conceptual marsh units defined by Ackerman and others (2022) and Defne and others (2023). The projections are based on the UBMorph model, described in Ganju and others (2025), which estimates changes in areal...
National Shoreline Change—A GIS compilation of vector shorelines and associated shoreline change data from the 1800s to the 2010s for the coast of Long Island Sound, New York and Connecticut National Shoreline Change—A GIS compilation of vector shorelines and associated shoreline change data from the 1800s to the 2010s for the coast of Long Island Sound, New York and Connecticut
The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from various historical sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. Shorelines are compiled in a GIS and analyzed in the USGS Digital Shoreline Analysis System (DSAS) software to calculate rates of...
Coastal landscape response to sea-level change for the northeastern United States Coastal landscape response to sea-level change for the northeastern United States
This data release presents an update to the Coastal Response Likelihood (CRL) model (Lentz and others 2015); a spatially explicit, probabilistic model that evaluates coastal response for the Northeastern U.S. under various sea-level scenarios. The model considers the variable nature of the coast and provides outputs at spatial and temporal scales suitable for decision support. Updated...
Topographic data, aerial imagery, and GPS data collected during uncrewed aircraft system (UAS) operations at Lower Darby Creek, Darby Township, Pennsylvania, March to August 2024 Topographic data, aerial imagery, and GPS data collected during uncrewed aircraft system (UAS) operations at Lower Darby Creek, Darby Township, Pennsylvania, March to August 2024
The U.S. Geological Survey deployed small uncrewed aircraft systems (sUAS) to collect aerial remote sensing data across sites within the Lower Darby Creek Superfund Site and the adjacent John Heinz National Wildlife Refuge (JHNWR) ~5 miles outside of Philadelphia, PA in March and August of 2024. March datasets include aerial images from natural color (RGB) and thermal infra-red (TIR)...
Modeling marsh migration: User needs for decision-making collected in 2021 and 2023 Modeling marsh migration: User needs for decision-making collected in 2021 and 2023
The U.S. Geological Survey (USGS) conducted interviews of professionals who make decisions about marshes during the Salt Marsh Evolution along the South Atlantic Bight project (SAB project) and the Marsh Model Retrospective initiative. During the SAB project, an advisory committee of marsh model users were interviewed in June 2023 about what decisions they make about marshes and how they...
Topographic data, aerial imagery, and GPS data collected during uncrewed aircraft system (UAS) operations at Sesuit Marsh, Dennis, Massachusetts, August 12, 2024 Topographic data, aerial imagery, and GPS data collected during uncrewed aircraft system (UAS) operations at Sesuit Marsh, Dennis, Massachusetts, August 12, 2024
Small Uncrewed Aircraft Systems (sUAS) were used to collect aerial remote sensing data over Sesuit Marsh in Dennis, MA. Raw data from aerial surveys include aerial images from natural color (RGB) and multispectral cameras and raw lidar data. These datasets were processed to produce high resolution digital elevation models (DEM), image mosaics, and lidar point clouds (LPC) to provide...
Supplemental data for Over and Sherwood (2025), Washover and washout locations and landcover classifications after hurricanes Florence, Dorian, Harvey, Ike, and Sandy in North Carolina, Texas, and New York Supplemental data for Over and Sherwood (2025), Washover and washout locations and landcover classifications after hurricanes Florence, Dorian, Harvey, Ike, and Sandy in North Carolina, Texas, and New York
The data in this release support the journal article "Outwash events inhibit vegetation recovery and prolong coastal vulnerability". The research details the vegetation cover in washover and washout locations in North Carolina, Texas, and New York after hurricanes Florence, Dorian, Harvey, Ike, and Sandy. Aerial imagery observations indicate that washout sites create ponds and have a...
Lifespan of marsh units in E.B. Forsythe NWR and Atlantic-facing New Jersey salt marshes Lifespan of marsh units in E.B. Forsythe NWR and Atlantic-facing New Jersey salt marshes
This data release contains the estimated lifespans of salt marshes in E.B. Forsythe National Wildlife Refuge (EBFNWR) and Atlantic-facing New Jersey. The lifespans are calculated based on estimated sediment supply and sea-level rise (SLR) predictions, following the methodology of Ganju and others (2020). The salt marsh delineations are from Ackerman and others (2024) and Defne and Ganju...
USGS CoastCam CACO-02 at Marconi Beach, Cape Cod National Seashore, Massachusetts (2024): Imagery and Calibration Data - Imagery Dataset USGS CoastCam CACO-02 at Marconi Beach, Cape Cod National Seashore, Massachusetts (2024): Imagery and Calibration Data - Imagery Dataset
A digital video camera was installed at Marconi Beach, Cape Cod National Seashore in Massachusetts (MA) as part of a U.S. Geological Survey (USGS) research project to study the beach and nearshore environment. The camera faced north-east along the beach and every hour during daylight hours, daily from January 2024 to September 2024, the camera collected raw video and produced snapshots...
USGS CoastCam CACO-02 at Marconi Beach, Cape Cod National Seashore, Massachusetts (2021, 2023, 2024): Imagery and Calibration Data USGS CoastCam CACO-02 at Marconi Beach, Cape Cod National Seashore, Massachusetts (2021, 2023, 2024): Imagery and Calibration Data
Two digital video cameras (CACO-02) were installed at Marconi Beach, Cape Cod National Seashore in Massachusetts (MA) as part of a U.S. Geological Survey (USGS) research project to study the beach and nearshore environment. The cameras faced north-east (c1) and east (c2) along the beach and every half hour during daylight hours. They ran daily from March through June 2021, Feburary...
Ground reference geospatial data collected on Fire Island National Seashore, NY, USA, September 16-19, 2024 Ground reference geospatial data collected on Fire Island National Seashore, NY, USA, September 16-19, 2024
Ground reference data in the form of ecogeomorphic evaluations, topographic survey measurements, and geotagged photographs were collected at four areas of interest (AOI) across Fire Island National Seashore (FIIS), NY, USA September 16-19, 2024, that document site conditions. The overall goals of USGS personnel for the data collection were to: (1) collect ground reference data that...