Skip to main content
U.S. flag

An official website of the United States government

Images

Coastal and Marine Hazards and Resources Program images.

Filter Total Items: 2491
Pilots from two USGS Coastal and Marine Science Centers collect imagery data using Unmanned Aerial System, while personnel from
Scientists collect data on Pelican Island, Alabama
Scientists collect data on Pelican Island, Alabama
Scientists collect data on Pelican Island, Alabama

In an effort spanning the Natural Hazards and Ecosystems Mission Areas, pilots from the Saint Petersburg and Woods Hole Coastal and Marine Science Centers collect imagery data using Unmanned Aerial System (UAS) while personnel from the Wetlands and Aquatic Research Center (WARC) conduct ground-based site surveys of Pelican Island, Alabama.

In an effort spanning the Natural Hazards and Ecosystems Mission Areas, pilots from the Saint Petersburg and Woods Hole Coastal and Marine Science Centers collect imagery data using Unmanned Aerial System (UAS) while personnel from the Wetlands and Aquatic Research Center (WARC) conduct ground-based site surveys of Pelican Island, Alabama.

a map shows a coastal area turning from green to blue (indicating water) across a future sea-level rise projection to 2100
Modeling Grand Bay Marsh Productivity with Sea-Level Rise
Modeling Grand Bay Marsh Productivity with Sea-Level Rise
Modeling Grand Bay Marsh Productivity with Sea-Level Rise

Scientists at the USGS St. Petersburg Coastal and Marine Science Center use Hydro-MEM, a two-dimensional coastal wetland model that integrates an Advanced Circulation hydrodynamic model with a Marsh Equilibrium Model to project marsh response to sea-level rise.

Scientists at the USGS St. Petersburg Coastal and Marine Science Center use Hydro-MEM, a two-dimensional coastal wetland model that integrates an Advanced Circulation hydrodynamic model with a Marsh Equilibrium Model to project marsh response to sea-level rise.

sphalerite, cubes of pyrite, and covellite
Sulfide minerals
Sulfide minerals
Sulfide minerals

Examples of sulfide minerals that occur at hydrothermal vents and are being studied by Amy Gartman: (left to right) sphalerite, an ore of zinc that often contains iron ([Zn,Fe]S); cubes of pyrite, rich in iron (FeS2); and covellite, containing copper and sulfur (CuS).The pyrite cubes are a little more than half an inch on a side.

Examples of sulfide minerals that occur at hydrothermal vents and are being studied by Amy Gartman: (left to right) sphalerite, an ore of zinc that often contains iron ([Zn,Fe]S); cubes of pyrite, rich in iron (FeS2); and covellite, containing copper and sulfur (CuS).The pyrite cubes are a little more than half an inch on a side.

Black smoke billows out of a crusty vent on the ocean floor.
Mineral-laden water emerging from a hydrothermal vent
Mineral-laden water emerging from a hydrothermal vent
Mineral-laden water emerging from a hydrothermal vent

Mineral-laden water emerging from a hydrothermal vent on the Niua underwater volcano in the Lau Basin, southwest Pacific Ocean. As the water cools, minerals precipitate to form tower-like “chimneys.” Image taken during 2016 cruise “Virtual Vents.”  

Mineral-laden water emerging from a hydrothermal vent on the Niua underwater volcano in the Lau Basin, southwest Pacific Ocean. As the water cools, minerals precipitate to form tower-like “chimneys.” Image taken during 2016 cruise “Virtual Vents.”  

Web browser screen showing an application with different parameters and controls on left and the resulting map on right.
Screenshot of Our Coast, Our Future
Screenshot of Our Coast, Our Future
Screenshot of Our Coast, Our Future

Screenshot of Our Coast, Our Future (OCOF) interactive map view of Stinson Beach, California, showing extent of flooding predicted if subjected to a sea-level rise of 100 centimeters (about 40 inches) and elevated water levels caused by a 100-year storm.

Screenshot of Our Coast, Our Future (OCOF) interactive map view of Stinson Beach, California, showing extent of flooding predicted if subjected to a sea-level rise of 100 centimeters (about 40 inches) and elevated water levels caused by a 100-year storm.

Coastal bathymetry, St. Thomas, US Virgin Islands, mapped using lidar and depicted with false-color
Coastal bathymetry, St. Thomas, US Virgin Islands, mapped using lidar
Coastal bathymetry, St. Thomas, US Virgin Islands, mapped using lidar
Coastal bathymetry, St. Thomas, US Virgin Islands, mapped using lidar

Coastal bathymetry, St. Thomas, US Virgin Islands, mapped using lidar and depicted with false-color (purple is deep, orange is shallow). Land areas are depicted with satellite imagery.

East end of Fire Island depicted with airborne imagery and lidar
East end of Fire Island depicted with airborne imagery and lidar
East end of Fire Island depicted with airborne imagery and lidar
East end of Fire Island depicted with airborne imagery and lidar

East end of Fire Island, showing white sandy beaches and marshes, depicted with airborne imagery, and lidar-derived bathymetric features in the estuary behind the island, in the offshore region, and in the channel connecting the estuary to the ocean. 

East end of Fire Island, showing white sandy beaches and marshes, depicted with airborne imagery, and lidar-derived bathymetric features in the estuary behind the island, in the offshore region, and in the channel connecting the estuary to the ocean. 

Seamless integrated elevation data for both land and submerged areas in Barnegat Bay, New Jersey
Elevation data for land and submerged areas, Barnegat Bay, NJ
Elevation data for land and submerged areas, Barnegat Bay, NJ
Elevation data for land and submerged areas, Barnegat Bay, NJ

 Coastal storms can severely alter the topography and ecosystems along heavily populated coastal regions. Seamless integrated elevation data for both land and submerged areas in Barnegat Bay, New Jersey, are fundamental to coastal planning of the northeastern U.S. Atlantic coast.

 Coastal storms can severely alter the topography and ecosystems along heavily populated coastal regions. Seamless integrated elevation data for both land and submerged areas in Barnegat Bay, New Jersey, are fundamental to coastal planning of the northeastern U.S. Atlantic coast.

Photo showing the cave passage and diver, with green tint from the water and strong shadows from the light source.
Diver in cave
Diver in cave
Diver in cave

Cave passage and diver (Bil Philips, cave explorer) in Ox Bel Ha Cave System of the northeastern Yucatan Peninsula.

Cave passage and diver (Bil Philips, cave explorer) in Ox Bel Ha Cave System of the northeastern Yucatan Peninsula.

Map shows the central part of California near Monterey, with onshore and offshore faults and features labeled.
Faults and features of the Big Sur area
Faults and features of the Big Sur area
Faults and features of the Big Sur area

Shaded-relief map of central California showing location of the Big Sur area (white dashed line). Red line shows the San Gregorio-Hosgri fault (SGHF) and the Big Sur Bend between Point Sur (PS) and Piedras Blancas (PB). Black lines show other faults.

Shaded-relief map of central California showing location of the Big Sur area (white dashed line). Red line shows the San Gregorio-Hosgri fault (SGHF) and the Big Sur Bend between Point Sur (PS) and Piedras Blancas (PB). Black lines show other faults.

A pole has two shaded cameras mounted on it and they are pointing at a beach from high up on a grassy bluff.
Sunset State Beach webcams
Sunset State Beach webcams
Sunset State Beach webcams

USGS Pacific Coastal and Marine Science Center in Santa Cruz, California installed these two video cameras, pointed at the shoreline. The cameras collected imagery every half hour for 10 minutes, during daylight hours. The images are stored in the cloud and are used to study coastal variations through time, like wave, shoreline, and sandbar dynamics.

USGS Pacific Coastal and Marine Science Center in Santa Cruz, California installed these two video cameras, pointed at the shoreline. The cameras collected imagery every half hour for 10 minutes, during daylight hours. The images are stored in the cloud and are used to study coastal variations through time, like wave, shoreline, and sandbar dynamics.

Image showing the deployment of seismic equipment from a research vessel, examples of seismic data, and examples of seismic
Seismic Collage
Seismic Collage
Seismic Collage

Image showing a collage of examples of multi-channel and single-channel seismic data collected by the USGS, seismic equipment deployed from a research vessel, and seismic equipment on a research vessel.  These data are critical to the CMG Program as they define the geology in marine and coastal environments.

Image showing a collage of examples of multi-channel and single-channel seismic data collected by the USGS, seismic equipment deployed from a research vessel, and seismic equipment on a research vessel.  These data are critical to the CMG Program as they define the geology in marine and coastal environments.

Image showing example of seafloor images and deployment of the SEABOSS sampler.
SEABOSS Collage
SEABOSS Collage
SEABOSS Collage

SEABed Observation and Sampling System (SEABOSS) (center image) and the MiniSEABOSS (right) designed for rapid, inexpensive, and effective collection of seabed imagery (photographs and video) as well sediment samples from the coastal/inner-continental shelf regions.

SEABed Observation and Sampling System (SEABOSS) (center image) and the MiniSEABOSS (right) designed for rapid, inexpensive, and effective collection of seabed imagery (photographs and video) as well sediment samples from the coastal/inner-continental shelf regions.

 Three-dimensional model of Chimney Bluffs, New York along Lake Ontario
Three-dimensional model of Chimney Bluffs, New York along Lake Ontari
Three-dimensional model of Chimney Bluffs, New York along Lake Ontari
Three-dimensional model of Chimney Bluffs, New York along Lake Ontari

Three-dimensional model of Chimney Bluffs, New York along Lake Ontario created from low-altitude digital images collected from an unmanned aerial system (UAS).

Map of distribution sediment textures from Nantucket and Marthas Vineyard, Massachusetts
Sediment textures distribution from Nantucket and Marthas Vineyard, MA
Sediment textures distribution from Nantucket and Marthas Vineyard, MA
Sediment textures distribution from Nantucket and Marthas Vineyard, MA

The distribution of sediment textures within the study area. The bottom-type classification is from Barnhardt and others (1998) and is based on 16 sediment classes. The classification is based on four sediment units that include gravel (G), mud (M), rock (R), and sand (S). If the texture is greater than 90 percent, it is labeled with a single letter.

The distribution of sediment textures within the study area. The bottom-type classification is from Barnhardt and others (1998) and is based on 16 sediment classes. The classification is based on four sediment units that include gravel (G), mud (M), rock (R), and sand (S). If the texture is greater than 90 percent, it is labeled with a single letter.

Geologic sections illustrating general distributions and thickness of seismic stratigraphic units Marthas Vineyard, Nantucket
Nantucket and Marthas Vineyard geologic illustrations
Nantucket and Marthas Vineyard geologic illustrations
Nantucket and Marthas Vineyard geologic illustrations

Geologic sections (C-C', D-D', and E-E') illustrating the general distributions and thicknesses of seismic stratigraphic units and major unconformities in the Martha’s Vineyard and Nantucket study areas.

Geologic sections (C-C', D-D', and E-E') illustrating the general distributions and thicknesses of seismic stratigraphic units and major unconformities in the Martha’s Vineyard and Nantucket study areas.

 Department of Interior UAS pilots
UAS pilots at Kilauea
UAS pilots at Kilauea
UAS pilots at Kilauea

Department of Interior UAS pilots from left to right – Elizabeth Pendleton (USGS, Woods Hole, MA), Colin Milone (Office of Aviation Services, AK), John Vogel (USGS; Flagstaff, AZ), Sandy Brosnahan (USGS, Woods Hole, MA), Brandon Forbes (USGS; Tucson, AZ), Chris Holmquist-Johnson (USGS; Fort Collins, CO),&nb

Department of Interior UAS pilots from left to right – Elizabeth Pendleton (USGS, Woods Hole, MA), Colin Milone (Office of Aviation Services, AK), John Vogel (USGS; Flagstaff, AZ), Sandy Brosnahan (USGS, Woods Hole, MA), Brandon Forbes (USGS; Tucson, AZ), Chris Holmquist-Johnson (USGS; Fort Collins, CO),&nb

Was this page helpful?