Skip to main content
Advanced Search

Filters: Tags: usa (X) > partyWithName: U.S. Geological Survey (X)

351 results (1s)   

Filters
Date Range
Extensions
Types
Contacts
Categories
Tag Types
Tag Schemes
View Results as: JSON ATOM CSV
thumbnail
The data set consists of time, depth, reflection coefficient synthetic, sonic velocity, density, and amplitude used to create synthetic seismogram - City of Hollywood Utility, G-2961, (HOL-IW1), Broward County, Florida.
thumbnail
Located in the northern tropical Pacific Ocean, Majuro is the capital of the Republic of the Marshall Islands. Majuro Atoll consists of a large, narrow landmass and a set of smaller perimeter islands surrounding a lagoon that is over 100 square miles in size. The waters surrounding the Majuro Atoll land areas are relatively shallow with poorly mapped bathymetry. However, the Pacific Ocean on the exterior of the coral atoll and the lagoon within its interior consist of deep bathymetry with steep slopes. The highest elevation of the Majuro Atoll is estimated at only 3-meters above sea level, which is the island community of Laura located on the western part of the atoll. At the eastern edge of the atoll lies the capital...
Categories: Data; Tags: 3D Elevation Program, 3DEP, American Society of Photogrammetry and Remote Sensing, Base Maps, Bathymetric, All tags...
thumbnail
These digital images were taken at select locations over the Potomac River using 3DR Solo unmanned aircraft systems (UAS) in October 2019. These images were collected for the purpose of evaluating UAS assessment of river habitat data such as water depth, substrate type, and water clarity. Each UAS was equipped with a Ricoh GRII digital camera for natural color photos, used to produce digital elevation models and ortho images, a MicaSense RedEdge multi-spectral camera that captures five specific bands of the visible spectrum (blue, green, red, rededge, and near-infrared), which can be used to classify vegetation, or FLIR Vue Pro R 640 13mm radiometric thermal camera that provides temperature data embedded in every...
thumbnail
These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Missouri River near Structure G0069 on Missouri State Highway 240 at Glasgow, Missouri, in 2011, 2013, and 2017. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and...
thumbnail
These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Mississippi River near structure A5054 on Interstate 72 at Hannibal, Missouri, in 2014 and 2018. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position...
thumbnail
These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Missouri River near dual bridge structure A3665 on U.S. Highway 36 at St. Joseph, Missouri, in 2011, 2014, and 2018. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal...
thumbnail
These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Mississippi River near structure A5076 on Missouri State Highway 34 at Cape Girardeau, Missouri, in 2014 and 2018. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal...
thumbnail
These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Mississippi River near structure A1700 on Interstate 155 near Caruthersville, Missouri, in 2008, 2011, 2014 and 2018. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal...
thumbnail
Low-altitude (80 and 100 meters above ground level) digital images were collected at Sage Lot Pond in Waquoit, Massachusetts, two sites on the Mill River in Taunton, MA, Great Marsh in Barnstable, MA, the Wells National Estuarine Research Reserve in Wells, ME, and on the Woods Hole Oceanographic Institution Quissett Campus in Woods Hole, MA using 3DR Solo unoccupied aircraft systems (UAS) during 2018. These images were collected to support science and data needs in wetland research, topographic mapping, and landcover detection at the U.S. Geological Survey Woods Hole Coastal and Marine Science Center. The imagery and associated ground control points can be used to create Digital Elevation Models (DEMs), orthoimages,...
This data release contains luminescence and weather data from eastern Chuckwalla Valley, Riverside County, California. This study investigates sedimentary and geomorphic processes in eastern Chuckwalla Valley, Riverside County, California, a region of arid, basin-and-range terrain where extensive solar-energy development is planned. The objectives were to (1) measure local weather parameters and use them to model aeolian sediment transport potential; (2) identify surface sedimentary characteristics in representative localities; and (3) evaluate longer-term landscape evolution rates and processes by analyzing stratigraphy in combination with luminescence geochronology.
Categories: Data; Tags: California, USA, luminescence
thumbnail
Low-altitude (80 and 100 meters above ground level) digital images were collected at Sage Lot Pond in Waquoit, Massachusetts, two sites on the Mill River in Taunton, MA, Great Marsh in Barnstable, MA, the Wells National Estuarine Research Reserve in Wells, ME, and on the Woods Hole Oceanographic Institution Quissett Campus in Woods Hole, MA using 3DR Solo unoccupied aircraft systems (UAS) during 2018. These images were collected to support science and data needs in wetland research, topographic mapping, and landcover detection at the U.S. Geological Survey Woods Hole Coastal and Marine Science Center. The imagery and associated ground control points can be used to create Digital Elevation Models (DEMs), orthoimages,...
thumbnail
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
thumbnail
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
thumbnail
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
thumbnail
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
thumbnail
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, OGC WFS Layer, OGC WMS Layer, Raster, Shapefile; Tags: Atlantic Ocean, Barrier Island, Bayesian Network, CMGP, Coastal Erosion, All tags...
thumbnail
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
thumbnail
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
thumbnail
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...


map background search result map search result map G-2946 : Synthetic Seismogram Data for Correlation Between Seismic-Reflection Profiles and Well Data, Broward County, Florida G-2961 (HOL-IW1) : Synthetic Seismogram Data for Correlation Between Seismic-Reflection Profiles and Well Data, Broward County, Florida One Meter Topobathymetric Digital Elevation Model for Majuro Atoll, Republic of the Marshall Islands, 1944 to 2016 Site 17 Missouri River Bathymetry and Velocimetry Data at Structure G0069 on Missouri State Highway 240 at Glasgow, Missouri, July 2011 through May 2017 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2012–2013 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2010 DisOcean: Distance to the ocean: Edwin B. Forsythe NWR, NJ, 2012 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Edwin B. Forsythe NWR, NJ, 2013–2014 DisOcean: Distance to the ocean: Edwin B. Forsythe NWR, NJ, 2014 ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2010–2011 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2012 Site 02 Missouri River Bathymetry and Velocimetry Data at Dual Bridge Structure A3665 on U.S. Highway 36 at St. Joseph, Missouri, July 2011 through July 2018 Site 31 Mississippi River Bathymetry and Velocimetry Data at Structure A5054 on Interstate 72 at Hannibal, Missouri, June 2014 and July 2018 Site 37 Mississippi River Bathymetry and Velocimetry Data at Structure A5076 on Missouri State Highway 34 at Cape Girardeau, Missouri, June 2014 and July 2018 Site 38 Mississippi River Bathymetry and Velocimetry Data at Structure A1700 on Interstate 155 near Caruthersville, Missouri, December 2008 through July 2018 Low-altitude aerial imagery from unmanned aerial systems (UAS) at select locations over the Potomac River, October 2019 Multispectral aerial imagery collected during unoccupied aircraft systems (UAS) operations in Massachusetts between March 2018 - September 2018 Ground control points collected during unoccupied aircraft systems (UAS) operations in Massachusetts and Maine between March 2018 - September 2018 Luminescence and weather data from eastern Chuckwalla Valley, Riverside County, California Site 02 Missouri River Bathymetry and Velocimetry Data at Dual Bridge Structure A3665 on U.S. Highway 36 at St. Joseph, Missouri, July 2011 through July 2018 Site 17 Missouri River Bathymetry and Velocimetry Data at Structure G0069 on Missouri State Highway 240 at Glasgow, Missouri, July 2011 through May 2017 Site 37 Mississippi River Bathymetry and Velocimetry Data at Structure A5076 on Missouri State Highway 34 at Cape Girardeau, Missouri, June 2014 and July 2018 Site 31 Mississippi River Bathymetry and Velocimetry Data at Structure A5054 on Interstate 72 at Hannibal, Missouri, June 2014 and July 2018 Site 38 Mississippi River Bathymetry and Velocimetry Data at Structure A1700 on Interstate 155 near Caruthersville, Missouri, December 2008 through July 2018 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2012–2013 Luminescence and weather data from eastern Chuckwalla Valley, Riverside County, California SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2012 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2010–2011 Multispectral aerial imagery collected during unoccupied aircraft systems (UAS) operations in Massachusetts between March 2018 - September 2018 One Meter Topobathymetric Digital Elevation Model for Majuro Atoll, Republic of the Marshall Islands, 1944 to 2016 DisOcean: Distance to the ocean: Edwin B. Forsythe NWR, NJ, 2012 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Edwin B. Forsythe NWR, NJ, 2013–2014 DisOcean: Distance to the ocean: Edwin B. Forsythe NWR, NJ, 2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2010 ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2014 G-2946 : Synthetic Seismogram Data for Correlation Between Seismic-Reflection Profiles and Well Data, Broward County, Florida G-2961 (HOL-IW1) : Synthetic Seismogram Data for Correlation Between Seismic-Reflection Profiles and Well Data, Broward County, Florida Low-altitude aerial imagery from unmanned aerial systems (UAS) at select locations over the Potomac River, October 2019 Ground control points collected during unoccupied aircraft systems (UAS) operations in Massachusetts and Maine between March 2018 - September 2018