Skip to main content
Advanced Search

Filters: Tags: Geomorphology (X) > Date Range: {"choice":"year"} (X)

479 results (352ms)   

Filters
Date Types (for Date Range)
Extensions
Types
Contacts
Categories
Tag Types
Tag Schemes
View Results as: JSON ATOM CSV
thumbnail
Denitrification measurements and ecosystem attributes in hummock-hollow microtopography of tidal freshwater forested wetlands along longitudinal riverine positions (upper, middle, and lower tidal river sites, and nearby upstream nontidal forested floodplains) of the adjoining Pamunkey and Mattaponi Rivers, Virginia.
thumbnail
The Barrier Island Comprehensive Monitoring (BICM) program was developed by Louisiana’s Coastal Protection and Restoration Authority (CPRA) and is implemented as a component of the System Wide Assessment and Monitoring Program (SWAMP). The program uses both historical data and contemporary data collections to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. Examples of BICM datasets include still and video aerial photography for documenting shoreline changes, shoreline positions, habitat mapping, land change analyses, light detection and ranging (lidar) surveys for topographic...
thumbnail
The files consist of two types: tabulated data files and graphical map files. Data files consist of six .csv files, representing six experiment dates (2016_06_14, 2016_16_15, 2016_18_15, 2016_16_21, 2016_16_22, 2016_16_23). Each of these files contains multiple columns of data, with each column representing either a time measurement or the value of a physical quantity measured at that time (e.g., flow depth, pore pressure, normal stress, etc.). Map files consist of six .pdf files, each representing an experiment date listed above. The maps show the thickness of the sediment deposited onto the runout pad after each experiment. Sediment thickness was determined using photogrammetery software from Adam Technology.
thumbnail
These data are bathymetry (river bottom elevation) in XYZ format, generated from the March 29-30, 2017 and April 13, 2017, bathymetric survey of the East Fork White River at Columbus, Indiana. The bathymetry was collected from approximately the confluence of Driftwood and Flatrock rivers, downstream to the confluence of Haw Creek. Hydrographic data were collected using an acoustic Doppler current profiler (ADCP) with integrated Differential Global Positioning System (DGPS). Data were collected as the surveying vessel traversed the river, approximately perpendicular to the velocity vectors at 55 cross sections which were spaced 200 feet apart along the river. Additional cross sections were collected upstream and...
thumbnail
The Barrier Island Comprehensive Monitoring (BICM) program was developed by Louisiana’s Coastal Protection and Restoration Authority (CPRA) and is implemented as a component of the System Wide Assessment and Monitoring Program (SWAMP). The program uses both historical data and contemporary data collections to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. Examples of BICM datasets include still and video aerial photography for documenting shoreline changes, shoreline positions, habitat mapping, land change analyses, light detection and ranging (lidar) surveys for topographic...
thumbnail
The Barrier Island Comprehensive Monitoring (BICM) program was developed by Louisiana’s Coastal Protection and Restoration Authority (CPRA) and is implemented as a component of the System Wide Assessment and Monitoring Program (SWAMP). The program uses both historical data and contemporary data collections to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. Examples of BICM datasets include still and video aerial photography for documenting shoreline changes, shoreline positions, habitat mapping, land change analyses, light detection and ranging (lidar) surveys for topographic...
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...
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
This dataset consists of point cloud data collected in 2016 and 2017 of the lower and upper Scenic Drive landslide locations in La Honda, California. Point cloud data were collected in 2016 to establish baseline for movement detection of past landslides. Point cloud data were collected in 2017 adjacent and upslope of 2016 data to document a newly formed landslide. The data were collected with a Riegl VZ400 Terrestrial Laser Scanner and georeferenced using a Leica Viva GS15 survey grade GPS. The data are delivered as georeferenced (NAD83 UTM zone 10N ellipsoid) classified point clouds, 5 cm resolution digital elevation models, and a text file of surveyed GPS control points. The included files are: LH2017_Jan.laz...
thumbnail
High-resolution acoustic backscatter data, bathymetry data, single channel minisparker seismic-reflection data were collected by the U.S. Geological Survey (USGS) and the Alaska Department of Fish and Game in May of 2014 southwest of Chenega Island and southwest of Montague Island, Alaska. Data were collected aboard the Alaska Department of Fish and Game vessel, R/V Solstice, during USGS field activity 2014-622-FA, using a pole mounted 100-kHz Reson 7111 multibeam echosounder, a 500 Joule SIG 2-mille minisparker sound source and a single channel streamer.
thumbnail
Scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center investigated the sedimentary and geochemical properties of the lower reaches of the Pascagoula River along the Mississippi coast of the Gulf of Mexico by collecting estuarine, riverine and marsh sediments. This was done in order to increase understanding of the region's environmental history, describe the long-term (millennial-scale) depositional history, and identify sedimentary intervals associated with extreme marine intrusions. To this end, the group obtained long sediment cores, shovel-dug sediment slabs and marsh and riverine channel/estuarine surface samples from a north-south transect along the river edge from...
thumbnail
This digital elevation model provides a tool for calibrating tsunami risk to observations of the 1945 Makran tsunami in Karachi Harbour. The DEM bathymetry is derived from soundings made mainly during the first eight years after the tsunami. Although deficient in portraying intertidal backwaters and upland topography, the DEM accurately depicts the sheltered setting of one of the two tide gauges that recorded the 1945 tsunami.


map background search result map search result map Sensor data from debris-flow experiments conducted in June, 2016, at the USGS debris-flow flume, HJ Andrews Experimental Forest, Blue River, Oregon Bathymetry on the East Fork White River at Columbus, Indiana, March 29-30 and April 13, 2017 Fish/Judy Creek Watershed map Terrestrial lidar data from the 2017 Upper Scenic Drive Landslide, La Honda, California: classified point cloud and gridded elevation data from 2016-2017 Sedimentary data from the lower Pascagoula River, Mississippi, USA Bathymetric and topographic grid intended for simulations of the 1945 Makran tsunami in Karachi Harbour Data on soil denitrification potential and physico-chemical characteristics of tidal freshwater forested wetlands in Virginia Louisiana Barrier Island Comprehensive Monitoring Program – 2015 habitat map, West Chenier Region Louisiana Barrier Island Comprehensive Monitoring Program – 2008-2016 habitat change, Modern Delta Region Louisiana Barrier Island Comprehensive Monitoring Program – 2008 habitat map, East Chenier Region 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 Sensor data from debris-flow experiments conducted in June, 2016, at the USGS debris-flow flume, HJ Andrews Experimental Forest, Blue River, Oregon Bathymetry on the East Fork White River at Columbus, Indiana, March 29-30 and April 13, 2017 Sedimentary data from the lower Pascagoula River, Mississippi, USA SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2012–2013 Bathymetric and topographic grid intended for simulations of the 1945 Makran tsunami in Karachi Harbour 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 Louisiana Barrier Island Comprehensive Monitoring Program – 2008-2016 habitat change, Modern Delta Region Data on soil denitrification potential and physico-chemical characteristics of tidal freshwater forested wetlands in Virginia Terrestrial lidar data from the 2017 Upper Scenic Drive Landslide, La Honda, California: classified point cloud and gridded elevation data from 2016-2017 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 Fish/Judy Creek Watershed map