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This data release consist of the annual sediment depositional volume at five floodplain and five point bar sites on Powder River in southeastern Montana from 1979 through 2017. These 10 sites are a subgroup of a larger group of cross-sections established in 1975 and 1977 to monitor the channel changes along a 90-kilometer reach of Powder River. In addition to the sediment deposition data, characteristic of the annual peak flood are listed. The data are in 1 Excel files containing worksheets (10) corresponding to each channel cross-section .
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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.
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Water surface elevations within seven Willamette River off-channel features (OCF; alcoves and side channels) were measured using submerged pressure transducers. Transducers were installed from late May through mid-October, 2016, when discharge of the Willamette River was between approximately 5,500 and 45,000 cubic feet per second at Salem, Oregon (USGS gage 14191000) and 3,500 to 17,500 cubic feet per second at Harrisburg, Oregon (USGS gage 14166000). Pressure transducer sensor depth was measured at all seven sites. For five of the sites, pressure transducer sensor depths were converted to water surface elevations by surveying the water surface at each transducer with a real-time kinematic global positioning system...
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The Leadville North 7.5' quadrangle lies at the northern end of the Upper Arkansas Valley, where the Continental Divide at Tennessee Pass creates a low drainage divide between the Colorado and Arkansas River watersheds. In the eastern half of the quadrangle, the Paleozoic sedimentary section dips generally 20–30 degrees east. At Tennessee Pass and Missouri Hill, the core of the Sawatch anticlinorium is mapped as displaying a tight hanging-wall syncline and foot-wall anticline within the basement-cored structure. High-angle, west-dipping, Neogene normal faults cut the eastern margin of the broad, Sawatch anticlinorium. Minor displacements along high-angle, east- and west-dipping Laramide reverse faults occurred in...
Tags: 10Be, 26Al, Belden Formation, Buckeye Peak, Bull Lake glaciation, Camp Hale, All tags...
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Wetland restoration efforts conducted by the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in Louisiana rely on monitoring efforts to determine the efficacy of these efforts. The Coastwide Reference Monitoring System (CRMS) was developed to assist in a multiple-reference approach that uses aspects of hydrogeomorphic functional assessments and probabilistic sampling for monitoring. The CRMS program includes a suite of approximately 390 sites that encompass the range of hydrological and ecological conditions for each stratum. As part of CRMS, land and water classifications are created from Digital Orthophoto Quarter Quadrangles (DOQQs) approximately every three years at all CRMS sites. A DOQQ...
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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...
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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.
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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.
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We used the 1981 historical imagery of the Escalante River, Utah in ArcGIS to quantify channel area and average width and quantify woody riparian vegetation cover in two reaches of the river. Reach 1 was approximately 15 river kilometers (rkms) long and located between Sand and Boulder creeks within Grand Staircase Escalante National Monument. Reach 2 was approximately 16 rkms in length, extending from the Glen Canyon National Recreation Area boundary to just upstream of Choprock Canyon. We delineated the extent of active channel. Active channel was defined as the portion of the channel free of vegetation. We also delineated fluvial geomorphic features such as point bars, mid-channel bars, lateral bars and floodplain....


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 Coastwide Reference Monitoring System (CRMS) 2015 land-water classifications Water surface elevations recorded by submerged water level loggers in off-channel features of the middle and upper Willamette River, Oregon, Summer, 2016 Terrestrial lidar data from the 2017 Upper Scenic Drive Landslide, La Honda, California: classified point cloud and gridded elevation data from 2016-2017 Data release for Geologic Map of the Leadville North 7.5' quadrangle, Eagle and Lake Counties, Colorado A polygon shapefile of bottomland vegetation cover and geomorphic features of the Escalante River, Utah mapped from 1981 aerial imagery Sediment Deposition on Floodplains and Point Bars of Powder River in Southeastern Montana from 1979 through 2017 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 Data release for Geologic Map of the Leadville North 7.5' quadrangle, Eagle and Lake Counties, Colorado A polygon shapefile of bottomland vegetation cover and geomorphic features of the Escalante River, Utah mapped from 1981 aerial imagery 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 Louisiana Barrier Island Comprehensive Monitoring Program – 2015 habitat map, West Chenier Region 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 Water surface elevations recorded by submerged water level loggers in off-channel features of the middle and upper Willamette River, Oregon, Summer, 2016 Louisiana Barrier Island Comprehensive Monitoring Program – 2008 habitat map, East Chenier Region Sediment Deposition on Floodplains and Point Bars of Powder River in Southeastern Montana from 1979 through 2017 Coastwide Reference Monitoring System (CRMS) 2015 land-water classifications