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Low-altitude (80 and 100 meters above ground level) digital images were taken over an area of the Plum Island Estuary and Parker River National Wildlife Refuge (NWR) in Massachusetts using 3DR Solo unmanned aircraft systems (UAS) on February 27, 2018. These images were collected as part of an effort to document marsh stability over time and quantify sediment movement using UAS technology. Each UAS was equipped with either a Ricoh GRII digital camera for natural color photos, used to produce digital elevation models and ortho images, or a MicaSense RedEdge multi-spectral camera that captures five specific bands of the visible spectrum (blue, green, red, red edge, and near-infrared), which can be used to classify...
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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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Coastal wetlands are major global carbon sinks, however, they are heterogeneous and dynamic ecosystems. To characterize spatial and temporal variability in a New England salt marsh, static chamber measurements of greenhouse gas (GHG) fluxes were compared among major plant-defined zones (high marsh dominated by Distichlis spicata and a zone of invasive Phragmites australis) during 2013 and 2014 growing seasons. Two sediment cores were collected in 2015 from the Phragmites zone to support previously reported core collections from the high marsh sites (Gonneea and others 2018). Collected cores were up to 70 cm in length with dry bulk density ranges from 0.04 to 0.33 grams per cubic centimeter and carbon content 22.4%...
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Transport of material in an estuary is important for water quality and hazards concern. We studied these processes in the Hudson River Estuary, located along the northeast coast of the U.S. using the COAWST numerical modeling system. A skill assessment of the COAWST model for the 3-D salinity structure of the estuary has been successfully studied in the past, and the present research extended that understanding to look at both physical and numerical mixing. The model grid extends from the south at the Battery, NY to the north in Troy, NY. The simulation is performed from March 25 to July 11, 2005 (111 days). For more information see: https://doi.org/10.5066/P95E8LAS.
Categories: Data; Types: Map Service, NetCDF OPeNDAP Service, OGC WMS Layer; Tags: CMG_Portal, Earth Science > Human Dimensions > Natural Hazards > Floods, Earth Science > Oceans > Marine Sediments >Sediment Transport, Earth Science > Oceans > Ocean Circulation > Ocean Currents, Earth Science > Oceans > Ocean Temperature > Potential Temperature, 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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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, CMHRP, 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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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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The development of Submerged Aquatic Vegetation (SAV) growth model within the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) model leads to a change in SAV biomass. The SAV biomass is computed from temperature, nutrient loading and light predictions obtained from coupled hydrodynamics (temperature), bio-geochemistry (nutrients) and bio-optical (light) models. In exchange, the growth of SAV sequesters or contributes nutrients from the water column and sediment layers. The presence of SAV modulates current and wave attenuation and consequently affects modelled sediment transport. The model of West Falmouth Harbor in Massachusetts, USA was simulated to study the seagrass growth/dieback pattern in a hypothetical...
Categories: Data; Types: Map Service, NetCDF OPeNDAP Service, OGC WMS Layer; Tags: CMG_Portal, Earth Science > Human Dimensions > Natural Hazards > Floods, Earth Science > Oceans > Marine Sediments >Sediment Transport, Earth Science > Oceans > Ocean Circulation > Ocean Currents, Earth Science > Oceans > Ocean Temperature > Potential Temperature, All tags...
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Two marine geological surveys were conducted in Long Island Sound, Connecticut and New York, in fall 2017 and spring 2018 by the U.S. Geological Survey, University of Connecticut, and University of New Haven through the Long Island Sound Mapping and Research Collaborative. Sea-floor images and videos were collected at 210 sampling sites within the survey area, and surficial sediment samples were collected at 179 of the sites. The sediment data and the observations from the images and videos are used to identify sediment texture and sea-floor habitats.
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Atlantic Ocean, Beckman Coulter Multisizer 3, CMHRP, CSV, Coastal and Marine Hazards and Resources Program, All tags...
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The U.S. Geological Survey, Woods Hole Coastal and Marine Science Center in cooperation with the University of Maine mapped approximately 50 square kilometers of the seafloor within Belfast Bay, Maine. Three geophysical surveys conducted in 2006, 2008 and 2009 collected swath bathymetric (2006 and 2008) and chirp seismic reflection profile data (2006 and 2009). The project characterized the spatial, morphological and subsurface variability of the Belfast Bay, Maine pockmark field. Pockmarks are large seafloor depressions that are associated with seabed fluid escape.
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Two marine geological surveys were conducted in Nantucket Sound, Massachusetts, in May 2016 and May 2017 by the U.S. Geological Survey as part of an agreement with the Massachusetts Office of Coastal Zone Management to map the geology of the sea floor offshore of Massachusetts. Samples of surficial sediment and photographs of the sea floor were collected at 76 sampling sites within the survey area, and sea-floor videos were collected at 75 of the sites. The sediment data and the observations from the photos and videos are used to explore the nature of the sea floor; in conjunction with high-resolution geophysical data, the observations are used to make interpretive maps of sedimentary environments and validate acoustic...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Atlantic Ocean, CMHRP, CZM, Coastal and Marine Hazards and Resources Program, MA CZM, All tags...
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This data publication is a compilation of six different multibeam surveys covering the previously unmapped Queen Charlotte Fault offshore southeast Alaska and Haida Gwaii, Canada. These data were collected between 2005 and 2018 under a cooperative agreement between the U.S. Geological Survey, Natural Resources Canada, and the National Oceanic and Atmospheric Administration. The six source surveys from different multibeam sonars are combined into one terrain model with a 30-m resolution. A complementary polygon shapefile records the extent of each source survey in the output grid.


map background search result map search result map True color aerial imagery from unmanned aerial systems (UAS) flights and image locations: Plum Island Estuary and Parker River NWR (PIEPR), February 27th, 2018 Numerical model of salinity transport and mixing in the Hudson River Estuary DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2012–2013 ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Edwin B. Forsythe NWR, NJ, 2012 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2010 Numerical model of Submerged Aquatic Vegetation (SAV) growth dynamics in West Falmouth Harbor without nitrate loading DisOcean: Distance to the ocean: Monomoy Island, MA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Assawoman Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fisherman Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Parramore Island, VA, 2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Parramore Island, VA, 2014 DisOcean: Distance to the ocean: Smith Island, VA, 2014 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Wreck Island, VA, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Wreck Island, VA, 2014 Location and grain-size analysis results of sediment samples collected in Long Island Sound, Connecticut and New York, in fall 2017 and spring 2018 by the U.S. Geological Survey, University of Connecticut, and University of New Haven during field activities 2017-056-FA and 2018-018-FA (simplified point shapefile and CSV files) Sea-floor videos and location of bottom video tracklines collected in Nantucket Sound, Massachusetts, in May 2016 and May 2017 by the U.S. Geological Survey during field activities 2016-005-FA and 2017-022-FA (MP4 video files and polyline shapefile) Seismic reflection-tracklines, shotpoints, and profile images collected in Belfast Bay, Maine using an EdgeTech SB-424 subbottom profiler during USGS field activities 2006-024-FA and 2009-037-FA (Esri polyline, and point shapefiles, WGS 84, and JPEG images) Polygon shapefile of data sources used to create a bathymetric terrain model of multibeam sonar data collected between 2005 and 2018 along the Queen Charlotte Fault System in the eastern Gulf of Alaska from Cross Sound, Alaska to Queen Charlotte Sound, Canada. (Esri polyon shapefile, UTM 8 WGS 84) Static chamber gas fluxes and carbon and nitrogen isotope content of age-dated sediment cores from a Phragmites wetland in Sage Lot Pond, Massachusetts, 2013-2015 Static chamber gas fluxes and carbon and nitrogen isotope content of age-dated sediment cores from a Phragmites wetland in Sage Lot Pond, Massachusetts, 2013-2015 True color aerial imagery from unmanned aerial systems (UAS) flights and image locations: Plum Island Estuary and Parker River NWR (PIEPR), February 27th, 2018 Numerical model of Submerged Aquatic Vegetation (SAV) growth dynamics in West Falmouth Harbor without nitrate loading DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Wreck Island, VA, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Wreck Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fisherman Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2014 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2012–2013 DisOcean: Distance to the ocean: Smith Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Parramore Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Assawoman Island, VA, 2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Parramore Island, VA, 2014 Sea-floor videos and location of bottom video tracklines collected in Nantucket Sound, Massachusetts, in May 2016 and May 2017 by the U.S. Geological Survey during field activities 2016-005-FA and 2017-022-FA (MP4 video files and polyline shapefile) DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Edwin B. Forsythe NWR, NJ, 2012 Location and grain-size analysis results of sediment samples collected in Long Island Sound, Connecticut and New York, in fall 2017 and spring 2018 by the U.S. Geological Survey, University of Connecticut, and University of New Haven during field activities 2017-056-FA and 2018-018-FA (simplified point shapefile and CSV files) shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2010 Numerical model of salinity transport and mixing in the Hudson River Estuary Polygon shapefile of data sources used to create a bathymetric terrain model of multibeam sonar data collected between 2005 and 2018 along the Queen Charlotte Fault System in the eastern Gulf of Alaska from Cross Sound, Alaska to Queen Charlotte Sound, Canada. (Esri polyon shapefile, UTM 8 WGS 84)