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The U.S. Geological Survey has been forecasting sea-level rise impacts on the landscape to evaluate where coastal land will be available for future use. The purpose of this project is to develop a spatially explicit, probabilistic model of coastal response for the Northeastern U.S. to a variety of sea-level scenarios that take into account the variable nature of the coast and provides outputs at spatial and temporal scales suitable for decision support. Model results provide predictions of adjusted land elevation ranges (AE) with respect to forecast sea-levels, a likelihood estimate of this outcome (PAE), and a probability of coastal response (CR) characterized as either static or dynamic. The predictions span the...
Categories: Data;
Tags: Atlantic City,
Atlantic Ocean,
Bayesian network,
Boston,
CMGP, All tags...
Chesapeake Bay,
Coastal and Marine Geology Program,
Connecticut,
Delaware,
Esri binary grid,
Gridded Raster Dataset,
Jersey Shore,
Long Island,
Maine,
Maryland,
Massachusetts,
New England,
New Hampshire,
New Jersey,
New York,
Norfolk,
North America,
Northeast CASC,
Ocean City,
Sea-Level Rise and Coasts,
U.S. Geological Survey,
USGS,
United States,
Virginia,
WHCMSC,
Water, Coasts and Ice,
Wetlands,
Woods Hole Coastal and Marine Science Center,
biota,
elevation,
environment,
geoscientificInformation,
imageryBaseMapsEarthCover,
landscape change,
oceans,
probabilistic predictions,
sea-level rise, Fewer tags
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The U.S. Geological Survey has been forecasting sea-level rise impacts on the landscape to evaluate where coastal land will be available for future use. The purpose of this project is to develop a spatially explicit, probabilistic model of coastal response for the Northeastern U.S. to a variety of sea-level scenarios that take into account the variable nature of the coast and provides outputs at spatial and temporal scales suitable for decision support. Model results provide predictions of adjusted land elevation ranges (AE) with respect to forecast sea-levels, a likelihood estimate of this outcome (PAE), and a probability of coastal response (CR) characterized as either static or dynamic. The predictions span the...
Categories: Data;
Tags: Atlantic City,
Atlantic Ocean,
Bayesian network,
Boston,
CMGP, All tags...
Chesapeake Bay,
Coastal and Marine Geology Program,
Connecticut,
Delaware,
Esri binary grid,
Gridded Raster Dataset,
Jersey Shore,
Long Island,
Maine,
Maryland,
Massachusetts,
New England,
New Hampshire,
New Jersey,
New York,
Norfolk,
North America,
Northeast CASC,
Ocean City,
Sea-Level Rise and Coasts,
U.S. Geological Survey,
USGS,
United States,
Virginia,
WHCMSC,
Water, Coasts and Ice,
Wetlands,
Woods Hole Coastal and Marine Science Center,
biota,
elevation,
environment,
geoscientificInformation,
imageryBaseMapsEarthCover,
landscape change,
oceans,
probabilistic predictions,
sea-level rise, Fewer tags
|
The U.S. Geological Survey has been forecasting sea-level rise impacts on the landscape to evaluate where coastal land will be available for future use. The purpose of this project is to develop a spatially explicit, probabilistic model of coastal response for the Northeastern U.S. to a variety of sea-level scenarios that take into account the variable nature of the coast and provides outputs at spatial and temporal scales suitable for decision support. Model results provide predictions of adjusted land elevation ranges (AE) with respect to forecast sea-levels, a likelihood estimate of this outcome (PAE), and a probability of coastal response (CR) characterized as either static or dynamic. The predictions span the...
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