Dataset Identification:
Resource Abstract:
- description: 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 coastal zone vertically
from -12 meters (m) to 10 m above mean high water (MHW). Results are produced at a horizontal resolution of 30 meters for
four decades (the 2020s, 2030s, 2050s and 2080s). Adjusted elevations and their respective probabilities are generated using
regional geospatial datasets of current sea-level forecasts, vertical land movement rates, and current elevation data. Coastal
response type predictions incorporate adjusted elevation predictions with land cover data and expert knowledge to determine
the likelihood that an area will be able to accommodate or adapt to water level increases and maintain its initial land class
state or transition to a new non-submerged state (dynamic) or become submerged (static). Intended users of these data include
scientific researchers, coastal planners, and natural resource management communities.; abstract: 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 coastal zone vertically from -12 meters (m) to 10 m above
mean high water (MHW). Results are produced at a horizontal resolution of 30 meters for four decades (the 2020s, 2030s, 2050s
and 2080s). Adjusted elevations and their respective probabilities are generated using regional geospatial datasets of current
sea-level forecasts, vertical land movement rates, and current elevation data. Coastal response type predictions incorporate
adjusted elevation predictions with land cover data and expert knowledge to determine the likelihood that an area will be
able to accommodate or adapt to water level increases and maintain its initial land class state or transition to a new non-submerged
state (dynamic) or become submerged (static). Intended users of these data include scientific researchers, coastal planners,
and natural resource management communities.
Citation
- Title 30 meter Esri binary grids of probability of predicted elevation with respect to projected sea levels for the Northeastern
U.S. from Maine to Virginia for the 2020s, 2030s, 2050s and 2080s (Albers, NAD 83).
-
- creation Date
2018-05-20T18:20:34.016775
Resource language:
Processing environment:
Back to top:
Metadata data stamp:
2018-08-07T01:04:31Z
Resource Maintenance Information
- maintenance or update frequency:
- notes: This metadata record was generated by an xslt transformation from a dc metadata record; Transform by Stephen M. Richard, based
on a transform by Damian Ulbricht. Run on 2018-08-07T01:04:31Z
Metadata contact
-
pointOfContact
- organisation Name
CINERGI Metadata catalog
-
- Contact information
-
-
- Address
-
- electronic Mail Address cinergi@sdsc.edu
Metadata language
eng
Metadata character set encoding:
utf8
Metadata standard for this record:
ISO 19139 Geographic Information - Metadata - Implementation Specification
standard version:
2007
Metadata record identifier:
urn:dciso:metadataabout:ac4039aa-65fa-400a-bbf7-0dbbfb464fa8
Metadata record format is ISO19139 XML (MD_Metadata)