US Migrating
type: Agent

30 meter Esri binary grids 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)
type: Dataset
contact point: Organization
  fn: E. Robert Thieler
keyword: national
keyword: virginia
keyword: usgs
keyword: u-s-geological-survey
keyword: boston
keyword: coastal-and-marine-geology-program
keyword: landscape-change
keyword: bayesian-network
keyword: gridded-raster-dataset
keyword: atlantic-city
keyword: geoscientificinformation
keyword: atlantic-ocean
keyword: new-hampshire
keyword: whcmsc
keyword: ckan
keyword: biota
keyword: cmgp
keyword: jersey-shore
keyword: long-island
keyword: chesapeake-bay
keyword: imagerybasemapsearthcover
keyword: probabilistic-predictions
keyword: geospatial-datasets
keyword: maryland
keyword: united-states
keyword: new-jersey
keyword: new-york
keyword: sea-level-rise
keyword: mathematical-modeling
keyword: oceans
keyword: woods-hole-coastal-and-marine-science-center
keyword: environment
keyword: geoss
keyword: connecticut
keyword: geo
keyword: elevation
keyword: norfolk
keyword: new-england
keyword: massachusetts
keyword: north-america
keyword: amerigeoss
keyword: amerigeo
keyword: delaware
keyword: maine
keyword: esri-binary-grid
keyword: ocean-city
keyword: topography
theme: {geospatial}
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.
issued: 2025-11-21T08:30:42.342682
modified: 20211116
spatial: Location

Original Metadata
type: Distribution
access URL: https://data.usgs.gov/datacatalog/metadata/USGS.c530800a-b9cf-4303-95af-2204008bd63a.xml
media type: text/xml
description: The metadata original format
format: XML
issued: 2022-07-28T20:19:49.714342
modified: 2025-11-21T08:30:42.319282

Digital Data
type: Distribution
access URL: https://doi.org/10.5066/F73J3B0B
media type: application/http
description: Landing page for access to the data
format: XML
issued: 2022-07-28T20:19:49.714349
modified: 2025-11-21T08:30:42.319695