US Migrating
type: Agent

Original Metadata
type: Distribution
access URL: https://data.usgs.gov/datacatalog/metadata/USGS.5d0bc8dce4b0941bde4fc5a2.xml
media type: text/xml
description: The metadata original format
format: XML
issued: 2022-07-28T19:22:20.993792
modified: 2025-11-21T10:03:16.882989

Digital Data
type: Distribution
access URL: https://doi.org/10.5066/P944FPA4
media type: application/http
description: Landing page for access to the data
format: XML
issued: 2022-07-28T19:22:20.993803
modified: 2025-11-21T10:03:16.883416

DisOcean: Distance to the ocean: Cedar Island, VA, 2012
type: Dataset
contact point: Organization
  fn: Sara L. Zeigler
keyword: cmgp
keyword: usgs-5d0bc8dce4b0941bde4fc5a2
keyword: virginia
keyword: delmarva-peninsula
keyword: cedar-island
keyword: st-petersburg-coastal-and-marine-science-center
keyword: coastal-and-marine-geology-program
keyword: national
keyword: usgs
keyword: geomorphology
keyword: virginia-coast-reserve
keyword: u-s-geological-survey
keyword: oceans
keyword: barrier-island
keyword: mhw
keyword: environment
keyword: north-america
keyword: geospatial-datasets
keyword: geoss
keyword: united-states
keyword: amerigeoss
keyword: geospatial-analysis
keyword: usa
keyword: atlantic-ocean
keyword: geographic-information-systems
keyword: geo
keyword: va
keyword: amerigeo
keyword: coastal-habitat
keyword: ckan
keyword: gis
keyword: mean-high-water
keyword: woods-hole-coastal-and-marine-science-center
theme: {geospatial}
description: 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 into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.
issued: 2025-11-21T10:03:16.899797
modified: 20200810
spatial: Location