US Migrating
type: Agent

Digital Data
type: Distribution
access URL: https://doi.org/10.5066/P9V7F6UX
media type: application/http
description: Landing page for access to the data
format: XML
issued: 2022-07-28T20:05:50.895601
modified: 2025-11-22T19:01:12.893995

ElevMHW: Elevation adjusted to local mean high water: Myrtle Island, VA, 2014
type: Dataset
contact point: Organization
  fn: Sara L. Zeigler
keyword: virginia-coast-reserve
keyword: geomorphology
keyword: usgs
keyword: u-s-geological-survey
keyword: lidar
keyword: geographic-information-systems
keyword: united-states
keyword: mhw
keyword: geospatial-analysis
keyword: coastal-habitat
keyword: geo
keyword: elevation
keyword: mean-high-water
keyword: usa
keyword: atlantic-ocean
keyword: ckan
keyword: digital-elevation-models
keyword: delmarva-peninsula
keyword: topography
keyword: national
keyword: barrier-island
keyword: virginia
keyword: gis
keyword: myrtle-island
keyword: geospatial-datasets
keyword: oceans
keyword: woods-hole-coastal-and-marine-science-center
keyword: st-petersburg-coastal-and-marine-science-center
keyword: geoss
keyword: usgs-5daa37d5e4b09fd3b0c9cee4
keyword: va
keyword: north-america
keyword: amerigeoss
keyword: cmhrp
keyword: amerigeo
keyword: coastal-and-marine-hazards-and-resources-program
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: 2025-11-22T19:01:12.913778
modified: 20200810
spatial: Location

Original Metadata
type: Distribution
access URL: https://data.usgs.gov/datacatalog/metadata/USGS.5daa37d5e4b09fd3b0c9cee4.xml
media type: text/xml
description: The metadata original format
format: XML
issued: 2022-07-28T20:05:50.895590
modified: 2025-11-22T19:01:12.893581