Skip to main content
USGS - science for a changing world

Using relative topography and elevation uncertainty to delineate dune habitat on barrier islands

Dates

Publication Date
Start Date
2014-01-12
End Date
2015-02-13

Citation

Enwright, N.M., Wang, L., Borchert, S.M., Day, R.H., Feher, L.C., and Osland, M.J., 2019, Using relative topography and elevation uncertainty to delineate dune habitat on barrier islands: U.S. Geological Survey data release, https://doi.org/10.5066/P9S25ZKX.

Summary

Dunes with a high relative topography can often be easily distinguished in high-resolution lidar-based digital elevation models (DEMs). Thus, researchers have begun using relative topography metrics, such as the topographic position index (TPI; Weiss, 2001), to identify ridges and upper slopes for extracting dunes from lidar-based DEMs (Wernette et al., 2016; Halls et al. 2018). DEMs are often used for automated delineations of intertidal and supratidal habitats in coastal applications despite issues related to vertical uncertainty. However, the level of vertical uncertainty from data collected with conventional aerial topographic lidar systems has been found to be as high as 60 cm in densely vegetated emergent wetlands throughout [...]

Contacts

Attached Files

Click on title to download individual files attached to this item.

dune_delineation_uncertainty_tpi.zip 15.05 MB
dune_delineation_overview_metadata.xml
Original FGDC Metadata

View
24.61 KB

Purpose

Barrier islands are dynamic ecosystems due to their position at the land-sea interface. Landscape position, such as elevation and distance from shore, influences habitat coverage on barrier islands by regulating exposure to harsh abiotic factors, including waves, tides, and salt spray. Geographers often use topographic data to extract landscape position information for research on barrier islands and beach-dune environments. When possible, researchers should consider lidar elevation uncertainty, especially when using automated processes for extracting elevation-dependent habitats from lidar data in low-relief coastal settings. The approach used to develop this dataset builds on recent efforts using relative topography for dune delineation (Wernette et al. 2016; Halls et al. 2018) and using Monte Carlo simulations to treat elevation uncertainty in coastal settings when extracting elevation-dependent habitats from a digital elevation model (Liu et al. 2007; Enwright et al. 2018). Collectively, these methods can be integrated into a framework for delineating geomorphology-based barrier island habitats to increase both efficiency and repeatability (Enwright et al. 2017). This data release and approach should interest scientists concerned with monitoring and forecasting habitats in dynamic coastal environments, especially elevation-dependent habitats.

Additional Information

Identifiers

Type Scheme Key
DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/P9S25ZKX

Item Actions

View Item as ...

Save Item as ...

View Item...