Skip to main content

Corrected digital elevation model in coastal wetlands in Nassau and Duval Counties, Florida, 2018

Dates

Publication Date
Start Date
2018-11-28
End Date
2018-12-18

Citation

McHenry, C.E., Enwright, N.M., Vervaeke, W.C., Thurman, H.R., Patton, B.A., Stoker, J.M., Osland, M.J., Day, R.H., Anderson, G.H., Passeri, D.L., and Simons, B.M., 2023, Corrected digital elevation model in coastal wetlands in Nassau and Duval Counties, Florida, 2018: U.S. Geological Survey data release, https://doi.org/10.5066/P941Z77K.

Summary

High-resolution elevation data provide a foundational layer needed to understand regional hydrology and ecology under contemporary and future-predicted conditions with accelerated sea-level rise. While the development of digital elevation models (DEMs) from light detection and ranging data has enhanced the ability to observe elevation in coastal zones, the elevation error can be substantial in densely vegetated coastal wetlands. In response, we developed a machine learning model to reduce vertical error in coastal wetlands for a 1-m DEM from 2018 that covered Nassau and Duval Counties, Florida. Error was reduced by using a random forest regression model within situ observations and predictor variables from optical and radar-based satellite [...]

Contacts

Attached Files

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

13.81 GB image/tiff
Final_SingleModel_CorrectedDEM_Mosaic_01112023.tfw 90 Bytes text/plain

Purpose

Sea-level rise is expected to transform habitats across the entire coastal zone including upslope habitats such as forested wetlands, freshwater marshes, and upland forests and grasslands. Natural resource managers require information on how these important coastal ecosystems change over time to assist with future-focused land management and decision-making. Periodically produced DEMs provide high-resolution elevation data that can be used to monitor coastal zone changes. However, elevation bias is typically unknown in wetlands, and can be substantial. Therefore, it is important to correct DEMs in densely vegetated areas. The objective of this effort is to reduce the elevation error of the DEM in coastal wetlands in and around the National Park Service’s Timucuan Ecological and Historic Preserve in northeastern Florida using a random forest regression model. This project was funded by the USGS Natural Resources Preservation Program. This product will be used to approximate the probability of inundation in and around the Timucuan Ecological and Historic Preserve under several contemporary high tide flooding and sea-level rise scenarios. Additionally, this product will be used to assess the potential transformation of coastal wetlands under various sea-level rise scenarios. In the future, the model used to create this product could be used to reduce the elevation error of the DEM in coastal wetlands in and around other coastal parks and preserves with similar wetland types.

Additional Information

Identifiers

Type Scheme Key
DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/P941Z77K

Item Actions

View Item as ...

Save Item as ...

View Item...