Bias-Corrected Topobathymetric Elevation Model for South Florida, 2018
Dates
Publication Date
2023-03-31
Start Date
2007
End Date
2018
Citation
Buffington, K.J., and Thorne, K.M., 2023, Bias-corrected topobathymetric elevation model for south Florida, 2018: U.S. Geological Survey data release, https://doi.org/10.5066/P9KV6FMQ.
Summary
Accurate elevation data in coastal ecosystems are crucial for understanding vulnerability to sea-level rise. Lidar has become increasingly available; however, in tidal wetlands such as mangroves and salt marsh, vertical bias from dense vegetation reduces accuracy of the delivered 'base earth' products. To increase accuracy of elevation models across south Florida, we applied the LEAN technique to six different lidar collections from 2007-2018. On average, LEAN correction increased DEM accuracy by 46.1 percent, reducing the vertical bias. After correction and post-processing, the DEMs were merged together with a bathymetric dataset to create a seamless topobathy product.
Summary
Accurate elevation data in coastal ecosystems are crucial for understanding vulnerability to sea-level rise. Lidar has become increasingly available; however, in tidal wetlands such as mangroves and salt marsh, vertical bias from dense vegetation reduces accuracy of the delivered 'base earth' products. To increase accuracy of elevation models across south Florida, we applied the LEAN technique to six different lidar collections from 2007-2018. On average, LEAN correction increased DEM accuracy by 46.1 percent, reducing the vertical bias. After correction and post-processing, the DEMs were merged together with a bathymetric dataset to create a seamless topobathy product.
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Purpose
The bias-corrected elevation model can be used to estimate current flooding risk and help understand vulnerability to future sea-level rise.
