Bias-corrected topobathymetric elevation model for south Florida, 2018

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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  "010:12"
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  "geospatial"
]