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Bias-Corrected Topobathymetric Elevation Model for South Florida, 2018


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Buffington, K.J., and Thorne, K.M., 2023, Bias-corrected topobathymetric elevation model for south Florida, 2018: U.S. Geological Survey data release,


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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Questions pertaining to the intended use of, or assistance with understanding limitations or interpretation of these data are to be directed to the individuals/organization listed in the Point of Contact section. Unless otherwise stated, all data, metadata, and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.


The bias-corrected elevation model can be used to estimate current flooding risk and help understand vulnerability to future sea-level rise.



  • National and Regional Climate Adaptation Science Centers
  • Southeast CASC
  • USGS Data Release Products
  • USGS Western Ecological Research Center



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DOI doi:10.5066/P9KV6FMQ

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