Removal of Positive Elevation Bias of Digital Elevation Models for Sea-Level Rise Planning

Elizabeth Burke Watson, LeeAnn Haaf, Kirk Raper and Erin Reilly
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Elizabeth Burke Watson: Department of Biodiversity, Earth & Environmental Sciences and the Academy of Natural Sciences, Drexel University, Philadelphia, PA 19103, USA
LeeAnn Haaf: Partnership for the Delaware Estuary, Wilmington, DE 19801, USA
Kirk Raper: Academy of Natural Sciences, Drexel University, Philadelphia, PA 19103, USA
Erin Reilly: The Barnegat Bay Partnership, Toms River, NJ 08754, USA

Data, 2019, vol. 4, issue 1, 1-6

Abstract: Digital elevation models (DEMs) based on LiDAR surveys provide critical information for predicting the vulnerability of coastal areas to sea-level rises. Due to the poor penetration of LiDAR pulses in marsh vegetation, bare-earth DEMs for coastal wetlands are often subject to positive elevation bias, and thus underestimate vulnerability. This data publication includes comprehensive elevation surveys from seven coastal wetlands in coastal New Jersey, and an evaluation of the accuracy and positive elevation bias of each publically available DEM. Resampling the DEMs at a coarser resolution, replacing cell values using the minimum value in a wider search window (4 m), removed this positive elevation bias with no loss of accuracy.

Keywords: LiDAR; post-processing; coastal marsh; signed error (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2019
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