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The impact of lidar elevation uncertainty on mapping intertidal habitats on barrier islands


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Enwright, N.M., Wang, L., Borchert, S.M., Day, R.H., Feher, L.C., and Osland, M.J., 2017, The impact of lidar elevation uncertainty on mapping intertidal habitats on barrier islands: U.S. Geological Survey data release,


These data represent low-lying lands and intertidal lands on Dauphin Island, Alabama, USA for January 2015. These data were delineated using airborne lidar elevation data, in situ elevation observations, lidar metadata, and tide gauge information. We applied Monte Carlo simulations to incorporate uncertainty into a digital elevation model and produce probabilistic outputs with regards to elevation relative to tide and water levels. Specifically, these include three error treatments, including leaving error untreated, and treating error via simulating the propagation of error using Monte Carlo simulations with error and bias estimates from the lidar metadata and site-specific Real-time Kinematic Global Position System data, respectively. [...]


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Barrier islands are dynamic ecosystems due to their position at the land-sea interface. Storms, waves, tides, currents, and relative sea-level rise are powerful forces that shape barrier island morphology and regulate habitats (e.g., beach, dune, marsh, tidal flat, and forest). High-resolution digital elevation models generated from airborne lidar are often used for assessing island morphology, extracting shorelines, and mapping habitats. While airborne lidar data have revolutionized the spatial scale for which elevations can be realized, data limitations are often magnified in coastal settings. Researchers have found airborne lidar can have a vertical error as high as 60 centimeters in densely vegetated marsh. The uncertainty of digital elevation models is often left unaddressed; however, in low-relief environments centimeters can make a difference in the exposure to physically demanding abiotic conditions (e.g., inundation, salt spray, wave energy). Thus, there is a need to develop straightforward techniques that address this uncertainty in digital elevation models used for coastal ecosystem monitoring and research. Monte Carlo simulations have been used by researchers as an efficient approach to delineating the land-sea interface while also incorporating vertical uncertainty. This dataset builds on these efforts through a comparative study of the delineation of low-lying lands and intertidal lands for three different error treatments in addition to showing how minor adjustments to error or bias values can affect results.

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DOI doi:10.5066/F7125RVT

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