Advancing barrier island habitat mapping through the treatment of elevation uncertainty and morphology

Authors: Nicholas M. Enwright*, U.S. Geological Survey, Wetland and Aquatic Research Center, Lei Wang, Louisiana State University, Department of Geography and Anthropology , Sinéad M. Borchert, Cherokee Nations Technology Solution, LLC at U.S. Geological Survey, Wetland Aquatic Research Center, Richard H. Day, U.S. Geological Survey, Wetland and Aquatic Research Center, Laura C. Feher, U.S. Geological Survey, Wetland and Aquatic Research Center, Michael J. Osland, U.S. Geological Survey, Wetland and Aquatic Research Center, Hongqing Wang, U.S. Geological Survey, Wetland and Aquatic Research Center
Topics: Remote Sensing, Coastal and Marine, Land Use and Land Cover Change
Keywords: barrier islands, habitat mapping, remote sensing, lidar, error propagation, coastal wetlands, object based image analysis
Session Type: Paper
Day: 4/12/2018
Start / End Time: 5:20 PM / 7:00 PM
Room: Bonaparte, Marriott, River Tower Elevators, 4th Floor
Presentation File: No File Uploaded


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 (for example, 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 accuracy with a root mean square 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, such as barrier islands, centimeters can affect exposure to physically-demanding abiotic conditions.


In this study, we used a semi-automated approach using object based image analysis coupled with a lidar-based digital elevation model, in-situ data, tide gauge data, and high-resolution orthophotography to map barrier island habitats on Dauphin Island, Alabama for the fall of 2015. We applied Monte Carlo simulations to propagate the uncertainty of the digital elevation model and produce probabilistic outputs with regards to height relative to tide and water levels. Here, we show how these data can enhance the results and increase the efficiency of delineating intertidal and supratidal habitats. The methodology and results of this effort should interest researchers that use lidar data to map coastal habitats or use lidar data in coastal studies.

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