Journal
REMOTE SENSING OF ENVIRONMENT
Volume 186, Issue -, Pages 616-625Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2016.09.020
Keywords
RTK-GPS surveys; Accuracy; LEAN; Normalized Difference Vegetation Index (NDVI); Sea-level rise
Funding
- DOI U.S. Geological Survey
- National Oceanic and Atmospheric Administration EESLR program [NA15NOS4780171]
- Northwest Climate Science Center (NWCSC) [1434-03HQRU1584]
- U.S. Fish & Wildlife Service North Pacific [F11RG0048]
- California Landscape Conservation Cooperatives [80250-A-H100]
- Oregon State University
- NWCSC fellowship [G10AC00702]
- Western Ecological Research Center
- National Climate Change and Wildlife Science Center
- Southwest Climate Science Center
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Airborne light detection and ranging (lidar) is a valuable tool for collecting large amounts of elevation data across large areas; however, the limited ability to penetrate dense vegetation with lidar hinders its usefulness for measuring tidal marsh platforms. Methods to correct lidar elevation data are available, but a reliable method that requires limited field work and maintains spatial resolution is lacking. We present a novel method, the Lidar Elevation Adjustment with NDVI (LEAN), to correct lidar digital elevation models (DEMs) with vegetation indices from readily available multispectral airborne imagery (NAIP) and RTK-GPS surveys. Using 17 study sites along the Pacific coast of the U.S., we achieved an average root mean squared error (RMSE) of 0.072 m, with a 40-75% improvement in accuracy from the lidar bare earth DEM. Results from our method compared favorably with results from three other methods (minimum-bin gridding, mean error correction, and vegetation correction factors), and a power analysis applying our extensive RTK-GPS dataset showed that on average 118 points were necessary to calibrate a site -specific correction model for tidal marshes along the Pacific coast. By using available imagery and with minimal field surveys, we showed that lidar-derived DEMs can be adjusted for greater accuracy while maintaining high (1 m) resolution. Published by Elsevier Inc.
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