No Substitute for Going to the Field: Correcting Lidar DEMs in Salt Marshes

Models that forecast the response of salt marshes to current and future trends in sea level rise increasingly are used to guide management of these vulnerable ecosystems. Lidar-derived DEMs serve as the foundation for modeling landform change. However, caution is advised when using these DEMs as the starting point for models of salt marsh evolution. While broad vegetation class (i.e., young forest, old forest, grasslands, desert, etc.) has proven to be a significant predictor of vertical displacement error in terrestrial environments, differentiating error among different species or community types within the same ecosystem has received less attention. Salt marshes are dominated by monocultures of grass species and thus are an ideal environment to examine the within-species effect on lidar DEM error. We analyzed error of lidar DEMs using elevations from real-time kinematic (RTK) surveys in saltmarshes in multiple national parks and wildlife refuge areas from the mouth of the Chesapeake Bay to Massachusetts. Error of the lidar DEMs was sometimes large, on the order of 0.25 m, and varied significantly between sites because vegetation cover varies seasonally and lidar data was not always collected in the same season for each park. Vegetation cover and composition were used to explain differences between RTK elevations and lidar DEMs. This research underscores the importance of collecting RTK elevation data and vegetation cover data coincident with lidar data to produce correction factors specific to individual salt marsh sites.