Assessment of Elevation Uncertainty in Salt Marsh Environments using Discrete-Return and Full-Waveform Lidar

Lidar data can serve as an important source of elevation information for studying, monitoring and managing salt marshes. However, previous studies have shown that lidar data tend to have greater vertical uncertainty in salt marshes than in other environments, hindering the ability to resolve small elevation differences that can be ecologically significant in marshes. For coastal scientists and managers to effectively collect, evaluate, and/or use lidar data in salt marshes, factors affecting elevation uncertainty (e.g., plant species, season, and lidar processing methods) must be well understood. This study addresses this need using discrete-return (DRL) and full-waveform lidar, along with field-surveyed reference data, for four marshes on Cape Cod, Massachusetts (USA). The lidar bias and standard deviation were computed across all four marsh systems and four major taxa using varying interpolation and filtering methods. The effects of seasonality were also investigated using lidar data acquired in the summer and the following spring. Relative uncertainty surfaces (RUS) were computed from lidar waveform-derived metrics and examined for their utility and correlation with individual lidar errors. The results clearly illustrate the importance of seasonality, species, and lidar interpolation and filtering methods on elevation uncertainty in salt marshes. Results also demonstrate that RUS generated from lidar waveform features are useful in qualitative assessments of lidar elevation uncertainty and correlate well with vegetation height (r = 0.85; n = 268). Knowledge of where DRL uncertainty persists within salt marshes and the factors influencing the higher uncertainty should facilitate the development of better correction methods