Salt marshes are important habitat for many estuarine species, including juvenile anadromous fish. They are also vulnerable to impacts from sea level rise. Changes in the depth and duration of inundation are of particular concern when predicting the potential effects of sea level rise on salt marshes, as inundation and hydrologic changes can influence vegetation, decomposition, and sedimentation rates. Remotely sensed data such as LIDAR have been used to map the marsh surface elevation and could help track changes over time. However, for imagery collected over tidally-inundated areas, dense vegetation and deep water can interfere with the accuracy of these data. In order to assess the accuracy of LIDAR collected in 2008, vegetation and elevation data were collected along transects at 52 sites across the Coos Bay Estuary in Oregon. The percent cover and height of all vascular plant species present were recorded for 1 m2 plots along transects from the bayside edge of the marsh to the upland. Plot location and elevation were determined at 1 m intervals along the transects with a Trimble Pathfinder Pro XRS differential GPS and TOPCON GTS223 TOTAL station. Post-processing of GPS points allowed for direct comparison of field measured and LIDAR-derived elevations.
Ordination of the vegetation data revealed associations that were consistent across sites. Stands of Distichlis spicata (saltgrass) and Sarcocornia perennis (swampfire) about 22-31 cm in height were characteristic of communities nearest the water’s edge, whereas Grindelia stricta var. stricta (Oregon gumweed) and Argentina egedii (Pacific silverweed) about 43 cm tall were most common in the high marsh. Extensive areas of Carex lyngbyei (Lyngbye’s sedge) averaging 64 cm in height, occurred in mid-marsh elevations. Comparison of the slope of the LIDAR surface elevation to the corresponding transect slope calculated from the field surveys revealed distinct patterns. While there was agreement along many of the transects between LIDAR-based and surveyed elevation data, for a number of sites, the slope and elevation of the marsh surface differed between survey data and LIDAR. Some areas of disagreement were marsh areas that had been inundated by high tide when the LIDAR survey was flown. In other areas, dense swaths of C. lyngbyei prevented the LIDAR from penetrating to ground surface through the vegetation. The combined vegetation and survey data collected along these transects result in a topology of error that can help estimate accuracy and identify areas where early LIDAR data elevations require correction.