Estimating Ground Elevation and Vegetation Characteristics in Coastal Salt Marshes Using UAV-Based LiDAR and Digital Aerial Photogrammetry

This study evaluates the skills of two types of drone-based point clouds, derived from LiDAR and photogrammetric techniques, in estimating ground elevation, vegetation height, and vegetation density on a highly vegetated salt marsh. The proposed formulation is calibrated and tested using data measured on a Spartina alterniflora-dominated salt marsh in Little Sapelo Island, USA. The method produces high-resolution (ground sampling distance = 0.40 m) maps of ground elevation and vegetation characteristics and captures the large gradients in the proximity of tidal creeks. Our results show that LiDAR-based techniques provide more accurate reconstructions of marsh vegetation (height: MAE(VH) = 12.6 cm and RMSEVH = 17.5 cm; density: MAE(VD) = 6.9 stems m(-2) and RMSEVD = 9.4 stems m(-2)) and morphology (MAE(M) = 4.2 cm; RMSEM = 5.9 cm) than Digital Aerial Photogrammetry (DAP) (MAE(VH) = 31.1 cm; RMSEVH = 38.1 cm; MAE(VD) = 12.7 stems m(-2); RMSEVD = 16.6 stems m(-2); MAE(M) = 11.3 cm; RMSEM = 17.2 cm). The accuracy of the classification procedure for vegetation calculation negligibly improves when RGB images are used as input parameters together with the LiDAR-UAV point cloud (MAE(VH) = 6.9 cm; RMSEVH = 9.4 cm; MAE(VD) = 10.0 stems m(-2); RMSEVD = 14.0 stems m(-2)). However, it improves when used together with the DAP-UAV point cloud (MAE(VH) = 21.7 cm; RMSEVH = 25.8 cm; MAE(VD) = 15.2 stems m(-2); RMSEVD = 18.7 stems m(-2)). Thus, we discourage using DAP-UAV-derived point clouds for high-resolution vegetation mapping of coastal areas, if not coupled with other data sources.

Automated summary

This study evaluates the skills of two types of drone-based point clouds, derived from LiDAR and photogrammetric techniques, in estimating ground elevation and vegetation characteristics on a salt marsh. Results show that LiDAR-based techniques provide more accurate reconstructions compared to Digital Aerial Photogrammetry (DAP). The classification procedure for vegetation calculation negligibly improves when RGB images are used as input parameters with the LiDAR-UAV point cloud.