Abstract
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: MAEVH = 12.6 cm and RMSEVH = 17.5 cm; density: MAEVD = 6.9 stems m−2 and RMSEVD = 9.4 stems m−2) and morphology (MAEM = 4.2 cm; RMSEM = 5.9 cm) than Digital Aerial Photogrammetry (DAP) (MAEVH = 31.1 cm; RMSEVH = 38.1 cm; MAEVD = 12.7 stems m−2; RMSEVD = 16.6 stems m−2; MAEM = 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 (MAEVH = 6.9 cm; RMSEVH = 9.4 cm; MAEVD = 10.0 stems m−2; RMSEVD = 14.0 stems m−2). However, it improves when used together with the DAP-UAV point cloud (MAEVH = 21.7 cm; RMSEVH = 25.8 cm; MAEVD = 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.
Highlights
Salt marshes are essential environments that provide ecological and anthropologic functions, such as storm attenuation [1,2], carbon sequestration, and water quality enhancement [3,4,5,6]
To test the Light Detection and Ranging (LiDAR)-Unmanned Aerial Vehicle (UAV) point cloud accuracy, we identified the geographic coordinates (X, Y, and Z) of the Ground Control Points (GCPs) centroids, and we compared them with the values surveyed in the field using the RTK-GPS
The method proposed by Pinton et al (2020) [23] was used to calculate ground elevation from transformed LiDAR- and Digital Aerial Photogrammetry (DAP)-UAV point clouds
Summary
Salt marshes are essential environments that provide ecological and anthropologic functions, such as storm attenuation [1,2], carbon sequestration, and water quality enhancement [3,4,5,6]. Coastal marsh systems suffered a progressive conversion to open water areas and mudflats due to sea-level rise (SLR), climate change, and anthropogenic impact [4,7,8,9,10]. The reduction in salt marsh extent limits the ecosystem functions, endangering human communities living in coastal areas. In the US alone, coastal communities represent ~30% of the total population [13]. Monitoring marsh morphology and vegetation can provide insight into the response of Remote Sens.
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