Comparing Drone-Derived Elevation Data with Air-Borne LiDAR to Analyze Coastal Sea Level Rise at the Local Level

Abstract Sea level rise is a coastal hazard leading to erosion, flooding, and habitat destruction among other effects. Geoinformatics plays a vital role in providing tools to assess coastal vulnerability. Recent improvements in drone technology offer new opportunities for collecting data. Calibrating drone elevation data to local sea-levels is a current challenge. This research compares the use of drone-derived digital elevation models (DEMs) created from a DJI Phantom 4 Pro drone with airborne LiDAR data to analyze sea-level rise in Essex, Massachusetts. To evaluate the best method of calibrating drone elevation data to the local environment, three different Ground Control Point (GCP) methods were evaluated: surveyed GCPs, LiDAR-derived GCPs, and the NAVD88 sea-level (0-value) of the LiDAR data. The three drone-derived DEMs were compared with a LiDAR DEM through two methods: 1) comparing how well the DEMs measured the elevation of surveyed GCPs, and 2) how well the DEMs modeled five different scenarios of sea level rise compared with a LiDAR DEM. Results showed that two of the calibration methods performed well; the surveyed GCP derived drone DEM and the LiDAR NAVD88 sea-level (0-value) derived drone DEM.