Aeolian dune modelling from airborne LiDAR, terrestrial LiDAR and Structure from Motion-Multi View Stereo

Abstract

In this work, we present an analysis of dune migration and volume change of the Garopaba dune field, southern Brazil, based on data from Airborne LiDAR (ALS -surveyed in 2010) and Structure from Motion-Multi View Stereo (SfM-MVS -surveyed in 2019). The accuracy of the SfM-MVS reconstruction was validated by a comparison between Terrestrial LiDAR (TLS) and SfM-MVS Digital Elevation Models (DEMs). Elevation differences of 2 000 random points resulted in RMSE of 0.16 m and MAE of 0.13 m, with SfM-MVS elevations slightly higher than the TLS ones. Although sand dunes are commonly regarded as a challenge to traditional photogrammetry due their homogeneous texture and spectral response, in this research image matching was successful in all areas of the survey due the presence of superficial features (footprints and sandboard tracks) and visibility of the sedimentary stratification, highlighted by heavy minerals. Displacement of dune crest lines from the ALS and SfM-MVS DEMs resulted in a migration rate of ≈5 m/year between 2010 and 2019, in good agreement with rates derived from satellite images and historical aerial photographs of the same area. Sand volume change in the same period showed an increase of only 0.5%, which can be related to the installation of sand fences to promote dune stabilization and sand removal from the front of the dune field to keep a road open to vehicles. ALS can cover large areas in little time but its high cost still remains a barrier to wider usage, especially by researchers in developing countries. TLS has an intermediate cost but demands more fieldwork and more processing time. In our case we needed three days for the TLS survey and around three weeks to produce a DEM of ≈80 400m 2 . On the other hand, we were able to cover ≈740 900m 2 with six flight missions in under three hours, with ≈13 hours processing time in a medium-range workstation. This makes SfM-MVS a low-cost solution with fast and reliable results for 3D modelling and continuous monitoring of coastal dunes.