One Tree Reef topographic and bathymetric LiDAR digital elevation model (2018) and roughness equivalent habitat data (2023)

A high-resolution LiDAR digital elevation model was developed to investigate the geomorphic features and surface roughness of a coral reef in the Southern Great Barrier (One Tree Reef). Given that there are few data sets of equivalent resolution the focus of this research was to detail the change in surface roughness expression over multiple spatial scales. Data were collected 8 October 2018 using a Riegl VQ-820-G topo-bathymetric LiDAR combined with a Riegl Q680i-S topographic scanner and a Canon EOS 5Dmk4 DSLR on a small research aircraft (Diamond Aircraft ECO-Dimona). The whole One Tree Reef area was covered twice using two different pulse rate settings for the VQ-820-G, viz. 284kHz and 522kHz. This measurement strategy ensured maximum spatial resolution (at 522kHz) and maximum depth penetration (at 284kHz). All LiDAR data was processed to a 0.25 m cell-size DEM using a combination of Riegl proprietary software, ARA-developed software, the RAPIDLASSO LAStools utilities, Bayesmap's StripAlign™ utility and Global Mapper V 20. Processing included human-machine interactive selection and confirmation of valid bathymetric points. The imagery from the DSLR was mosaiced at 0.14 m cell size using the AgiSoft PhotoScan© (now Metashape) Software package and overlaid onto the LiDAR point cloud. The relative error of the LiDAR point cloud was ± 0.1 m. Two methods of characterising surface roughness were applied to the LiDAR DEM: the vector ruggedness measure (VRM) and the Multiscale Roughness (MR) tool from WhiteBox Tools. The VRM was applied over filter radii of 8, 20, 100 and 400 cells. The MR approach was conducted between filter radii of 1 – 1500 cells (≈ 0.5 to 750 m) with step intervals of 1. MR analysis revealed the roughness signatures of the geomorphic coral reef zones defined by Roelfsema et al. (2018, doi:10.1016/j.rse.2018.02.005). Geomorphic zones with similar roughness signatures were combined to produce roughness equivalent habitats. Roughness equivalent habitats are regions with similar roughness signature that do not necessarily form geographical contiguous areas. Data contained in this repository are: 1. The LiDAR DEM as a geotiff; 2. Roughness magnitude and scale geotiffs computed using the MultiscaleRoughness tool from Whitebox Tools and 3. The ESRI shapefiles for the roughness equivalent habitats. Further details of the results and analysis of the LiDAR DEM can be found in Harris et al. (2023, doi:/10.1016/j.geomorph.2023.108852).