Terrestrial Laser Scanning Data of the ROV (Remote Operated Vehicle) area on the MOSAiC (Multidisciplinary Drifting Observatory for the Study of Arctic Climate) Expedition on February 22, 2020

• Main Authors: Clemens-Sewall, David, Polashenski, Chris, Raphael, Ian
• Format: Dataset
• Language: English
• Published: NSF Arctic Data Center 2021
• Subjects: Snow; Wind; LiDAR; Arctic; Arctic Ocean; Sewall; Sea ice
• Online Access: https://dx.doi.org/10.18739/a2jh3d38m; https://arcticdata.io/catalog/view/doi:10.18739/A2JH3D38M

These Terrestrial Laser Scanning (TLS) data were collected on February 22, 2020 at the Multidisciplinary Drifting Observatory for Arctic Climate (MOSAiC) Expedition. The MOSAiC Expedition continuously made in-situ measurements on a collection of drifting sea ice floes In the Arctic Ocean from October 2019 to May 2020. TLS, also known as Terrestrial Light Detection and Ranging (LiDAR), is an active remote sensing modality in which a tripod-mounted, rotating laser emitter and detector (the TLS sensor) scans the surroundings emitting pulses of light and tracking the time it takes for a pulse to return. From the time of flight and the orientation of each pulse, the sensor creates a point cloud of the surroundings. These point clouds have been written out as LAS 1.4 files. This dataset consists of nine point clouds collected from scan positions in the vicinity of the Remote Operated Vehicle (ROV) tent on February 22, 2020. This dataset contains 9 Terrestrial Laser Scans (TLS) of snow and sea ice on the MOSAiC Expedition. There were moderate blowing snow conditions on the day these data were collected. These data are used by Clemens-Sewall et al. 2021 to demonstrate the efficacy of FlakeOut, a filter designed to remove wind-blown snowflakes from TLS data. They were collected by Ian Raphael and processed by David Clemens-Sewall. These data are provided in a directory structure such that they can be processed and analyzed by FlakeOut (Clemens-Sewall 2021: https://github.com/davidclemenssewall/flake_out/tree/v1.0.0 or https://zenodo.org/record/5657286#.YZRRcLtOlH4). To download these data in this directory structure, please press 'Download All'.