Point clouds with ground point classification and individual tree segmentation of 25 northern boreal forest and tundra sites from UAV-based lidar surveys in northwestern Canada in 2022

This dataset represents LiDAR 3D point clouds with centimetre accuracy. It is a collection of processed point clouds that were collected by a UAV-based laser scanner (YellowScan Mapper). The region covered is part of the Northern Boreal Forest and the Tundra-Taiga Ecotone (TTE). The aim is to map the forest structure and in particular to segment individual trees. This allows structural and biophysical information to be derived on forest condition, structure, topography, morphology, disturbance (wildfire, thaw slumps, wind events), thermokarst lakeshore interfaces, etc. The fieldwork was planned and carried out by researchers from the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI). It took place in the peak summer of 2022, from 10 July to 19 August. The study area covers a long bio-climatic gradient from the northern tundra and open forested areas around Inuvik, Northwest Territories, Canada, through the southern Yukon Territory and mountainous terrain across the Mackenzie Mountains and southern Cassiar Mountains, to areas near Fort Nelson, British Columbia, Canada. At 26 sites, we pre-selected locations based on satellite data. At each site, transects at least 50 m wide and 500 m long were flown in a grid of parallel flight lines 20 m apart. At the ground level, one or, in rare cases, multiple 30-metre-diameter plots were inventoried as ground reference data. The recordings were made at an altitude of 70 m above ground liftoff at a speed of 5 m/s, as recommended by the manufacturer. Before each flight, a GPS base station was set up to collect data for later geographic correction. The raw data processing steps involved correcting the flight trajectories in POSPac PP-RTX , flight strip alignment in software YellowScan CloudStation, and colorization with RGB module picture data. The subsequent processing and metadata collection in PC2RCHIVE includes (i) ground classification, (ii) creating Digital Terrain Model (DTM), Digital Surface Model (DSM) and Canopy Height Model (CHM), (iii) tree segmentation, (iv) generating maps and (v) user provided metadata and relevant information from the data processing are summarized in tables. The processing of the resulting point clouds followed methods developed in PC2RCHIVE, a tool to easily standardise the point cloud data products and their metadata.