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Kruse, Stefan; Gloy, Josias; Farkas, Luca; Schladebach, Jacob; Hao, Kunyan; Döpper, Veronika; Heim, Birgit (2025): 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 [dataset]. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.977771 (DOI registration in progress)

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Published: 2025-03-31

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Abstract:
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.
Keyword(s):
boreal forest; Canada; canopy cover; CHM; Drone; elevation model; Field measurements; GNSS; Individual Trees; Laser scanning; Lidar; permafrost; point clouds; Surface Elevation; thermokarst; topography; UAS; UAV; UAV data; Vegetation; wildfire
Related code / software:
Farkas, Luca; Kruse, Stefan (2024): StefanKruse/PC2RCHIVE: PC2RCHIVE: a FAIR and easy point cloud archiving GUI [software]. Zenodo, https://doi.org/10.5281/ZENODO.14534516
Funding:
Ministerium für Wissenschaft, Forschung und Kultur, grant/award no. F221-08-AWI/001/002
Coverage:
Median Latitude: 64.329523 * Median Longitude: -133.518502 * South-bound Latitude: 58.747792 * West-bound Longitude: -138.454814 * North-bound Latitude: 68.721716 * East-bound Longitude: -121.839175
Date/Time Start: 2022-07-22T20:03:00 * Date/Time End: 2022-08-14T01:03:00
Event(s):
EN22002_Lidar (EN22002) * Latitude: 60.809231 * Longitude: -135.370674 * Date/Time: 2022-08-07T22:20:00 * Location: Yukon, Canada * Campaign: CA-Land_2022_NWCanada (Forest Change Northwest Canada) * Basis: AWI Arctic Land Expedition * Method/Device: Unmanned Aerial Vehicle (UAV), DJI Technology Co, Matrice 300 RTK; coupled with Light detection and ranging scanner (LiDAR), YellowScan, Mapper
EN22003_Lidar (EN22003) * Latitude: 60.439054 * Longitude: -133.565797 * Date/Time: 2022-08-14T01:03:00 * Location: Yukon, Canada * Campaign: CA-Land_2022_NWCanada (Forest Change Northwest Canada) * Basis: AWI Arctic Land Expedition * Method/Device: Unmanned Aerial Vehicle (UAV), DJI Technology Co, Matrice 300 RTK; coupled with Light detection and ranging scanner (LiDAR), YellowScan, Mapper
EN22005_Lidar (EN22005) * Latitude: 67.909441 * Longitude: -133.567374 * Date/Time: 2022-07-25T19:39:00 * Location: Northwest Territories, Canada * Campaign: CA-Land_2022_NWCanada (Forest Change Northwest Canada) * Basis: AWI Arctic Land Expedition * Method/Device: Unmanned Aerial Vehicle (UAV), DJI Technology Co, Matrice 300 RTK; coupled with Light detection and ranging scanner (LiDAR), YellowScan, Mapper
Comment:
This work was funded by the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, for the expedition CA-Land_2022_NWCanada Forest Change Northwest Canada. We also acknowledge funding for our equipment by the project "Potsdamer InnoLab für Arktisforschung" no. F221-08-AWI/001/002 from the Brandenburg Ministry for Science, Research and Culture (MWFK). Additional funding came from the Helmholtz DataHub Information Infrastructure funds within the projects BorFIT and PC2RCHIVE
We would like to thank the logistics department of the Alfred Wegener Institute, especially Volkmar Aßmann and Jan Kahl, for their support in realising the fieldwork. During the preparation phase, contacts with several First Nations people in the areas of our planned field work, Canadian agencies and institutes were very helpful. We are particularly grateful to Katherine Wolfenden, Land and Resources Coordinator in Fort Nelson, Christina Martin, Lands & Resources Coordinator for the Gwich'in Tribal Council, and Laura Nerysoo, Teslin Tlingit Renewable Resource Council Coordinator, as well as Andrew Koe, our wildlife monitor from the Gwich'in First Nation, for helping to ensure our safety during our fieldwork in bear country.
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
1Event labelEventKruse, Stefan
2Latitude of eventLatitudeKruse, Stefan
3Longitude of eventLongitudeKruse, Stefan
4Date/Time of eventDate/TimeKruse, Stefan
5UTM Zone, Universal Transverse MercatorUTM ZoneKruse, Stefan
6UTM Easting, Universal Transverse MercatorUTM eastmKruse, StefanExtent of the area in UTM coordinates as bounding box, Eastings minimum
7UTM Northing, Universal Transverse MercatorUTM northmKruse, StefanExtent of the area in UTM coordinates as bounding box, Northings minimum
8UTM Easting, Universal Transverse MercatorUTM eastmKruse, StefanExtent of the area in UTM coordinates as bounding box, Eastings maximum
9UTM Northing, Universal Transverse MercatorUTM northmKruse, StefanExtent of the area in UTM coordinates as bounding box, Northings maximum
10AreaAream2Kruse, Stefan
11Number of pointsPoints#Kruse, StefanTotal number of points
12Point densityPoint dens#/m2Kruse, StefanNumber of points per area
13Color descriptionColor descKruse, StefanPoints are RGB colored (yes/no)
14Device typeDeviceKruse, StefanLight detection and ranging scanner (LiDAR) with YellowScan Mapper +Laserscanning device
15Processing softwarePSKruse, StefanUsed software for processing
16Method commentMethod commKruse, StefanMode of strip alignment that conducted in the processing
17ErrorErrorKruse, StefanError after strip alignment
18Correction descriptionCorrKruse, StefanInformation about the correction of the position
19Point cloud, LAS fileLASKruse, StefanLight detection and ranging scanner (LiDAR) with YellowScan Mapper +Ground classified point cloud
20ClassificationClassificationKruse, StefanStatement about the ground classification source
21ClassificationClassificationKruse, StefanInformation on ground classification
22Number of points, on groundPoints ground#Kruse, StefanTotal number of ground points
23Tree height, maximumTree h maxmKruse, StefanTotal number of above-ground point
24ResolutionResmKruse, StefanResolution of the rasterized data (Digital Terrain Model DTM, Digital Surface Model DSM, Canopy Height Model CHM)
25Point cloud, LAS fileLASKruse, StefanLight detection and ranging scanner (LiDAR) with YellowScan Mapper +Individual Tree Detection (ITD) point cloud
26Method commentMethod commKruse, StefanLinear function for LMF
27Tree heightTree heightmKruse, StefanTree segmentation parameter
28Number of pointsPoints#Kruse, StefanTotal number of points in trees
29Number of treesTrees#Kruse, StefanTotal number of detected trees
30Tree crown diameterCrown diammKruse, StefanMean crown diameter of all detected trees
31Tree heightTree heightmKruse, StefanMean height of all detected trees
32Tree height, maximumTree h maxmKruse, StefanMaxiumum height of all detected trees
33Tree height, minimumTree h minmKruse, StefanMinimum height of all detected trees
34Binary ObjectBinaryKruse, Stefanreport
35Point cloud, LAS fileLASKruse, StefanLight detection and ranging scanner (LiDAR) with YellowScan Mapper +aboveground point cloud
36Point cloud, LAS fileLASKruse, StefanLight detection and ranging scanner (LiDAR) with YellowScan Mapper +ground point cloud
37Point cloud, LAS fileLASKruse, StefanLight detection and ranging scanner (LiDAR) with YellowScan Mapper +point cloud
38Text fileTEXTKruse, Stefan
39ImageIMAGEKruse, StefanESRI footprint
40ImageIMAGEKruse, StefanOpen Street Map footprint
41ImageIMAGEKruse, Stefanaspect
42ImageIMAGEKruse, StefanCanopy Height Model
43ImageIMAGEKruse, StefanCanopy Height Model aggregated
44ImageIMAGEKruse, StefanDigital Surface Model
45ImageIMAGEKruse, StefanDigital Terrain Model
46ImageIMAGEKruse, Stefanslope
47Geospatial vector, shapefilesShapefileKruse, Stefantree crown shapefiles
48Geospatial vector, shapefilesShapefileKruse, Stefanfootprint shapefiles
49Geospatial vector, shapefilesShapefileKruse, Stefantrajectory shapefiles
Status:
Curation Level: Enhanced curation (CurationLevelC)
Size:
1123 data points

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