Overview

Orthophoto (Orthofoto) and LiDAR (Laser) data, which are organized into folders named after the area and year they are from.

  Dataset Structure

Geodata Kristiansand.zip (example) fgb Vann_22.fgb...

geojson Vann_22.geojson...

Ortofoto Agder_og_Telemark_2021.zip (example) Agder_og_Telemark_2021.zip_mosaic_cog.tif

Laser Bergen_2pkt_2010 Bergen_2pkt_2010_mosaic.laz

  Usage

Currently only been used in QGIS to display Ortofoto, Laser Data and… See the full description on the dataset page: https://huggingface.co/datasets/kartai/DX_datasett.

Point clouds collected at the of the Forest and Biodiversity Experiment 2 located at the Cedar Creek Ecosystem Science Reserve (CCESR), Minnesota, USA. These point clouds were collected using a LiDAR onboard an Uncrewed Aerial Vehicle (UAV) thoughout the growing season of 2022. , We collected LiDAR data across the FAB2 experiment eight times during 2022 on the following days of the year: 100, 138, 163, 188, 215, 250, 261, and 297. Flights were conducted throughout the growing season before leaf out until after leaf senescence of the deciduous species in accordance with sufficient accumulated growing degree days for 2022. Data were collected using a Zenmuse L1 sensor onboard an Uncrewed Aerial Vehicle (UAV) DJI Matrice 300. This sensor integrates a Livox LiDAR module, an inertial measurement unit, and an RGB camera on a 3-axis stabilized gimbal. The LiDAR module has a conic footprint on ground with a field of view of 77.2° vertical and 70.4° horizontal, enabling it to capture multiple returns. All the surveys were conducted using autonomous flights programmed to take place at a speed of 8 m/s at 50 m above ground. These surveys were done in an area of ~5.8 ha with 85% overlap between sidetracks allowing capture of dense point clouds (~ 2100 point/m2). During thes..., , # UAV-LiDAR point clouds from the Forest and Biodiversity Experiment 2 (2022)

https://doi.org/10.5061/dryad.jdfn2z3hk

Eight point clouds were collected on the Forest and Biodiversity Experiment 2 throughout the 2022 growing season

Description of the data and file structure

We provide point clouds using the compressed format (.LAZ) clipped to the area where the experiment is located. These point clouds were not filtered by noise nor decimated by the redundancy of points. However, these were processed by stripe alignment, ground classification, and normalization by height. The height provided (i.e., Z coordinate) is in reference to the height from the ground. The X and Y columns are coordinates projected to NAD83 UMT15 (EPSG:26915). The names of the files refers to the date of data collection.

Code/Software

Point clouds can be opened using QGIS, [CloudCompare,](https://www.danielgm.net...