Dataset
ForestScan: Terrestrial Laser Scanning (TLS) of Gabon 1ha plot OKO-01
Abstract
Terrestrial laser scanning was conducted from June to July 2022 by Cecilia Chavana-Bryant & Phil Wilkes using a Reigl VZ-400i for the ForestScan project. Scans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce a high-quality point cloud of this 1ha (100 x 100m) forest plot in Gabon. Capturing a complete sample of the scene at each location requires two scans (an upright & a 90° tilt scan), owing to a 100° field of view. Upright scans will be odd numbered while tilt scans will be even numbered. The first scan on a plot is collected on its SW corner (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently) with the tilt scan oriented towards the next sampling position & tilt scans along the edges of plots oriented towards the inside of the plot while all other tilt scans are oriented towards the previously scanned line. A total of 242 scans were collected per 1ha plot.
Details
Previous Info: |
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Access rules: |
Please contact the data centre for details on how to access these data.
For data use licensing information please contact: support@ceda.ac.uk |
Data lineage: |
To generate a plot-level point cloud, all 242 scans were registered using RiSCAN Pro version 2.14.1 software. Scans were coarse registered via GNSS enabled Auto-Registration 2 (AR2), coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2), and finally, the Sensor's Orientation and Position (SOP) matrix for all scans saved into the "matrix" project directory and the GNSS coordinates (geographical coordinate system: WGS84 Cartesian) for all scans saved as a .kmz file. |
File Format: |
Not defined
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Related Documents
Process overview
Independent Instruments
UCL REIGL VZ-400i Terrestrial Laser Scanner (Serial #: H2226750) |
Computation Element: 1
Title | TLS2trees: a semi-automated processing pipeline |
Abstract | Plot-level point clouds were processed using TLS2trees which is a set of Python command line tools & designed to be horizontally scalable, e.g., on a High Performance Computing (HPC) facility. Pipeline steps: 1) Point cloud re-processing, 2) semantic segmentation into wood & leaf point classes, 3) instance segmentation into sets of point clouds representing individual trees, 4) Quantitative structural models (QSMs) of individual tree point clouds, & 5) Plot biophysical & AGB estimates. |
Input Description | None |
Output Description | None |
Software Reference | None |
Output Description | None |
No variables found.
Temporal Range
2022-06-04T00:00:00
2022-06-09T00:00:00
Geographic Extent
-0.1945° |
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11.5833° |
11.5834° |
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-0.1958° |