Point-Cloud Tree Extraction
What is it
Individual trees measured from your point cloud
Clear Timber Analytics extracts individual trees and their measurements from LiDAR and other point-cloud data. Already have suitable data? Send it directly to our team. If not, we can source available third-party datasets or arrange new point-cloud collection worldwide through local partners. The result is a validated, GIS-ready tree inventory for use in urban forestry, surveying and infrastructure management.
What we work from
Mobile-mapping, aerial, UAV and handheld point clouds
We work with the LiDAR data collected by various capture method. Point density, coverage and accuracy differ a lot, but we tell you up front what each dataset can and cannot deliver.
drone
mobile mapping
aircraft
handheld
backpack
Supported data formats
.LAZ .LAS .COPC .E57 .PLY
We do not require pre-classified or tiled point cloud, we’ll take care of that. We just need a raw pointcloud.
WHAT YOU GET
A tree inventory, not a point cloud
We hand over you a tree layer, with one record per tree, each with a crown geometry and a set of measurements.
Individual tree detection
Every tree is segmented as its own object with a unique number and a GPS position.
Stem points and crown polygons
We deliver two geometries per tree: a point at the stem base (location) and a polygon of the crown projection.
Height, DBH and crown measurements
The metrics come straight from the point-cloud geometry of each individual tree, not from a simplified model. So a crown is captured in its real shape, not simplified as a circle. It means the tree is read the way it actually stands.
Other available tree attributes
Beyond the core set, further attributes are agreed per project and delivered only where the data genuinely supports them:
- Crown volume
- Lowest limb height
- Leaf area index (LAI)
- Lean angle (inclination)
- Clearance to road or rail
- Distance to façade
- Broadleaf/coniferous class
- Change against a previous capture.
Before and After
From raw points to every tree seperate
We turn raw, unclassified point clouds into a classified point clouds, where individual trees are identified and segmented separately.
How we get the data
Three routes to the same inventory
There are few ways to get the point cloud of your Area of Interest.
1 · ANALYSE YOUR DATA
Use the client's existing data
The client supplies previously collected point cloud data. It can be mobile-mapping, aerial, UAV or handheld. Clear Timber assesses its suitability and extracts the individual trees and requested measurements.
2 · SOURCE EXISTING DATA
Source suitable existing data
In many cases, the data already exists. When our mobile-mapping partners already cover the project area, Clear Timber identifies and purchases already existing data.
3 · ARRANGE NEW COLLECTION
Arrange new data collection
If there is no suitable data is available, Clear Timber coordinates new point-cloud collection. We arrange it worldwide through qualified local partners and afterwards we run the analysis.
Methodology
Analysis and qc
Before the quote and processing we check the quality of the data. If the data cannot carry the attributes you asked for, we say so at this stage.
Once the quality of collected data is validated, we classify the objects, extract a terrain model and segment all the trees.
The segmentation of the trees is checked by our specialists.
When the tree segmentation is checked and confirmed we can run the measurements. Each tree gets the list of measured attributes, such as DBH, tree height and crown parameters.
Before the handover of the results, our specialists check again the outcome. We check outliers, unrealistic height-to-DBH ratios and remove the metrics of low-confidence trees.
Once the results are reviewed, the inventory in form of zipped package is delivered to the client.
Honest Limitations
What point clouds cannot tell you
- Data quality depends on the scanner type and method used, as well as the terrain itself. Areas with dense low vegetation can reduce point-cloud accuracy and result in missing measurements.
- DBH is measured only when sufficient data is available. If a stem is covered by shrubs or other obstacles, such as fence or a car, the measurement cannot be calculated.
- If a tree is located far from the scanning path or is captured from only one side, there might not be enough points to calculate reliable metrics. As a result, the data for that specific tree may be incomplete or less accurate.
- Vitality and health status usually require additional data sources, such as multispectral imagery or field verification.
Delivery
GIS-ready delivery formats
Shapefile (.shp)
GeoJSON
DXF / DWG
CSV / XLSX with coordinates
FILL IN THE FORM
If you happen to have already your data, send it to us a small area and we return with a short assessment of what your data can deliver. If you have no data yet, tell us the project area instead.
Where are you starting from?
