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LiDAR for forestry
Tree, Canopy and TerrainDeliverables in Minutes
Extract tree crowns, build canopy height models, estimate per-tree carbon stock, and generate terrain models under dense canopy — without desktop-heavy workflows.
No software to install • 50 hectares included
Tree detection
Crowns & tops
Crowns & tops
Carbon
102 species models
102 species models
Canopy height
CHM raster
CHM raster
DTM
Ground under canopy
Ground under canopy
The challenge
Processing bottlenecks in forestry
Dense canopy makes complex multi-return point clouds that are hard to classify accurately, and traditional software wants tuning for every forest type.
Traditional tools
- Expensive desktop software with a steep learning curve
- Weeks of training before the first dataset is processed
- Manual parameter tuning per forest type
- Project timelines slipping while staff learn the workflow
Lidarvisor AI
- Upload and process in minutes
- No installation, no parameter tuning
- Complex canopy structures handled automatically
- DTMs, tree crowns, carbon estimates and vegetation metrics
The outputs
What a forestry job actually needs
Tree detection
Tree Crown & Tree Top Extraction
Individual tree data for forest inventory.
Individual crowns are detected and delineated from the point cloud automatically, giving tree positions and crown polygons ready for inventory analysis.
- Individual tree-top point locations
- Crown boundary polygons for every tree
- Automatic sensitivity — detection adapts to local canopy height instead of asking you to pick a setting
- No manual digitising required
Carbon New
Per-Tree Carbon Estimation
Carbon stock from LiDAR-measured heights.
Turn tree height into carbon metrics that matter. Lidarvisor calculates per-tree carbon stock, CO₂ equivalent and above-ground biomass using species-specific allometric models — the data carbon credit programmes and climate reporting need.
- Carbon (t C), CO₂ equivalent (t CO₂eq) and biomass (t AGB)
- 8 regions: Europe, Canada, USA, Tropical, Australia, Boreal, East Asian, African Dryland
- 102 species-specific allometric models
- IPCC-sourced methodology documented in the PDF report
Canopy height model
Canopy Height Analysis
Measure forest structure and vertical distribution.
CHM shows vegetation height above the terrain surface, derived automatically from multi-return LiDAR, so you can measure structure and identify dominant trees.
- CHM raster output ready for analysis
- Identify dominant and co-dominant trees
- Analyse vertical forest stratification
Vegetation layers
Vegetation Classification
Low, medium and high vegetation, separated.
Vegetation returns are classified into ground cover and shrubs, understory, and canopy. That three-tier structure is what habitat assessment, fire fuel modelling and forest management run on.
- Three-tier vegetation structure data
- Built for habitat and fuel modelling
- Automatic LAS class assignment
Terrain model
DTM Generation Under Canopy
Accurate ground surface beneath dense forest.
The most critical forestry output. Lidarvisor filters through multiple vegetation returns to find the actual ground points, producing clean terrain models even in difficult forest.
- Penetrates dense canopy cover
- AI-powered ground classification
- GeoTIFF and contour exports
Detection sensitivity
One setting fewer to get wrong
Tree detection used to hinge on a single sensitivity choice applied to the whole site. It no longer does.
A single global setting
- You pick one sensitivity for the entire site
- A 1 m notch reads the same on a 30 m conifer and a 5 m shrub
- Mixed stands force a compromise: split stems or missed trees
Automatic, per location
- Sensitivity derived from local canopy structure
- Required peak prominence rises with local canopy height
- Smoothing scales the same way, so mixed stands stop being a compromise
Processing options
Carbon estimation, configured in three clicks
Region selection
Choose from 8 geographic regions so the allometric model fits your forest.
Species dropdown
Pick from 102 species-specific models, or fall back to regional defaults.
Reporting
The deliverable your stakeholders read
Forest inventory report
Digital Forest Inventory
Complete tree metrics in PDF and CSV.
A professional PDF for stakeholders, plus raw CSV for your forest management software and GIS workflows.
- PDF report with tree statistics and visualizations
- CSV export: height, crown diameter, crown area, X/Y coordinates
- Carbon columns in CSV (t C, t CO₂eq, t AGB per tree)
- Carbon Estimation Summary page in the PDF report
How it works
Your forestry LiDAR workflow
01
Upload
Drag and drop LAZ or LAS files. No format conversion, no preprocessing required.
02
Process
The AI classifies the cloud, extracts vegetation layers, identifies trees and calculates carbon stock.
03
Export
Download classified clouds, DTM/DSM, CHM, crown polygons, tree tops and the inventory report.
Use cases
Forestry use cases
Forest Inventory
Individual tree locations and crown dimensions for stand-level inventory and timber volume.
Habitat Assessment
Vertical vegetation structure for wildlife habitat quality and ecosystem health.
Timber Harvest Planning
Accurate terrain models for logging road design and harvest unit delineation.
Carbon Stock & Credits
Per-tree carbon, CO₂eq and biomass for credit programmes and climate reporting.
Questions
Frequently asked questions
How accurate is tree detection under dense canopy?
The models are trained on diverse forest types including conifer, broadleaf and mixed stands. Accuracy depends on point density and canopy structure, but the algorithms handle complex multi-layer forests reliably. For best results we recommend point clouds with 10+ points per square metre.
How does carbon estimation work?
Carbon stock is calculated from LiDAR-measured tree heights using species-specific allometric models. Enable carbon estimation in processing options, select your geographic region, and choose from 102 species models. The system outputs carbon (t C), CO₂ equivalent (t CO₂eq) and above-ground biomass (t AGB) per tree, in the CSV export and a dedicated summary page in the PDF report with methodology and IPCC sources.
Can I process large forest datasets?
Yes. Upload your LAS or LAZ files and the cloud infrastructure scales automatically. Paid plans support files up to 50 GB LAS / 10 GB LAZ, you can combine up to 50 tiles of one survey in a single project, and processing stays fast even over extensive forest areas.
What outputs do I get for forest inventory?
Classified point cloud (LAS), DTM, DSM, CHM, tree top points (CSV/SHP), crown polygons (SHP/GeoJSON), and a Digital Forest Inventory report (PDF/CSV) with height, crown diameter, crown area, position coordinates and optional carbon metrics.
Does it work with different forest types?
The AI is trained on temperate deciduous, tropical rainforest, boreal conifer, plantation and mixed stands, and adapts automatically with no parameter tuning. For carbon estimation, select the matching geographic region and species for the most accurate allometric model.
How does pricing work for forestry projects?
Pricing is based on processed hectares. Start with free hectares to test the outputs, then choose a plan based on your project size. Volume discounts are available for large forest management operations.
Documentation
Learn the forestry workflow
How to process forestry LiDAR data with Lidarvisor.
Ready to process your forest LiDAR data?
Stop waiting weeks for classified point clouds and forest metrics. Upload your first dataset and see results in minutes, carbon estimates included.
Get started freeNo software to install. No parameters to configure. View pricing or contact our team