Forestry Guide: Tree Inventory, Canopy Analysis, and Carbon Estimation

This guide walks you through a forestry workflow in Lidarvisor — from a raw LAS file to a complete tree-by-tree inventory with optional carbon stock estimates.

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What You Will Produce

By the end of this workflow, you will have:

• A classified point cloud with ground and vegetation classes
• A DTM (bare ground) and CHM (canopy height model showing tree heights)
• Tree tops — individual tree locations and heights
• Tree crowns — canopy boundary polygons for each tree
• A Digital Forest Inventory report (PDF + CSV) with per-tree measurements
• Optional: Carbon estimation with above-ground biomass, below-ground biomass, carbon stock, and CO2 equivalent per tree

A field-based forest inventory typically requires weeks of manual work with measuring tapes and clinometers. Lidarvisor produces a comparable inventory from aerial data in minutes.

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Step 1: Prepare Your Data

Export your LiDAR data as a LAS or LAZ file. For forestry, ensure:

• The flight covered the entire area of interest — gaps in coverage mean missed trees
• Flight altitude and sensor settings captured canopy penetration — you need ground points under the trees, not just treetop points
• If possible, fly during leaf-off season (winter/early spring for deciduous forests) for better ground penetration

Tip: If your data has poor ground penetration (few points reaching the forest floor), the DTM and tree height measurements will be less accurate. Lidarvisor will still classify and process the data, but results improve with better ground coverage.

Step 2: Create a Project and Upload

1. Log in to cloud.lidarvisor.com.
2. Click Create a project.
3. Name it (e.g., "Oakridge Forest Plot - Spring 2026").
4. Select your LAS/LAZ file and click Import project.

Step 3: Configure Processing Options

In the left panel, enable these options:

Terrain (Raster):

• Generate DTM — Resolution: 100 cm (sufficient for most forestry work; ground under canopy is naturally sparse)
• Generate CHM — Resolution: 100 cm

Vector:

• Extract Tree Tops
• Extract Tree Crowns — Crown shape: Narrow for conifer-dominated forests, Wide for deciduous-dominated forests. If mixed, choose the dominant type.

Reports:

• Generate Digital Forest Inventory
• Carbon Estimation — toggle ON if you need biomass and carbon data
• Allometric Region — select the region closest to your forest:
  • Europe, Canada, USA, Tropical, Australia, Boreal/Russia, East Asia, African Dryland
• Dominant Tree Species — select the most common species. If unsure, choose the generic option for your region.

Click Process Data and confirm.

Step 4: Review Your Results

Check the CHM

Toggle the CHM layer on in the project tree. This shows vegetation height as a color gradient:

• Blue/green = low vegetation or clearings
• Yellow = medium-height trees
• Red = tallest trees

Does the height distribution look reasonable for your forest? If the tallest trees show 25 m and you know the forest has 30 m trees, the ground model may be slightly high (reducing apparent tree heights).

Check Tree Detection

Toggle Tree Tops and Tree Crowns on. Overlay them on the classified point cloud:

• Are individual trees detected where you expect them?
• In very dense canopy, some trees may be merged — this is normal
• In open areas, isolated trees should each have their own crown polygon

Review the Forest Inventory

Download the forest inventory (ZIP with PDF + CSV):

• The PDF has overview maps and statistics (total trees, average height, max height, average crown area)
• The CSV has a row per tree with ID, position, height, crown area, and (if enabled) biomass and carbon values

Step 5: Use Your Results

For Timber Inventory

The CSV gives you tree count, height distribution, and crown area for the entire area. Filter by height classes to estimate timber volume:

• Trees under 10 m → understory / not merchantable
• Trees 10–20 m → mid-canopy / potentially merchantable
• Trees over 20 m → dominant canopy / high-value timber

For Carbon Credits

If you enabled carbon estimation, the report includes:

• Total above-ground biomass (AGB) in tonnes
• Total below-ground biomass (BGB) in tonnes
• Total carbon stock in tonnes (AGB + BGB × carbon fraction)
• Total CO2 equivalent in tonnes (carbon × 3.67)

These values follow IPCC-referenced methodologies and can support carbon credit documentation. For formal carbon credit projects, you will typically need to validate these numbers with field samples.

For Habitat Assessment

The CHM and crown data reveal forest structure:

• Crown size distribution indicates forest maturity
• Canopy gaps indicate disturbance or clearings
• Height variation indicates structural diversity (important for biodiversity)

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Recommended Settings by Forest Type

Forest Type	DTM Resolution	CHM Resolution	Crown Shape	Species Example
Dense conifer plantation	100 cm	50 cm	Narrow	Scots Pine, Norway Spruce
Deciduous temperate forest	100 cm	100 cm	Wide	European Beech, Pedunculate Oak
Mixed forest	100 cm	100 cm	Wide	Generic or dominant species
Tropical forest	100 cm	100 cm	Wide	Generic tropical hardwood
Open savanna / scattered trees	50 cm	50 cm	Wide	Site-specific species

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Limitations to Be Aware Of

• Very dense closed-canopy forests: Some individual trees may be merged into a single crown. The tree count may be slightly lower than the actual count.
• Young plantations with very small trees: Trees below approximately 4 m height may not be detected as individual trees.
• Mixed-species forests: Carbon estimation uses a single species model. If your forest has multiple species, consider processing with the dominant species and applying species-specific corrections to the CSV data.
• Understory trees: Trees completely hidden beneath the canopy of taller trees are generally not detected by aerial LiDAR.

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What This Replaces

In a traditional field-based workflow:

1. Plan and execute field plots (~1–2 days per km²)
2. Measure DBH and height for sample trees (~10–30 min per plot)
3. Extrapolate from plots to the full area (~1 day)
4. Calculate biomass using allometric equations manually (~1 day)
5. Assemble the inventory report (~1 day)

Total: days to weeks depending on area size.

Lidarvisor provides a wall-to-wall inventory (every tree, not just sampled plots) in a single processing run. Field validation is still recommended for formal reporting, but the desktop work is eliminated.