WHY FORESTERS CHOOSE LIDAR

Traditional inventory relies on field crews walking transects, manually measuring sample trees. The results? Statistical estimates based on a fraction of your actual forest.

forest

Measure Every Tree

Complete coverage, not sample plots

layers

Penetrate Canopy

Multi-return LiDAR reaches ground

speed

Cover Vast Areas

Survey hundreds of hectares daily

terrain

Access Difficult Terrain

Steep slopes and remote areas

update

Repeat Surveys

Track growth over time

THE PROCESSING CHALLENGE

The bottleneck isn’t data collection anymore. It’s processing those millions of points into actionable forest metrics.

Complex Ground Classification
Under dense canopy, separating ground returns from low vegetation is notoriously difficult. Traditional algorithms require extensive parameter tuning.

Expensive Specialized Software
Forest-specific LiDAR tools come with steep learning curves and steeper price tags.

Manual Tree Delineation
Individual tree detection algorithms often require manual review and correction. Crown segmentation stretches into hours of editing.

Format Integration Issues
Converting between LiDAR tools and GIS platforms introduces errors and delays.

How Lidarvisor Streamlines Forest Inventory

Automate the entire workflow, from raw point cloud to tree-level deliverables.

AI-Powered Ground Classification

Upload your LAS or LAZ file. Lidarvisor’s deep learning algorithms automatically classify ground points, even under dense forest canopy. Built-in manual tools let you refine classification for complex terrain.

No parameter tuning required. The system adapts to your specific forest conditions.

The platform classifies vegetation into low, medium, and high strata, giving you the vertical forest structure needed for habitat analysis and biomass estimation.

Instant Canopy Height Model

From classified ground points, Lidarvisor generates:

Digital Terrain Model (DTM): Bare earth beneath the canopy
Digital Surface Model (DSM): Top-of-canopy elevation
Canopy Height Model (CHM): DSM minus DTM = actual tree heights
Hillshade: For visualization and terrain analysis

Export any layer as GeoTIFF for integration with your GIS or forestry software.

Lidarvisor - Canopy Height Model
Lidarvisor - Tree Crowns

Automatic Tree Detection

Lidarvisor identifies individual trees as local maxima in the Canopy Height Model. For each detected tree, you get:

Tree top location: XY coordinates of each stem
Tree height: Extracted from CHM
Crown boundary: Polygon delineating each tree’s canopy extent

Export tree tops and crown polygons in DXF, SHP, or GeoJSON format. Import directly into your forest management GIS.

Per-Tree Carbon Estimation

Lidarvisor converts LiDAR-measured tree heights into carbon stock estimates using 102 species-specific allometric models across 8 geographic regions:

EuropeCanadaUSATropical
AustraliaBoreal/RussianEast AsianAfrican Dryland

For each tree, get:
Carbon stock (tonnes C)
CO₂ equivalent (tonnes CO₂eq)
Above-ground biomass (tonnes AGB)

Enable carbon estimation in processing options, select your region and species, then export results in the enhanced CSV with carbon columns.

Forest Inventory Reports

Lidarvisor generates PDF reports with key forest metrics:

• Tree count and density
• Height distribution statistics
• Canopy cover percentage
• Area summaries by height class
Carbon Estimation Summary with methodology, stand-level carbon statistics, and IPCC-referenced sources

Share reports with stakeholders who need forest metrics without raw LiDAR access. Carbon reports support carbon credit programs and sustainability documentation.

Forestry Applications

Timber Volume Estimation

Combine tree heights and crown dimensions with allometric equations. Wall-to-wall coverage means volume estimates for entire compartments, not extrapolations from sample plots.

Harvest Planning

Identify mature stands ready for harvest based on height thresholds. Map access routes using the terrain model. Plan selective harvest by targeting specific size classes.

Growth Monitoring

Compare CHMs from different survey dates to track height growth. Identify vigorous growth areas versus stagnation. Detect mortality and gap formation.

Carbon Accounting & Credits

Per-tree carbon estimates from LiDAR support carbon credit programs, REDD+ reporting, and corporate sustainability documentation. Lidarvisor’s carbon outputs include IPCC-referenced methodology for defensible measurements across 8 global regions.

Wildfire Risk Assessment

Map canopy density and vertical fuel structure. Identify ladder fuels where low and high vegetation connect. Three-tier classification supports fire behavior modeling.

Habitat Analysis

Vertical structure data (low/medium/high vegetation) supports wildlife habitat assessment. Map forest structure characteristics that specific species require.

Pricing for Forest Inventory

Pay by the hectare. A model that aligns with how forest inventory projects are scoped.

Plan Price Processing
Free $0 10 hectares
Premium $89/month 100 hectares/month
Advanced $249/month 500 hectares/month

Frequently Asked Questions

Yes. The AI-powered ground classification is specifically designed to handle forested terrain where separating ground from low vegetation is challenging. Multi-return LiDAR data provides the vertical information needed for accurate classification.

Tree detection accuracy depends on point density and canopy structure. In open-canopy forests, individual tree detection is highly accurate. In very dense, closed-canopy stands, some tree crowns may merge. Review detection results for your specific forest conditions.

Lidarvisor uses LiDAR-measured tree heights with species-specific allometric models to estimate carbon stock, CO₂ equivalent, and above-ground biomass for each tree. Select your geographic region and dominant species during processing. The system includes 102 models across 8 regions, with methodology referenced to IPCC guidelines.

Lidarvisor accepts LAS and LAZ formats. For forest inventory, we recommend multi-return sensors with point densities of 4+ points per square meter. Higher densities improve tree detection in dense stands.

Lidarvisor is optimized for aerial LiDAR data. Terrestrial laser scanning produces different point distributions and may not classify optimally. Use aerial data for best forest inventory results.

Rasters (DTM, DSM, CHM, hillshade): GeoTIFF. Vectors (tree tops, crowns, contours): DXF, SHP, GeoJSON. Tree metrics with carbon data: CSV. Reports: PDF. Choose the format that fits your GIS or forestry software.

Create a FREE account now and start processing your point cloud

Get 2 GB of storage space and classify up to 10 hectares for free.