Case Studies
Published on 20 Jun 2025
James Willoughby
Measuring tree height with drone LiDAR
How drone LiDAR can be used to create accurate Canopy Height Models to measure trees, ideal for forestry and land management, ecology, and carbon monitoring.
In-depth blog explaining how drone LiDAR helps obtain accurate data to measure tree heights;
Tree-height measurements are important for sectors such as forestry and land management, conservation and ecology, and carbon and climate monitoring;
Data collected by heliguy™ in collaboration with Forestry England shows the benefit of using drone LiDAR for measuring trees;
DJI Zenmuse L2 and DJI M350 RTK surveyed almost 10,000 trees across 15 hectares in 15 minutes;
The drone data was fed in to DJI Terra and then Esri ArcGIS Pro’s 3D Analyst toolbox to enable accurate height measurements: Watch the workflow video.
Forests and woods are living landscapes, shaped by growth, disturbance, and regeneration. To understand these complex ecosystems, one of the most revealing metrics we can measure is tree height.
It’s not just a number - it’s a gateway to deeper insights into structure, biomass, carbon storage, biodiversity, and ecological health.
Data collected by heliguy™ in collaboration with Forestry England demonstrates how drone LiDAR offers an efficient and accurate way of capturing this information - using the DJI Zenmuse L2 and DJI M350 RTK to map just shy of 10,000 trees in just 15 minutes.
And this workflow video illustrates how the data can be used to generate Canopy Height Models and transformed into graphical charts that showcase tree height - utilising DJI Terra and Esri ArcGIS Pro’s 3D Analyst toolbox.
This method facilitates a range of insights, such as the accurate measurement of individual trees, with this particular bloom stretching 5.7 metres...
…or the ability to view the height of a cluster of trees throughout the survey area.
In this blog, we explore:
Why tree height data matters;
Why LiDAR matters;
How a Canopy Height Model (CHM) and applying a Local Maximum Raster (LMR) are fundamental to obtaining tree-height insights;
Real-world benefits of tree height maps;
Tree height mapping workflow.
Why measure tree height?
Tree height is a fundamental indicator of forest/wood condition and vitality. Whether you’re managing a woodland, monitoring habitat, or conducting scientific research, tree height reveals:
Forest/wood age and structure
Vegetation density
Biomass and carbon content
Growth trends or damage over time
Potential habitat quality for canopy-dwelling species.
This is beneficial for forestry and land management, conservation and ecology, carbon and climate monitoring, and risk assessment/disaster response.
The table below highlights the benefits of capturing data about tree height within these respective sectors.
Application | Benefit |
|---|---|
Timber estimation | Estimate timber volume and market value |
Harvest planning | Plan selective harvesting zones |
Reforestation monitoring | Monitor reforestation success over time |
Biodiversity assessment | Identify mature stands, key for biodiversity |
Habitat analysis | Assess habitat for birds, insects, or mammals |
Canopy structure | Detect canopy gaps indicating disturbance or regeneration |
Biomass estimation | Estimate above-ground biomass and carbon stock |
Carbon offsets | Support carbon credit programmes with verifiable data |
Growth monitoring | Analyse forest growth rates and carbon sequestration potential |
Treefall risk | Detect treefall risk near power lines or roads |
Fire-risk mapping | Analyse fire-prone zones by canopy density |
Damage assessment | Map post-storm or fire damage accurately |
Why is Drone LiDAR important for measuring tree height?
Drone LiDAR is a powerful tool for capturing accurate tree height information.
Advantages of drone LiDAR include:
Penetrates Canopy to Map the Ground: LiDAR pulses can reach the forest floor even in dense canopies, as shown by the image below.
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This is essential for building DTMs and DSMs. This data - as we’ll explore later - helps build reliable CHMs.
High Resolution: LiDAR is a very accurate survey method, helping you collect dense point clouds. It also enables the detection of individual trees, provides more accurate height information, provides better separation of closely-spaced trees, and Drone LiDAR is a powerful tool for capturing accurate tree height information. improves detection in rugged or sloped terrain.
Fast and Repeatable: Fly the same area over time to track forest changes, growth rates, or impacts from storms or human activity.
Works in All Light Conditions: LiDAR is active sensing—it doesn’t rely on sunlight. This means consistent results in shaded forests, overcast skies, or even dusk/dawn flights.
What Is a Canopy Height Model (CHM)?
A Canopy Height Model (CHM) is crucial to visualising tree heights throughout a survey area.
This type of dataset is a surface map that shows the height of vegetation (especially tree canopies) above ground level.
A CHM is derived using two base layers:
Digital Surface Model (DSM): Captures the elevation of everything - trees, buildings, and terrain.
Digital Terrain Model (DTM): Captures the elevation of the bare ground, excluding any vegetation or structures.
This gives us the equation: DSM - DTM = CHM
By subtracting the ground elevation from the surface elevation, the CHM isolates the true height of the trees. Once a CHM is generated, we can generate a Local Maximum Raster.
This highlights the highest point (or pixel value) within a defined neighbourhood or window in a Canopy Height Model. It’s used to identify local peaks, which usually correspond to tree tops.
This graphic shows the difference between a DSM, DTM, CHM, and LMR.
And this table provides an overview of their differences.
Model | What it represents | Includes trees? | Created from | Main use cases | Output type |
|---|---|---|---|---|---|
DTM | Bare earth surface elevation | No | LiDAR ground returns | Topography, hydrology, slope/aspect analysis, flood modelling | Raster (elevation grid) |
DSM | Top surface of everything (ie ground, trees, buildings) | Yes | LiDAR first returns | Urban planning, solar studies, flight planning, forest canopy mapping | Raster (elevation grid) |
CHM | Tree/canopy height above ground | Yes | DSM - DTM | Tree height mapping, biomass estimation, forest structure analysis | Raster (height grid) |
LMR | Detected tree tops from CHM | Tree tops only | CHM + neighbourhood filter | Individual tree detection, height extraction, crown delineation | Raster or vector (tree points) |
Tree height mapping: Real-world workflow
To showcase the benefits of deploying drone LiDAR for obtaining tree height insights, heliguy™ teamed up with Forestry England to map a section of Kielder Forest, in Northumberland, UK.
The information below is an end-to-end tree height workflow, from collecting the data with the DJI Zenmuse L2 and DJI M350 RTK, processing the data in DJI Terra, and then moving into ArcGIS Pro for CHM and LMR generation.
1: Data capture
The data was captured quickly: Surveying 9,274 trees across an area of 15 hectares in 15 minutes, with the following parameters.
60m altitude.
5m/s ortho flight.
Repetitive scanning.
Penta return.
1.5m GSD.
2: DJI Terra
The data was uploaded into DJI Terra and processed into a .LAS file.
It’s worth noting that the L2 can generate true-colour point clouds, as well as displaying various LiDAR metrics, such as number of returns, intensity, and height.
3: ArcGIS Pro
i. Convert .LAS from Terra into a .LAS dataset in ArcGIS Pro.
ii. Create raster DTM from the ground classification and raster DSM from all points.
iii . Create CHM through DSM-DTM.
iv. Apply local maximum filter to CHM.
V: Locate all local maxima - and then filter.
vi: Once converted to points, this can be plotted using 3D symbology to show individual trees scaled by height.
vii: Statistics on tree height can be generated and further analysis undertaken.
As well as height, this view shows how the data can be used to highlight the spread of trees across the survey area.
Summary
Mapping tree height is more than a measurement—it’s a window into the health, structure, and value of a forest. And when powered by drone LiDAR and visualized through a Canopy Height Model, it becomes a powerful tool for environmental intelligence.
Whether you’re managing a commercial forest, restoring native woodlands, or conducting ecological research, tree height data helps you see the forest for the trees—literally.
To integrate drone LiDAR into your mapping workflows, contact us, and our drone survey team can help you.
