Measuring Tree Height from Lidar

Forests are a wealth of life, providing habitat for wildlife and timber resources for human benefit. As such, forest observations are an important part of many natural resource data collections. Tree height is one of the most widely used indicators of an ecosystem’s site index, or its ability to grow trees. It is also used to quantify timber resources, measure stocks of forest carbon, and is foundational in ecological studies. Lidar and other remote sensing methods have become a staple method for measuring modern forests. To penetrate dense canopies, foresters use lidar data in Global Mapper Pro to map bare ground elevation values and visualize forest density, crown coverage, and tree heights. Timber cruises for manual measurements take manpower and time. Measuring forests from lidar, as well as other measures of life such as midstory cover and exposed ground, helps foresters have a better understanding of existing stand dynamics at a fraction of the labor costs.

Lidar Classification

Lidar provides precise and accurate estimates of forest height. Whether the lidar is collected by a user or downloaded from a free online resource, Global Mapper’s extensive lidar toolset is used to prepare data for analysis and feature extraction. 

The automatic lidar classification options assign an attribute to each point, identifying them as features to improve human visualization and computer processing. Noise classification is especially important in highly vegetated areas due to the frequency of outliers that need to be omitted from future processing. Next, ground and then vegetation classifications are assigned automatically based on the point cloud structure. Once classified, the point cloud is used in Global Mapper to create 3D products such as digital terrain models, topographic maps, and more.

Trees in lidar
Point classification separates vegetation from ground points, an essential step in the processing of forest data.

Other Optional Preprocessing

Many of the lidar point clouds available online, such as those provided by the USGS, are preprocessed before release and don’t require much classification or quality control. These point clouds, which can be easily downloaded from Global Mapper’s Online Data tool, are great to use as a control for users who collect their data. Global Mapper’s Lidar QC and Fit Point Cloud tools allow users to measure and improve point cloud accuracy. By comparing the point cloud against GPS-collected ground control points or another point cloud with a known accuracy, the point cloud can be adjusted to better fit real-world measurements. These tools also allow for the easy merging of two separate point clouds and measuring between them.

Tree Extraction Settings
The extraction tool offers settings to adjust for different forest structures.
2d and 3d views of a forest side by side in global mapper
In Global Mapper’s 3D viewer, the generated 3D point features scale to match tree height, allowing for a virtual tour of the forest on top of any extra data present

Using the Measured Tree Heights

Once the tree heights have been measured, Global Mapper’s vector tools can be used to sort and categorize the point and area features. The Search Vector Data tool can be used to sort and count trees that fit in different height classes. Boolean operators are easy to use and give you the ability to set your height classes. After the tree points have been selected, they can be copied into their own layer. Heat maps can be created to identify clusters of trees, identifying dense areas that may need to be thinned, as shown in the screenshot below. These heat map grids use color to highlight areas of high and low point density.

Tree density heat map
The Create Heat Maps from Point Features tool maps densities of points or attributes such as tree height, highlighting any clusters of similar (red) or different (blue) heights.

Visualizing Spatial Patterns in Canopy Heights

A canopy height model (CHM) is a raster layer representing tree heights as a continuous surface. It represents the height of the tallest point above the ground without being affected by changes in ground elevation. CHMs can be easily made in Global Mapper Pro by creating a DTM (digital terrain model) representing the ground, a DSM (digital surface model) representing the trees, and subtracting them. More information and Step-by-step instructions for creating canopy height models are available in this blog.

Canopy height model
Visualizing the canopy heights of a forest as a whole helps to see trends across the entire stand.

Assessing Understory Vegetation

Vegetation that grows beneath the main canopy provides food and cover for wildlife. Measuring the height of this understory can be indicative of forest health, whether assessing young growth for stand replacement or determining a need for competition removal in a timber stand. Dense lidar, especially in leaf-off season, penetrates forest canopies to reveal the ground and understory. Global Mapper’s Path Profile tool is used to peak at these lidar points hidden beneath the canopy. In the images below, the path profile viewer shows how vegetation near the edge of roads has more sunlight, nourishing a dense understory layer, as compared to the middle of the forest, where the ground is shaded out.

The Path Profile tool is used to see data from a perpendicular perspective and assess ground cover and vegetation.

Digitizing Areas with Low Canopy Cover

Dense canopies create competition for sunlight, affecting future forest speciation by determining which trees become suppressed and eventually die out. Areas without canopy cover have increased availability of sunlight, allowing for the growth of a wider variety of plant species. These exposed areas are an important part of a healthy forest structure and, in older forests, can be indicative of forest health in terms of counting the number of fallen old-growth trees. Measuring these areas on foot is an arduous task, but in Global Mapper, acres of land are measured in a few minutes. By creating rasters from lidar data representing areas with forest canopy and the ground, the difference in areas between them is calculated and measured. In the data shown below, the rasters were assigned new values, vectorized, and then cut.

Swipe to see polygons demarcating areas without forest canopy cover created from lidar using Global Mapper’s elevation and vector editing tools.

Other land measurements beneficial to foresters can be extracted from lidar as well, including slope values derived from lidar-based elevation models that are used to highlight steep areas to be avoided. When planning a road, try using the terrain painting tool to visualize and then measure any soil that would need to be removed. For more information on measuring forests in Global Mapper, check out our other industry scenario on monitoring forest change


Global Mapper provides an innovative way for professionals involved in agriculture and other industries to perform a terrain suitability analysis for a variety of use cases. A few freely available data layers were used to identify areas suitable for vineyard development. Of course, not all site selection criteria can be analyzed in a GIS program. Site visits, advanced soil sampling, planning, and infrastructure implementation are all needed before beginning grape cultivation. The areas identified by this suitability analysis are now vector features with attributes describing slope, aspect, area, and soil type that can be further edited, exported, or taken into the field for further site exploration.
Want to try Global Mapper? Sign up for a 14-day free trial. You can also request a demo from one of our experts to see this workflow or other Global Mapper processing abilities.

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Atkins, J. W., Costanza, J., Dahlin, K. M., Dannenberg, M. P., Elmore, A. J., Fitzpatrick, M. C., Hakkenberg, C. R., Hardiman, B. S., Kamoske, A., LaRue, E. A., Silva, C. A., Stovall, A. E. L., & Tielens, E. K. (2023). Scale dependency of lidar-derived forest structural diversity. Methods in Ecology and Evolution, 14, 708–723.

De Petris, S.; Sarvia, F.; Borgogno-Mondino, E. About Tree Height Measurement: Theoretical and Practical Issues for Uncertainty Quantification and Mapping. Forests 2022, 13, 969.

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