Drone Lidar and The Use Case for Forestry

Author: Barry Gregg
Co-Author: Frank Segarra
December 14, 2022

Lidar (Light Detection and Ranging) is an active remote sensing technology used to measure distances and geospatial data with great precision. This technology provides horizontal and vertical information at high spatial resolution and vertical accuracy, offering opportunities for enhanced forest monitoring, management, and planning.

Lidar, as a high-accuracy detection instrument, can acquire measurements needed to produce three-dimensional point cloud models of forests with centimeter levels of accuracy. Critical information can be extracted directly from these Lidar point cloud models, and further calculations can be performed when coupled with other sources of forest inventory data. Using Lidar data, you can determine tree densities, stocking levels, and expected yield of a given area and perform regression analyses.

Using Lidar Data for Fire Modeling

Metrics and GIS information required to manage forests include identifying individual tree crowns, which can be used in fire modeling. Researchers also assess the mix of species within them with a system of measurements such as canopy bulk density and average height from ground level up until underneath canopy covering. This data provides an idea about how much space each type takes up relative to their own size compared to other species present within the same area/forest region etc. With these data points collected over time, we’re able to produce estimates that will help us avoid future problems caused by highly unpredictable natural disasters like fires.
Additionally, high-quality drone Lidar data allows clients the ability to perform a “digital walk-through” of the scanned area. During the walk-through, vital information can be extracted, such as stem, DBH (Diameter at Breast Height), canopy, undergrowth, and surface-to-canopy measurements. Lidar data can also be used to segment individual trees, classify areas of interest, and produce digital elevation and digital surface models even in dense and overgrown areas – allowing for a streamlined workflow and fewer trips to the site.

The Benefits of Both Aerial AND
Terrestrial Lidar for Forestry Scans

The Earth’s forests are an important global resource, playing key roles in both the environment and economy. There is increased focus on sustainable development as well as climate change mitigation with regard to tropical rainforests because they contribute so much towards our planet’s carbon cycle via photosynthesis processes affecting plant growth patterns worldwide – ranging from small-scale measurements using ground-based terrestrial laser scanning technology, all the way up through aerial Lidar which can provide depth perception for architects designing buildings within these areas.

Does the mystery still remain on which data capture methodology is best when it comes to aerial vs. terrestrial?

In the two images below, note the difference in point cloud density between the two collection methods. Simply put, aerial Lidar alone misses valuable stem and branch information while SLAM LIDAR (Simultaneous Localization and Mapping) lacks the ability to create dense point clouds near the tree canopy (the two methods work in tandem). Drone service providers who employ efficient collection and processing workflows to effectively combine SLAM data from the ground with Lidar information extracted in flight results in not only accurate informational extraction but also greater efficiency than any other method available.

Unclassified Lidar Data vs. Classified Lidar Data

Every Lidar point can have a classification assigned to it that defines the type of object that has been rejected. Lidar points can be classified into a limitless number of categories, including bare earth, top of the canopy, building, vegetation, powerlines, and water. The different classes are defined using numeric integer codes in the LAS files.

Unclassified Point Cloud

This full, unclassified point cloud displays all buildings, trees, and powerlines as a single point cloud.

Classified Point Cloud

After classifications, individual classes can be turned on and off, or all classes can be toggled off to view only the bare earth.

Common Forestry and Lidar Deliverables

Every Lidar point can have a classification assigned to it that defines the type of object that has been rejected. Lidar points can be classified into a limitless number of categories, including bare earth, top of the canopy, building, vegetation, powerlines, and water. The different classes are defined using numeric integer codes in the LAS files.

Contour Lines

(.dxf, .shp formats – CAD/ESRI ready)
CAD-Ready, geospatially accurate 3D Contour Lines

Digital Surface Model

(3D model of the surface with all trees and structures removed. Data is compressed into a TIN model for smooth CAD operations- .dxf format)
TIN surface of a dense forest created with Lidar data and processing. Exportable into AutoCAD

Digital Elevation Model

(.tif format)
Digital Elevation Model overlayed into GIS Software
Digital Elevation Model

SLAM Lidar Under-Canopy Forestry Scan

Figure 2 shows just how dense the forestry point cloud can be when collected with SLAM Lidar and subsequently paired with aerial Lidar. These collection and ground control methods have been tried and tested in the field, and our experience shows the most dense and accurate data.
Figure 2

Tree Segmenting

Using A.I., deep learning algorithms, and professional Lidar editing software, individual trees can be segmented and classified. This feature is extremely useful for end users who need to organize trees by grouping or performing analysis in a grid
or tile layout.

Lidar for Sinkhole Detection and Monitoring in Forest Areas

Sinkholes are a form of natural disaster that can be found all over the world. They’re typically located in karst regions (a type of landscape where the dissolving of the bedrock has created sinkholes), which have high levels of geology and hydrology activity to promote their formation through chemical dissolution from carbonate rock within its landscape – especially when there is also sufficient rainfall or groundwater recharge happening at one time. Scientists monitor these potentials by measuring things like velocity waves travel through earth tremors/seismic events, water content analysis around each specific sinkhole location, as well changes compared with surrounding areas’ readings. Tracking this information gives us insight into how often they occur over time and space. Given Lidar’s ability to penetrate dense vegetation to measure the ground below, it is the perfect tool to detect and measure sinkholes. Quarterly or yearly scans can be performed in order to monitor sinkhole progression, allowing for unprecedented site awareness and decision-making.
Subsurface view of 40'-70' deep sinkholes. The area above the sinkholes is covered by dense, impenetrable vegetation. Without Lidar, the full extent of the sinkholes would never be known.
Subsurface view of three large sinkholes near the base of a limestone quarry. The haul road between two of the sinkholes had to be reevaluated for safety and eventually shut down after the severity of the sinkholes became known.

How Geologists use Lidar Data

Have you ever wondered how geologists are able to create those detailed maps of the earth’s surface? Or how they are able to identify different types of rocks and minerals? It all starts with collecting data. In recent years, one of the most common ways geologists collect data is using Lidar. Besides forestry, Lidar data has been used for over fifty years to analyze geological phenomena that scientists can use to better understand the earth. 

Lidar was first used in the early 70s by NASA, which used the laser-based remote sensing technology in its development of exploratory spacecraft. Applications for Lidar continued to expand into gauging the properties of ocean water and the atmosphere for topographic mapping purposes. Other areas of geological study where Lidar technology is used include:


The information gathered from Lidar technology is invaluable for understanding the behavior of glaciers, especially those that are found in high concentrations or near mountain ranges. For example, Geologists can use this data when determining how much global warming may have occurred due to accelerating Sea Level Rise, along with other factors like moraines and outwash channels, which can be identified based on their findings.


Faults can be found anywhere, not just in faraway places. The earth’s surface is constantly changing, and there will always be areas where something happened that caused damage – like an earthquake or cavity at the bottom of a hill formed by underground water flow over time. Living in a region with faults does carry some risk; after all, humans are unable to control if or when the next catastrophe will strike. But, the information gathered from Lidar technology helps geologists study the earth’s surface to monitor changes that could signal a seismic event in the future.


By measuring how much soil erosion has occurred over time, scientists can determine the volume and depth of streams that have been altered by slides or gullies. With this information in hand, they are better able to map out which areas are the most susceptible to further damage due to their high erosion levels when compared to other regions nearby, which may not yet be showing signs of strain or damage.


Floodplains are essential to our environment, providing a home for many plants and animals. These areas also have unique natural features that make them beautiful when intact but can be damaged by floods or other events. In order to not wash away these delicate ecosystems, accurate maps are required by planners so they know exactly what’s at risk before making decisions on future developments near rivers.


Drone Lidar technology is amazing and has so many applications in different industries. Its use can enhance results while opening the door to a new phase of remote sensing. In the forestry sector, conservation biology, and other related areas, drone Lidar technology can be used to create more accurate maps, leading to less time required on-site for planning, photos, hand measurements, and conceptual design. The list of cost savings and enhancements that drone Lidar technology creates is massive!

If you have a project that you think could benefit from drone Lidar mapping services, don’t hesitate to contact us. We would be more than happy to discuss your specific project needs and see how we can help.

Barry Gregg

Barry Gregg

Barry Gregg is a Lidar Data Engineering Consultant and Chief UAV Pilot with over 10+ years of experience in the utility engineering industry.

Barry holds an FAA Part 107 Remote Pilot Certification, having logged hundreds of lidar, photogrammetry, and industrial inspection flight hours. An expert in aerial, static, and mobile lidar data collection and processing, his passion for the drone industry centers on projects focused on integrating the latest in geospatial data collection and visualization technology with new and aging infrastructure systems.

 Frank Segarra

Frank Segarra

Frank Segarra is the founder and CEO of ConnexiCore. He has over 30 years of IT, telecommunications and aviation industry experience and was a US Navy aircraft carrier airman specializing in Avionics Engineering. As a thought leader in drone technology, Frank was invited to be a founding member and CompTIA Drone Advisory Council. and is on the Board of Advisors for the PA Drone Association.