July 29, 2025

Lidar vs Photogrammetric Point Clouds: What’s the Difference?

Written by: Amanda Lind

 

Lidar point clouds and those derived from drone photogrammetry look and function similarly in Global Mapper Pro®, but have distinct differences. They can both be classified, features can be extracted, and they’re equally compatible with the vast lidar toolset the software is known for. Without examining the attributes, it can be challenging to distinguish them—the differences between the two stem from how they are created. Lidar can more accurately see through vegetation, but on its own, it lacks color and is more expensive to collect than photogrammetry. Knowledge of each data type’s strengths and limitations can help you better use your data to its full potential with Global Mapper.

Dense point cloud created by Global Mapper using drone photogrammetry data
Drone photogrammetry can create accurate and affordable high-resolution point clouds, but has limitations compared to lidar.

What is a Lidar Point Cloud?

Lidar, an acronym for light detection and ranging, is traditionally the more accurate data collection method for measuring terrain. Unlike photogrammetry, lidar can often penetrate vegetation and see the ground below to create a more detailed picture of the terrain and surface. A lidar sensor works by sending beams of light to the surface and back, calculating distance by measuring the time it takes for the beam of light to return. Sometimes the beam of light can fracture, where part of the beam hits a surface and returns to the sensor while the rest continues to the next surface. This creates multiple returns from the same beam of light. Return numbers are saved as an attribute that can be used in the analysis.

Lidar returns of trees displayed in Global Mapper
The top of the trees are the first returns (blue). The other returns are intermixed. The light reflected from the ground is a last return regardless of the return number.

This process makes lidar data ideal for creating digital terrain models in densely vegetated areas or when working with smaller and less visible objects or structures. The image below is a side profile of lidar data that has been classified. Notice that even in a densely forested area, the brown ground points are visible beneath the green trees.

Classified lidar point cloud displayed in Global Mapper
Lidar can detect the ground beneath vegetation and other penetrable structures.

*This forest lidar data was collected by the Latvian State Forest Research Institute ”Silava.”

Learn more about how Global Mapper users leverage lidar data to map forests:

What is a Photogrammetric Point Cloud?

While lidar is a direct measurement of the landscape, photogrammetry is an indirect measurement, as it derives locational and elevation data (XYZ) by triangulating from overlapping aerial imagery. What’s important is that photogrammetry can only map what is visible in the imagery. Continuing with our forest example, this means that in areas of dense forests where the canopy obstructs the camera’s view of the ground, no ground points can be created. This is photogrammetry’s most outstanding limitation. Learn how Pixels to Points works in Global Mapper and uses photogrammetric data to create points from aerial imagery.

Photogrammetric point cloud and a lidar point cloud of a forest
Compare a photogrammetric point cloud (colored by imagery) against a lidar (colored by returns). While lidar penetrated to and mapped the forest floor, photogrammetry could only map the top of the canopy.

Benefits of Drone Photogrammetry

When comparing lidar vs photogrammetry, the latter has the advantage over lidar in the ease of data collection. Despite the development of more portable lidar apparatuses, drone imagery is still the more affordable, and therefore a very popular, method of data collection. This accessibility allows users to measure areas more frequently, collecting more time-relevant data. Users can take advantage of this in Global Mapper to measure changes in the terrain over time, like erosion or habitat fragmentation. The Compare Point Clouds tool can be used to measure differences or detect changes between point clouds. While this is possible for lidar point clouds as well, photogrammetric point clouds are easier to gather at higher frequencies.

Another advantage is that drone photogrammetric point clouds are derived from imagery; they automatically include the color (RGB value) of the surface being measured. Colored point clouds are easier to visually interpret, classify, and they make for a more visually appealing product. Color can be manually added to lidar from an image, but those colors are not necessarily representative of actual ground color at the time of lidar collection.

Eventually, technological advancements will make drone-mounted and color-compatible lidar sensors more affordable and accessible, but for today, photogrammetry fills this data void.

Make a Point Cloud in Global Mapper!

Both point cloud types are great tools for mapping terrain and surface data, no matter what purpose you wield them for. When used together, they can create a complete view of the landscape. Understanding the differences between the two will help you make the best of your data and create higher-quality results.

Learn more about processing lidar and drone-collected data in Global Mapper Pro by downloading a free, 14-day trial!

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