Photogrammetry vs. LiDAR: A Technical Comparison for Aerial Mapping
- Anvita Shrivastava
- Jan 12
- 4 min read
Surveyors, engineers, and GIS professionals have had access to ever-increasing amounts of high-resolution spatial data created from aerial mapping technologies such as the above. Aerial mapping uses two main types of technology - photogrammetry and LiDAR (Light Detection and Ranging) - and these are the most commonly used methods for the creation of geospatial data and 3D models.
The primary difference between photogrammetry and LiDAR is how they collect the geospatial data. Both technologies collect 3D data via airborne vehicles like drones, helicopters, and airplanes; however, they do so in very different ways, resulting in significantly different degrees of accuracy, costs, and applications. In this article, we will compare the technical aspects of photogrammetry and LiDAR so that professionals will have some guidance on which method is the best fit for their specific projects.
What Is Photogrammetry?
Photogrammetry uses the technique of remote sensing to measure three-dimensional space through the overlap of two-dimensional photographs. To achieve this, high-resolution digital images (RGB, or multispectral) taken from either a drone or an airplane are processed through computer vision algorithms to find the same area in multiple images and reconstruct the spatial geometry. The reconstruction produces many outputs.
The Process of Photogrammetry
When taking aerial photographs for photogrammetric processing, the images should have significant overlap between adjacent images (approximately 70-90% overlap).
The photogrammetric process involves applying Structure-from-Motion (SfM) algorithms to identify and create "tie" points between overlapping photos.
The Bundle Adjustment step focuses on computing the position and orientation of the aerial camera when taking each image.
The last step involved in the photogrammetry is to produce several outputs, including orthomosaics, digital surface models (DSM), and dense cloud points.
Outputs of Photogrammetry
Orthomosaic maps
Three-dimensional textured meshes
Dense cloud points.
What Is LiDAR?
LiDAR is an active remote sensing technology that employs laser pulses to measure the distance to the Earth's surface from a sensor; therefore, it is typically defined as a laser rangefinder. LiDAR systems transmit thousands to millions of laser pulses per second, and with each returned laser pulse, LiDAR calculates an accurate three-dimensional (3D) point cloud.
LiDAR Operation
The laser pulse(s) are directed downward toward Earth.
The laser pulse(s) are reflected off various surfaces back to the sensor.
Time or flight is used to calculate the precise distance.
The facility to receive multiple returns enables penetration of vegetation.
The Primary Outputs Generated from LiDAR
Classified point clouds
Canopy Height Model
Photogrammetry vs. LiDAR: Technical Comparison
Accuracy and Precision
In terms of vertical accuracy, LiDAR has much greater variance (usually ±2–5 cm) than Photogrammetry, which is dependent on surface texture and lighting conditions.
Photogrammetry has very good horizontal accuracy, but it can suffer from shadow interference as well as low-quality images due to poor lighting conditions or non-uniform surfaces.
Winner: LiDAR (due to its use in precision-critical applications).
Vegetation Penetration
LiDAR rays penetrate through most forms of vegetation to reach the ground, making LiDAR a prime candidate for a wide range of applications (i.e., forestry, flood model production, terrain mapping, etc.).
Photogrammetry primarily captures surface items, so it is less effective when working in heavy vegetation areas.
Winner: LiDAR (due to its ability to penetrate vegetation).
Data Density and Classification
LiDAR generates very dense point clouds because they contain multiple returns and intensity readings, making it possible to automatically classify the various objects within the point cloud.
Photogrammetric point clouds are highly dense, but they do not provide much information regarding object classification; therefore, they require extensive post-processing before field work.
Winner: LiDAR (due to the high density of point clouds).
Texture and Visual Realism
Photogrammetry can produce authentic, texture-mapped 3D photorealistic models and the lateral map lookalikes.
While LiDAR has no actual color, if used in conjunction with RGB imagery, it can produce colored data.
Winner: Photogrammetry
Cost and Accessibility
Photogrammetry systems are based on standard digital cameras and are therefore considerably less expensive.
LiDAR sensors are very costly and need specialised calibration and processing experience.
Winner: Photogrammetry
Operational Requirements
Photogrammetry will work best when the lighting is good, and shadows are minimal, and the scanned surface is consistent.
Unlike photogrammetry, LiDAR will work with low light levels and even at nighttime.
Winner: LiDAR
Use Case Comparison
Application | Best Technology |
Topographic mapping | LiDAR |
Urban 3D modeling | Photogrammetry |
Forestry & vegetation analysis | LiDAR |
Construction progress monitoring | Photogrammetry |
Corridor mapping (roads, pipelines) | LiDAR |
Cultural heritage documentation | Photogrammetry |
Choosing Between Photogrammetry and LiDAR
The decision between photogrammetry and LiDAR depends on project requirements, accuracy needs, terrain complexity, and budget:
Choose photogrammetry when visual quality, cost efficiency, and high-resolution imagery are priorities.
Choose LiDAR when terrain accuracy, vegetation penetration, and reliable elevation data are critical.
In many professional workflows, hybrid approaches combining LiDAR elevation data with photogrammetric imagery deliver the best results.
Aerial mapping technologies are comprised of photogrammetry and LiDAR, both with significant strengths, and each has specific advantages over the other. To choose the best aerial mapping technology, you must understand the differences in accuracy, data structures, costs, and other operating restrictions for each technology.
With recent advances in drone payloads, sensors, and processing software will continue to improve the integration of photogrammetric data and LiDAR data, and improve future surveying, engineering, GIS, and geospatial analytics capabilities.
For more information or any questions regarding photogrammetry and LiDAR, please don't hesitate to contact us at:
Email:
USA (HQ): (720) 702–4849
Comments