Photogrammetry vs. LiDAR: Choosing the Right Tool for the Job, with Dr. Philippe Simard

SimActive Inc. has played a pivotal role in the evolution of geospatial data processing since its founding in 2003. Leading the company is Dr. Philippe Simard, a pioneer in the industry with a doctorate in electrical engineering from McGill University, specializing in computer vision. Under Dr. Simard’s leadership, SimActive’s flagship software, Correlator3D™, has become a trusted solution for governments, military organizations, and mapping firms in over 100 countries. His early innovations in photogrammetry and LiDAR integration have positioned SimActive at the forefront of the field, earning him accolades such as the Young Innovator Award from the Networks of Centres of Excellence.

Recently, DRONELIFE interviewed Dr. Simard for his insights about a frequently misunderstood concept in drone mapping: photogrammetry vs. LiDAR

Comparing Photogrammetry and LiDAR: Expert Insights

Dr. Philippe Simard’s expertise in both photogrammetry and LiDAR is rooted in decades of research and practical development. “With a PhD in computer vision, I had explored photogrammetry and LiDAR during my graduate studies in the late 1990s,” he explains. “And then with SimActive, one of the first things we developed included tools for registering images to LiDAR”.

When discussing the fundamental differences between these technologies, Dr. Simard notes, “Photogrammetry uses passive sensors to measure light reflected from surfaces, generating detailed point clouds from imagery. LiDAR, an active sensor, emits laser pulses to capture precise 3D geometry, excelling in penetrating vegetation for accurate ground mapping.” He adds, “Photogrammetry shines in large-scale projects due to its rapid data collection and rich visual output. Both achieve comparable accuracy, but LiDAR’s edge lies in vegetated areas, while photogrammetry offers cost-effective scalability for broader regions”.

Fusing Technologies for Superior Results

SimActive’s Correlator3D™ is designed to harness the strengths of both photogrammetry and LiDAR. “Correlator3D seamlessly integrates LiDAR and photogrammetry data through advanced aerial triangulation, ensuring precise co-registration,” Dr. Simard says. “Imagery provides color information, while LiDAR delivers accurate geometry. The software aligns datasets by using LiDAR as a reference, colorizing point clouds and generating orthomosaics from LiDAR-derived DTMs. This fusion creates visually rich, geospatially accurate outputs, surpassing the limitations of single-technology approaches by combining detailed visuals with precise 3D structure”.

Choosing the Right Tool for the Job

For drone operators, the choice between photogrammetry and LiDAR depends on several factors. Dr. Simard advises, “Drone operators should evaluate project size, environmental conditions, budget, and required deliverables. LiDAR excels in densely vegetated areas, such as mapping terrain beneath forest canopies, and can operate in low-light conditions, like nighttime surveys. Photogrammetry is ideal for large-scale projects, such as urban mapping or agricultural monitoring, where budget constraints favor its simpler, cost-effective workflows. Choose LiDAR for ground-focused precision; opt for photogrammetry for expansive, visually detailed outputs”.

He emphasizes that while both technologies can deliver high accuracy, their operational strengths are distinct. “If your work involves large areas or visual deliverables, invest in photogrammetry for its affordability and versatility. For projects requiring precise ground mapping in challenging environments, prioritize LiDAR”.

Cost and Workflow Considerations

The decision between photogrammetry and LiDAR is also influenced by cost and workflow complexity. “LiDAR systems are more expensive, requiring complex, high-cost equipment and intricate post-processing, which increases operational expenses,” Dr. Simard explains. “Photogrammetry relies on affordable cameras and streamlined, often automated workflows, making it more cost-effective. However, projects demanding high accuracy or complex deliverables may require skilled personnel for photogrammetry, raising costs. LiDAR’s operational complexity suits specialized tasks, while photogrammetry’s simplicity supports broader, budget-conscious applications”.

Integrating LiDAR into Photogrammetry Workflows

For professionals looking to enhance their photogrammetry workflows with LiDAR, Dr. Simard offers practical advice: “Successful integration hinges on precise co-registration. In Correlator3D, import LiDAR data first, convert intensity data into raster images, and identify tie points linking features visible in both LiDAR and imagery. These tie points act as ground control during aerial triangulation, aligning datasets perfectly. This approach ensures LiDAR’s geometric precision enhances photogrammetry’s visual richness, creating robust, unified datasets for superior mapping outcomes”.

He further notes, “Removing the need to manually tag GCPs facilitates the integration of LiDAR data with imagery. Our clients can benefit from different data sources, with perfect co-registration”.

The Future: Complementary Technologies

Looking ahead, Dr. Simard sees photogrammetry and LiDAR as increasingly complementary. “Photogrammetry and LiDAR are increasingly complementary, not competitive. Future advancements will enhance their integration, enabling hybrid workflows for diverse applications,” he says. He also addresses a common misconception: “A common misconception is that one technology universally outperforms the other. In reality, project needs dictate the choice—LiDAR for vegetation-heavy ground mapping, photogrammetry for large-scale visual outputs, or both for comprehensive results. Educating clients on their synergy dispels myths and optimizes project outcomes”.

Software Innovations for Both Technologies

SimActive continues to innovate with its latest software release. “Correlator3D version 10.4 introduces texturized mesh generation, triangulating point clouds from either photogrammetry or LiDAR and applying imagery for visually stunning, georeferenced 3D models. This feature enhances both technologies, allowing users to create detailed, accurate 3D products. The software’s flexibility ensures seamless processing of diverse data sources, empowering users to deliver high-quality results tailored to their project needs”.

Final Recommendations

In summary, Dr. Simard encourages drone operators to carefully assess their project requirements and remain open to hybrid solutions: “Ideally, consider hybrid capabilities with Correlator3D to leverage both technologies, maximizing flexibility and delivering superior results across diverse applications”.