LIDAR vs. Photogrammetry, Which One is Right for Your Project

Surveyors have several new tools and technologies at their disposal to capture existing conditions. For those just getting started, these options may seem overwhelming. There are several systems with varying pricing and capabilities. A major decision is whether to go with a LIDAR or photogrammetry workflow, as each has its pros and cons.

LIDAR workflows use laser scanners to capture existing conditions by shining a laser beam and measuring the distance it takes for that beam to bounce back. This creates an accurate representation of a space, known as a point cloud, even with poor lighting conditions. These point clouds are rich data sets that can be used in software programs to get measurements, assist with 2D drawings, and create a 3D digital twin. For interiors, LIDAR is ideal to capture a space.

Photogrammetry utilizes photos to capture data of an existing site. The differences between each photo are calculated by a software program like Bentley’s ContextCapture to create a 3D mesh model. Users can utilize a DSLR, iPhone camera, or aerial drone to capture a subject. Lighting should be consistent and clear. Photogrammetry is great at capturing exteriors and has become a popular solution for bridge inspections, site surveys, and construction tracking.

A major difference between LIDAR and photogrammetry workflows is the startup cost. LIDAR systems tend to be more expensive and require calibration that must be done by the manufacturer. Photogrammetry has a lower start-up cost because you can use a variety of different camera systems and scale up your production. However, photogrammetry does require proper acquisition techniques to ensure good overlap between photos. Many users are finding a combination of both systems to be beneficial, especially when required to capture interiors and exteriors. 

Bentley’s reality modeling software, ContextCapture, can take in both photogrammetry and LIDAR data. Learn more about how you can purchase a one-year subscription to ContextCapture through Virtuosity: 

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