SimActive Adds Lidar to Point Cloud Processing Solution - 11/12/2019


In response to the growing use of Lidar, photogrammetry software developer SimActive has integrated a new Lidar workflow in its Correlator3D product. The capability enables users to import a point cloud in the software and to perform registration with an image dataset. Using Lidar as control eliminates the need for traditional ground control points (GCPs) during image processing.

Registration occurs during aerial triangulation, leading to a precise alignment of imagery with the Lidar data. Following this, Correlator3D can output colourized point clouds as well as seamless orthomosaics. “Removing the need to manually tag GCPs facilitates the integration of Lidar data with imagery,” says Dr Philippe Simard, president of SimActive. “Our clients can benefit from different data sources, with perfect co-registration.”

“The majority of organizations using Lidar sensors also collect imagery during their projects. Consequently, a lot of SimActive’s clients had a need to integrate Lidar data as part of their photogrammetric worklow.  Adding such functionnality was the natural next step for us,” Simard continues.

Rising trend in Lidar use

Philippe Simard: “With Lidar sensors becoming small enough to be mounted on drones, we definitely see a rising trend in their use. We have an exponentially growing number of drone firms using our software in the last couple of years, which means there also will be an increase in Lidar users. Developing the right tools for them to integrate such data was definitely part of our plans.”

When asked about SimActive's future plans related to Lidar, Philippe Simard replies: “We've always regarded Lidar and imagery as complementary sources of information. Since they are often collected together, being able to process them simultaneously is a definite plus. The new Lidar workflow that we introduced was thus a beginning for us, and we will keep adding functions to help our users with their projects in the future.”

Last updated: 28/11/2020