Coloured level clouds and extra new options from Simactive

The Canadian mapping platform SimActive added several significant new features this year, including colored point clouds and reflective calibration. CEO Philippe Simard explains what these features are – and how customers use them.

SimActive releases new functions regularly. “As our user base grows exponentially, we constantly monitor how our software is being used and how it can be improved further,” says Simard. “Customer feedback is of central importance for the design of our product development.”

The latest versions of SimActive’s mapping software, which includes images from satellites, manned aircraft and drones, include several new features. Calibrated reflection maps can now be created from multispectral images using reflection fields and sun sensors. LiDAR data can now be merged with images. This is an efficient way of creating colored point clouds: assigning color information to each 3D point captured by the LiDAR sensor.

Reflection Calibration: Assessment of Vegetation Health in Precision Agriculture

Reflectivity is the amount of light that is reflected from surfaces (and detected by a multispectral sensor) relative to the incident light, explains Simard. “In order to precisely calculate the incident light, one possibility is to use sun sensors to evaluate how much light is being emitted. Another option is to take calibration patches for which the reflectivity is known and use that as a reference for calculating reflectivity for other surfaces, ”he says.

This is an important feature for drone service providers in agriculture. Reflection maps are widely used in agriculture to assess vegetation health. Enable early detection of abnormal changes in the growth process. “They can also help to locate stressed plants, measure plant productivity and predict future yield,” explains Simard.

Merge LiDAR with images for colored point clouds

LiDAR data provide very dense point clouds. When combined with images, these point clouds are a rich source of information that is often used by large companies. “One interesting application is corridor mapping for inspecting power lines,” says Simard. “Data can often be collected and used to monitor vegetation encroachment – which really minimizes the risk of power outages.”

The new functions of SimActive for merging LiDAR data with images represent a significant improvement in the generation of colored point clouds. “The greatest challenge when combining 3D points with images is to perfectly match both data sets,” says Simard. Typically this is achieved by manually marking ground control points. With the latest software version, however, SimActive has introduced a much more efficient method. “The LiDAR data are used directly as a reference and the images are automatically registered by adjusting the bundles,” explains Simard.

What’s next?

According to Simard, SimActive is preparing for industry growth by focusing on responding to customer needs. “We anticipate the future needs of the industry – and we see growing requirements for handling larger projects,” he says. “Our focus is on staying one step ahead of the competition and further increasing the processing speed in order to meet the large production requirements.”

Miriam McNabb is Editor-in-Chief of DRONELIFE and CEO of JobForDrones, a marketplace for professional drone services, and a passionate observer of the emerging drone industry and regulatory environment for drones. Miriam has written over 3,000 articles focusing on the commercial drone space and is an international speaker and recognized figure in the industry. Miriam graduated from the University of Chicago and has over 20 years experience in high tech sales and marketing for new technologies.
For advice or writing on the drone industry, email Miriam.

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