Point cloud is used around the globe in a variety of industries, from construction and engineering to highway planning and the development of self-driving cars. Point clouds allow technology to interpret and represent 3D spaces through 3D digital images.

So, what is a point cloud?

A point cloud is a collection of data points defined by a given coordinates system. In a 3D coordinates system, for example, a point cloud may define the shape of some real or created physical system. Point clouds are used to create 3D meshes and other models used in 3D modelling for various fields including medical imaging, architecture, 3D printing, manufacturing, 3D gaming and various virtual reality (VR) applications.

As the world’s gone digital, so too has technology, being used ever more in construction and planning projects. 3D images representing real-world objects, landscapes and spaces are being generated by software and displayed digitally. But for these images to be created, we first need to be able to read and identify their dimensions. That’s where point cloud data comes in.

Point clouds are a series of different “points”, similar to pixels in a digital picture. Each pixel is made up of two coordinates – X and Y, while a LiDAR point is made up of three coordinates — X, Y and Z — which refers to a specific position in a three-dimensional space.

Point clouds can be created in the following ways.

LiDAR (Light Detection and Ranging) technology uses light to measure distances and dimensions. Time of flight LiDAR (the most popular method) works by sending a pulse of light from a laser. Each pulse is measured and added to the point cloud. Once the entire space or landscape has been measured, the point cloud can be used to create a 3D map or CAD model.

Point clouds can also be collected using photogrammetry, which uses multiple photos, taken from various angles, to calculate points. Photogrammetric point clouds give each point an RGB value, which then creates a colorized point cloud.

Both photogrammetry and LiDAR point cloud generating systems are popular. Typically, photogrammetry systems are cheaper, but LiDAR systems are much more accurate. The correct choice depends on the application of your project.

Point cloud data can be used to bring coordinates to life in the form of a 3D CAD (Computer-Aided Design) image. For example, if a point cloud has been collected from a highway, once the data is added to point cloud processing software, it can be transformed into a digital model of the road. The 3D model will include not just the transport corridor but also its surroundings, such as buildings, road signs, trees, and curbs.

3D CAD models can also include moving parts, such as cars, so that users can see how they will interact with the existing structures and how they might be affected by certain changes.

By using point cloud data in conjunction with point cloud processing softwares, we can, not only create 3D models, but also identify risks and create solutions. This could be not just more efficient, but potentially life-saving.

When planning, measurements, and experiments can take place safely in the digital point cloud environment, time and money can be saved.

Disclaimer : The views and opinions expressed in the article belong solely to the author, and not necessarily to the author's employer, organisation, committee or other group or individual.