With mobile mapping technology readily available, anyone can effortlessly map the environment around them, whether it’s a cave, 10 storey building or a construction site. For newcomers to surveying, this tech breakthrough removes the dependency on trained experts – but it does require the mapper to have a basic understanding of a point cloud. What is it, how is it created and how is it used? In our latest education article, we look at the top point cloud questions and provide all the information you need to get started.
Point clouds are now faster, easier and more accessible than ever before. If you’re interested in mapping but aren’t trained in point cloud software – this guide is for you.
1. What is a point cloud? What measurements are included in a point cloud?
A point cloud is essentially a huge collection of tiny individual points plotted in 3D space. It’s made up of a multitude of points captured using a 3D laser scanner. If you’re scanning a building, for example, each virtual point would represent a real point on the wall, window, stairway, metalwork or any surface the laser beam comes into contact with.
The scanner automatically combines the vertical and horizontal angles created by the laser beam to calculate a 3D X, Y, Z coordinate position for each point to produce a set of 3D coordinate measurements which often includes its colour value stored in RGB (more on that in question 6) and intensity. These details can then be transformed into a digital 3D model that gives you an accurate detailed picture of your object.
The denser the points, the more detailed the representation, which allows smaller features and texture details to be more clearly and precisely defined. So, if you were to zoom in on a point cloud of The Tower Bridge in London, you’d see tiny points creating the whole point cloud.
What is Point Cloud Data?
Point cloud data is the term used to refer to the data points collected for a given geographical area, terrain, building or space. A LiDAR point cloud dataset is created when an area is scanned using light detection and ranging.
What is Point Cloud Processing?
Point cloud processing is a means of turning point cloud data into 3D models of the space in question.
3. How long does it take to create a point cloud?
It all depends on how many scans are needed and what exactly needs scanning. Or whether you’re using traditional stationary scanning equipment or a mobile laser scanner which would considerably reduce scanning time. For example, a 130-scan point cloud dataset (which is a lot of point cloud data) of an office building including all the individual rooms, corridors and service areas could take nearly 25 hours to process with a traditional, static laser scanner.
Those scans may have only taken a day to collect with a mobile scanner, but manual involvement in processing means that the registration of that point cloud dataset can take around 3 days to carry out, and potentially longer if manual correction is necessary. Smaller datasets can be processed in hours.
With a device like the ZEB Revo RT a point cloud is created in real-time and you can see the live visualisation progress with the attached tablet or phone. It requires no processing other than extracting data from the device, so you can have a full point cloud in a matter of minutes – depending on what’s being scanned.
6. Can a point cloud be created in colour – how?
When you look at a colourised point cloud of a room, you’re seeing both the dimensional measurements and the RGB value. This data is taken at each point the scanner measured. The effect is that users (both new and experienced) can understand quickly and easily what they’re looking at because the point cloud looks more like a 3D photograph. Cloud colour can simply be added via your chosen format.
7. How do you put multiple point clouds together?
Handheld 3D laser scanners are efficient enough that many spaces can be captured in a single scan. However, larger projects such as a large sports arena or campus may require more scans for complete coverage, which means you’ll have a number of point clouds that you’ll need to merge into one final point cloud for the whole asset. A variety of software applications enable you to do this. However, if you use a GeoSLAM laser scanner, it makes good sense to use GeoSLAM’s complimentary Connect software.
Within GeoSLAM Connect you have the stop-and-go alignment feature where common static points are captured during several scans meaning that these datasets can be automatically aligned. A single point cloud is then exported as if the data was captured in a single scan.
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