The generation of Point Cloud data is not only limited to LiDAR. Another helpful technology called photogrammetry also assists different industries in creating 3D models (Data source: Example of photogrammetry inaccuracies DJI P4 RTK).
In this article, we will look at how photogrammetry is being used in point cloud data.
What is Photogrammetry
When combined, it is also known as the measurement of light recordings in the form of images.
Historically, photogrammetry used to create maps of different locations. Modern photogrammetry has led experts to render 3D information just by gauging distances available in 2D pictures.
Photogrammetry mainly uses the science of geometry and optics to obtain data. Metric and interpretative branches divide it into two.
Metric tackles accurate and precise computations regarding the x, y, and z coordinates of a subject. On the other hand, interpretative touches classification and identification of different attributes seen in the photo.
Three things are necessary to start photogrammetry: a camera, a measurement tool, and result storage. The camera is for the capture of multiple images, the measurement is to compare the distances of the photos, and the result storage acts as the medium that deposits observations.
Photogrammetry uses multiple camera views to gauge slight or major differences in measurements. With the help of multiple perspectives, it results to an exact 3D representations.
The same process happens in the human eye. As humans have two different sources of information, we grasp depth, distance, and spatial coordinates.
Since computers are not limited to only two images, they gather and render more precise and accurate data.
Types of Photogrammetry in Point Cloud
Two types of photogrammetry exist, and these are terrestrial and aerial.
When a camera is handheld or attached to a tripod and then used to gain measurements inland. It uses ground-based photographs for recording.
On the other hand, cameras attached to vehicles capable of flight such as UAVs, hot air balloons, or drones identify as aerial photogrammetry tools.
To greatly benefit from the point cloud measurements taken from a photogrammetry process, post-processing is necessary.
Platforms that allow classification of objects, conversion to 3D models enable this to happen, including clean-up of noise in each data set.
While traditional processing software is widely used for these tasks, they present many limitations. First, they require heavy-duty workspaces to accommodate the rendering process. Another is that licenses for these platforms usually cost thousands of dollars.
Datasource: Device, Topcon GLS2000
ScanX, a web-based point cloud post-processing software, removes these cons. It is an easy-to-use, intuitive, and collaborative system full of automated workflows.
Photogrammetry vs. LiDAR in Point Cloud
One major advantage of LiDAR with photogrammetry is its core concept. While LiDAR relies on lasers generated by a scanner, photogrammetry has no inherent light source and only bases on captured images.
Another is that LiDAR can penetrate between gaps of different objects such as vegetation. This enables better surveying in cases where many leaves or trees are present.
In terms of color accuracy, photogrammetry is superior since it makes use of already captured photos to generate digital twins. This is not present in LiDAR since it uses laser bits to get an overall sense of an area. Thus, photorealism is possible when dealing with photogrammetry.
Another major difference is that LiDAR has a faster processing speed, and its measurements are less taxing to compute since timing systems, GPS, and IMUs are already embedded.
Above is a laser scan taken at the onset of a mudslide disaster in Atami City, Shizuoka that was post-processed with ScanX. With the swiftness and accuracy of our platform, concerned Japanese organizations, as well as the government, quickly responded to address issues. Not only that but the total damages was also estimated.
Softwares gather total area and canopy sizes with processed point clouds from photogrammetry. Powerful tools such as ScanX can even segment trees separately to count them or determine their respective trunk size, tree height, and even diameter.
Best Photogrammetry Point Cloud Processor
ScanX is an amazing web-based platform that uses advanced algorithms to process point clouds taken from photogrammetry. It features an intuitive and easy-to-learn platform that encourages collaboration.