Multi Cloud Operations & DevOps / SRE
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Point Cloud Processing
Billions of points—and now…?
3D point clouds can be generated from images using photogrammetric methods and dense matching algorithms, or with Light Detection And Ranging (LiDAR), also referred to as Laser Scanning. Both approaches deliver measurements with a tremendous degree of detail. Point clouds are used in many fields of technology and application areas: construction, quality evaluation and assurance, environmental monitoring, agriculture and forestry, to name but a few. Objects described by point clouds can be as small as a few millimeters, or as large as whole cities, including buildings, roads, trees and cars.
Next to the coordinate information, they may also include colour, mapped to every single 3D point, thus giving a very realistic presentation.
Point clouds are often the basis for highly accurate 3D models, which are then used for measurements and calculations directly in or on the object, e.g. distances, diameters, curvatures or cubatures. They are therefore a great source of information in 3D feature and object recognition, as well as in deformation analysis of surfaces.
BUT: the data amounts generated by modern sensors are huge!
The question is: How can one efficiently and effectively work with those data sets?
OPALS: The toolbox for point clouds
OPALS—which stands for Orientation and Processing of Airborne Laser Scanning data—is a modular program system developed by the Research Group of Photogrammetry and Remote Sensing of the Vienna University of Technology. It is specifically designed to provide a complete toolbox for processing of 3D point cloud data.
We use its modular component-based system to create analysis workflows for various tasks: georeferencing, quality control, point cloud classification, structure line extraction, and DTM generation. These are important processing steps for several fields of application like forestry, hydrology/hydraulic engineering, city modelling and power line extraction.
OPALS enables our processing chains to run with the necessary degree of automation—extracting information from billions of points without user interaction. At the click of a button.
Combining OPALS with supercomputing power
Together with the Earth Observation Data Centre (EODC), Catalysts maintains and operates a private cloud computing infrastructure, featuring several hundred CPU cores and multiple Terabytes of RAM. Moreover, we can exploit the resources of one of Europe’s most powerful high performance computers: The Vienna Scientific Cluster 3 (VSC-3). 32.000 CPU cores put the VSC-3 among the top500 supercomputers in the world.
Being connected to a multi-Petabyte data storage system, this environment represents the ideal backbone for large-scale analysis of high resolution 3D point cloud data. It provides the unique capability to finish your analysis on time and on budget.
Want to know more about our processing service? Do not hesitate to contact us and we will be in touch!