3D scanning makes it possible to quickly capture objects, buildings, and sites in three dimensions with a high level of detail. In this Blended Learning course, you’ll learn how various scanning techniques work, how point clouds are constructed, and what factors influence the quality of the measurements. You’ll also learn how point clouds are processed, verified, and used for 3D models and applications in geodesy, construction, infrastructure, and Geo-ICT.
During this Blended Learning course, you’ll be introduced to 3D scanning and working with point clouds. You’ll discover how laser scanners and other sensors can be used to collect large quantities of three-dimensional measurement points, allowing objects, buildings, infrastructure, and entire sites to be captured in great detail.
The focus is on the entire data chain: from performing a scan to registering, verifying, processing, and visualizing point clouds. You’ll learn how raw 3D measurement data is ultimately converted into usable geographic information.
A laser scanner measures a large number of distances between the scanner and objects in the environment. By simultaneously recording the direction of each measurement, three-dimensional coordinates can be calculated for every measured point.
You’ll learn the basics of how different measurement principles, such as time-of-flight and phase shift, are used to determine distances. You’ll also be introduced to concepts such as scan resolution, measurement range, accuracy, and reflectivity.
A modern laser scanner can collect millions of points in a short amount of time. Together, these points form a detailed three-dimensional point cloud of the environment.
The goal is not to become a specialist in a single type of laser scanner. The focus is on understanding how 3D measurement data is collected and which factors determine the quality of a scan.
3D scanning can be performed from various platforms. In Terrestrial Laser Scanning (TLS), the scanner remains in a fixed position during the scan. This allows for highly detailed measurements of, for example, buildings, structures, and industrial facilities.
In Mobile Laser Scanning (MLS), the scanner is mounted on a moving platform, such as a vehicle. GNSS and inertial sensors are used to determine the scanner’s position and orientation while in motion.
Airborne Laser Scanning involves surveying from an airplane, helicopter, or drone. This allows large areas to be surveyed in a short amount of time.
You will learn the differences between these methods and explore which technique is suitable for various types of applications.
It is usually not possible to fully scan an object or area from a single position. Therefore, multiple scans are often performed from different locations.
These individual scans must then be merged. This process is called registration. You’ll learn how corresponding points, targets, or other recognizable objects can be used to merge different scans.
In addition, the point cloud often needs to be linked to an existing coordinate system. This is called georeferencing. For example, known ground control points or GNSS measurements can be used for this purpose.
You’ll discover why proper registration and georeferencing are essential when point clouds need to be combined with other geographic data.
A point cloud can contain millions of measurement points, but a large number of points does not automatically mean that the dataset is accurate or reliable.
You’ll learn which factors influence the quality of a laser scan. These include distance to the object, the angle of incidence of the laser beam, the reflective properties of materials, moving objects, and obstructions.
You’ll also examine point density, overlap between scans, and potential discrepancies during registration and georeferencing.
This will teach you not only to visually examine a point cloud but also to critically assess its quality and suitability for a specific application.
A raw point cloud is usually not the final product. The data must be processed before it can be effectively used in GIS, CAD, BIM, or other applications.
You’ll be introduced to techniques for filtering, classifying, and segmenting point clouds. This allows you, for example, to distinguish between ground level, buildings, vegetation, and other objects.
You’ll also explore how to create elevation models, profiles, cross-sections, surfaces, and 3D models from point clouds.
The course covers common data formats such as LAS and LAZ, as well as methods for efficiently storing, exchanging, and processing large point clouds.
During the Blended Learning component, you’ll work with provided point clouds to go through the various steps from raw measurement data to usable 3D information. You’ll examine the structure and quality of datasets and process point clouds within Geo-ICT software.
You’ll work on assignments such as:
By the end of the course, you will understand how 3D scanning works, how point clouds are constructed, and which factors influence the quality of 3D measurements. You will be able to explain how different scans are registered and georeferenced, and how raw point clouds are processed into usable 3D information for surveying, construction, infrastructure, and other Geo-ICT applications.
You’ll receive 1-on-1 guidance. After signing up, our course coordinator will contact you to schedule your first session.
Do you have questions about the course content? Or are you unsure whether the course aligns with your learning goals or preferences? Would you prefer an in-house or private course? We’d be happy to help.
