Point clouds and LiDAR data are increasingly being used for 3D modeling, terrain analysis, and digital twins. In this course, you’ll learn how to process, analyze, and visualize large amounts of point cloud data using Python. You’ll work with professional open-source libraries such as LasPy, PDAL, and Open3D to convert raw LiDAR data into actionable insights. This will help you develop practical skills for working with 3D geodata in GIS, infrastructure, and remote sensing.
LiDAR and point cloud data play a key role in GIS, surveying, infrastructure, 3D modeling, and digital twins. Using millions of measurement points, highly accurate models of terrain, buildings, and objects can be created.
In this blended learning course, you’ll learn how to process, analyze, and visualize LiDAR and point cloud data using Python. You’ll work with commonly used libraries for managing point clouds, performing 3D analyses, and generating spatial insights from large datasets.
The course is suitable for GIS professionals, surveyors, data analysts, and anyone who wants to learn how to work with 3D geodata. Thanks to the hands-on approach, you’ll not only learn the theory but also apply techniques directly to realistic datasets.
In this blended learning course, you’ll learn the fundamentals of LiDAR and point cloud analysis using Python. You’ll start by importing, managing, and visualizing point cloud data and learn how these datasets are applied in geospatial projects.
Among other things, you’ll learn to work with libraries such as LasPy and PDAL for processing and managing LAS and LAZ files. You’ll then discover how to filter, classify, and prepare large point clouds for further analysis.
You’ll also work with Open3D, PyntCloud, PyVista, and Trimesh for 3D visualization and geometric analysis. You’ll learn how to generate terrain models, detect objects, and analyze spatial patterns within point cloud data. You’ll also gain insight into processing LiDAR data for applications in infrastructure, surveying, and spatial modeling.
In short: this course is ideal for anyone who wants to use LiDAR and point cloud data for 3D analysis, terrain modeling, and advanced geospatial applications.
Blended learning combines self-paced online learning with hands-on guidance. You’ll gain access to online course materials that allow you to learn how to work with LiDAR data, point clouds, and 3D analysis techniques at your own pace. The theory is supported by practical assignments, allowing you to immediately practice with realistic datasets.
During the guided sessions, you can ask questions, get additional explanations, and work on assignments related to applications in GIS, surveying, infrastructure, and 3D modeling. You’ll learn how to process, visualize, and analyze point clouds to extract actionable insights from large datasets.
Upon completion of this course, you’ll have a solid foundation in LiDAR and point cloud analysis using Python. You’ll be able to independently process point cloud data, generate 3D models, and perform spatial analyses for a wide range of geospatial 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.
