Rendering LiDAR and 3D Geodata

LiDAR and 3D city data are expensive to acquire, then often presented as flat, noisy screenshots. The problem is rarely the data. Points have no surface, no shading and no depth cue unless the rendering adds them, and default viewer settings do not.

This course covers the full pipeline, from preparing the data to producing a finished video: subsampling and normals, derived products (DTM, DSM, sky-view factor), lighting techniques that make geometry readable (splatting, Eye-Dome Lighting, sky-visibility shading), colour mapping, camera animation, and real-time GPU shaders for effects that standard tools cannot produce, such as geometry-driven colour transitions, voxelisation or city models rising from the points.

The methods apply whether you work in CloudCompare, OpenScanTools, Blender or your own code. You learn why each technique works, when to use it and how to set its parameters, so you can reproduce the results on your own data for reports, conferences, clients and publications.