High-density LiDAR data across Germany was classified into terrain, vegetation, powerline, mast, vehicle and underground feature classes for engineering and municipal use.
The challenge
The scale of the terrain required consistent classification across thousands of tiles.
The project needed subtle feature separation, including masts, powerlines, vegetation, vehicles and underground points.
The approach
SBL structured the LiDAR workflow around defined classification classes, tile-level consistency checks and feature-specific review.
The team prepared LAS outputs that engineering and municipal teams could inspect and use downstream.
Ingest
Organize high-density point-cloud tiles for classification.
Classify
Separate terrain, vegetation, utilities, vehicles and underground features.
Deliver
Validate and package LAS outputs for engineering use.
The result
The client received a classified regional point-cloud dataset that could support planning, engineering and municipal analysis.
- Large terrain volumes were processed within a defined delivery window.
- Complex feature classes were separated for practical use.
- LAS deliverables supported engineering workflows.
- Quality checks helped maintain consistency across the region.