LiDAR point clouds were classified to separate powerlines, vegetation, terrain and related utility features so infrastructure teams could assess risk and plan maintenance.
The challenge
Raw point clouds do not give planners immediate insight into clearance, encroachment or maintenance risk.
Powerlines, poles and vegetation require careful class separation because small errors can change risk interpretation.
The approach
SBL classified point-cloud features into utility-relevant classes and applied review rules for powerline and vegetation separation.
Outputs were structured for GIS and infrastructure workflows rather than one-time visualization.
Prepare
Organize corridor point-cloud data for utility classification.
Classify
Separate terrain, vegetation, powerlines, poles and related assets.
Review
Validate feature classes for GIS and planning use.
The result
Infrastructure teams gained classified corridor data that could support inspection, planning and vegetation-management decisions.
- Powerline and vegetation features were separated for analysis.
- Classified outputs supported GIS inspection workflows.
- Risk and maintenance planning became easier to ground in data.
- Quality review reduced misclassification in narrow infrastructure features.