Raw point clouds turned into classified, modelling-ready data, aerial, mobile and bathymetric, at volume and to your specification.
LiDAR and point-cloud volumes grow 30-40% a year, and in-house teams do not grow with them. Classifying ground, vegetation, buildings and power lines to a consistent schema takes domain expertise in coordinate reference systems and classification standards - exactly where generalist teams fall behind on aerial, mobile and bathymetric datasets alike.
Ground, vegetation, buildings and power lines classified to your class schema. LAS/LAZ.
Street-level point cloud classification, façade extraction, road surface modelling. LAS/LAZ.
Water surface and riverbed modelling, depth extraction, coastal and inland waterway mapping. LAS/LAZ.
| Inputs | LAS, LAZ, E57, raw flight lines |
|---|---|
| Outputs | Classified LAS/LAZ, DTM/DSM rasters, QA report |
| Standards | ASPRS class codes, or your project schema |
Send a real LAS/LAZ/E57 dataset. We classify it to your schema in 5 working days; you compare the output against your own baseline.
A paid classification project scoped to test the relationship: clear deliverables, an agreed timeline and defined quality criteria, typically 2-4 weeks.
Named engineers and a dedicated project manager on an established QA workflow, monthly retainer or per-project pricing, from around week 4-6.
Increase or decrease classification capacity as volume changes, month 2 onward, adding aerial, mobile or bathymetric workstreams as needed.
Digital elevation, terrain, and surface models from classified point clouds or survey data, delivered as TIN and raster output with contour generation and breakline editing.
1 to 10+ named engineers embedded in your workflow, with a dedicated project manager, scaling up or down monthly. No recruitment overhead, any format, any toolchain.