LiDAR & Point Cloud Engineering

LiDAR & Point Cloud Engineering

LiDAR point cloud engineering encompasses the full processing pipeline from raw sensor data to deliverable products: noise filtering, coordinate transformation, ground classification, feature extraction, and surface generation. Airborne, terrestrial, and mobile laser scanning platforms each produce billions of three-dimensional measurements that require systematic workflows to become actionable geospatial assets.

Automated and semi-automated classification algorithms separate ground returns from vegetation, buildings, power lines, and other features. Digital terrain models, digital surface models, and normalized height models derived from classified point clouds support volumetric analysis, flood modeling, vegetation canopy studies, and infrastructure clearance assessments. Breakline-enforced triangulated irregular networks ensure hydrological correctness in derived surfaces.

Quality assurance processes validate vertical accuracy against ground control, assess point density uniformity, and verify classification correctness through statistical sampling. Final deliverables conform to industry standards such as ASPRS LAS specifications and can be integrated into CAD, GIS, and BIM environments for downstream engineering and design applications.