01 · CLEAN
Noise review and preparation
Inspect source files, coordinate reference information, point attributes and obvious outliers before classification begins.
POINT CLOUD PROCESSING · CLASSIFICATION · QA/QC
Turn LiDAR point clouds into engineering-ready data.
GeoProcess Consulting supports geospatial teams with structured LiDAR processing, classification and deliverable preparation. We work with client-provided point clouds and project specifications to produce organized datasets that downstream GIS, utility, corridor and engineering teams can use.
LAS / LAZGround classificationVegetation
& buildingsDTM / DSMPower-line corridorsQA/QC
LIDAR / POINT-CLOUD PROCESSING
GPC
POINT CLOUD
ENGINEERING DATA
GIS INTELLIGENCE
POINT CLOUD CLASSIFICATION
OUR APPROACH
A structured workflow from source data to usable deliverables.
LiDAR processing quality affects every downstream product. A few classification errors can flow into terrain models, asset extraction and corridor decisions. Our workflow applies repeatable processing steps and review checks to help keep the outputs consistent with the agreed specification.
02 · CLASSIFY
Ground, vegetation and structures
Classify points into the project-required classes, which may include ground, low/medium/high vegetation, buildings, power lines and other infrastructure.
03 · DELIVER
Models, features and quality checks
Prepare classified LAS/LAZ, DTM/DSM products, feature layers or QA reports according to the project scope.
LIDAR PLATFORM TYPES
Three LiDAR platforms. Different views of the same world.
Platform, altitude, scan geometry and project conditions affect what a point cloud captures. GeoProcess Consulting processes client-provided datasets and aligns the outputs to the project specification.
ALS — Airborne Laser Scanning
LiDAR mounted on a crewed aircraft or helicopter. ALS is suited to regional terrain mapping, forestry, watersheds and long corridors because it covers large areas efficiently. Multiple returns can record canopy and, where laser pulses pass through gaps, ground points beneath vegetation.
- Typical use: broad-area terrain and surface models
- Processing focus: ground filtering, vegetation classes, DTM/DSM and corridor features
- Consideration: point spacing and detail depend on flight height, scan pattern, canopy and sensor settings
UAV-LS — UAV LiDAR
A laser scanner carried by an unmanned aerial vehicle. Flying closer to the target can produce dense, detailed point clouds for sites with complex terrain, embankments, stream banks, construction areas and vegetation structure. Density is mission-specific; values above 100 points/m² and higher are possible on some systems, but are not a universal guarantee.
- Typical use: detailed site, slope, drainage and vegetation analysis
- Processing focus: strip alignment, noise review, ground/structure classification and surface generation
- Consideration: trajectory, GNSS/IMU quality, calibration, flight plan and overlap affect consistency
MLS — Mobile Laser Scanning
LiDAR carried by a moving ground platform such as a vehicle, backpack or handheld rig. MLS is particularly useful for streets and transport corridors, capturing road assets, façades, signs, poles, trees and roadside structures from a ground-level viewpoint.
- Typical use: roads, rail corridors, streetscapes and asset inventory
- Processing focus: trajectory-aware alignment, classification, feature extraction and clearance-support layers
- Consideration: visibility and point density vary with distance, occlusion, speed and scan geometry
Choose the platform for the deliverable—not just the point
count.
ALS, UAV-LiDAR and MLS data have different viewpoints and coverage patterns. We review the supplied data, coordinate reference, required classes, intended DTM/DSM or feature outputs, and acceptance criteria before production.
VISUAL WORKFLOW / EXAMPLE OUTPUTS
See the data take shape.
Illustrative outputs from related geospatial workflows. Final deliverables are agreed to the project specification.
TYPICAL DELIVERABLES
Outputs aligned to the project specification.
- Classified LAS / LAZ point clouds
- Ground and non-ground classification review
- DTM, DSM and related elevation products
- Vegetation and infrastructure feature extraction
- Power-line corridor and clearance-support layers where specified
- QA/QC summaries and exception lists
Final classification classes, accuracy tolerances, software formats and acceptance criteria are agreed against the client’s specification before production.