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LiDAR

Mobile Mapping

Vehicle and backpack LiDAR processing for corridors, highways, rail and urban survey.

Mobile Mapping — representative deliverable
Overview

Mobile Mapping

Mobile mapping trades absolute accuracy for extraordinary coverage rate. The processing challenge is recovering that accuracy: GNSS degradation under canopy and in urban canyons, IMU drift on long runs, and misalignment between overlapping passes all have to be resolved before any feature extraction is worth doing.

We process from raw trajectory and scanner data — tightly coupled trajectory adjustment, strip adjustment between passes, control tie-in and residual reporting — before classifying and extracting. Getting that order right matters; features extracted from an unadjusted cloud inherit every trajectory error.

From there we extract what you need: road and rail asset inventories, kerb and edge-of-pavement strings, signage and furniture, clearance envelopes, surface condition surfaces and cross-sections at whatever interval the design requires.

What you receive

Every item below is issued in your own template, with your layer conventions, title block and revision scheme.

  • Trajectory adjustment and strip alignment with residual report
  • Control tie-in and absolute accuracy verification
  • Classified cloud — road surface, kerb, vegetation, structures, furniture, wires
  • Feature extraction — signs, poles, drainage, markings, barriers
  • Rail-specific extraction — track centreline, cant, ballast, catenary, clearance envelope
  • Kerb, edge-of-pavement and channel strings as 3D polylines
  • Cross-sections at the specified interval
  • Surface model and pavement condition raster
  • Asset inventory with attributes and geolocation
  • Panoramic imagery linkage where imagery was captured

Production detail

Key production parameters for Mobile Mapping
Typical turnaround150–400 km per month per team by extraction depth
Platforms handledVehicle-mounted, rail trolley, backpack, handheld SLAM
Absolute accuracyTypically 2–5 cm with good control; reported against check points
Relative accuracy1–2 cm within a pass
Extraction intervalCross-sections at 5 m to 50 m as specified
Output formatsLAS / LAZ, RCP, E57, DWG, GDB, SHP, LandXML, GeoTIFF
RevisionsTwo rounds included

Software and formats

We work in your toolchain. If something you use is not listed, ask — the list below is only what we use most.

Trimble Business CenterTerraScanLeica CycloneOrbit GTGlobal MapperCivil 3DArcGIS ProPython / PDAL

Frequently asked

With good GNSS conditions and adequate control, two to five centimetres absolute and one to two centimetres relative within a pass. Urban canyons and dense canopy degrade the absolute figure, which is why control tie-in and residual reporting are part of the standard deliverable rather than an option.

Yes — vehicle-mounted, rail trolley, backpack and handheld SLAM systems, working from raw trajectory and scanner data or from a pre-registered cloud. Raw data gives us more to work with when accuracy needs recovering.

Yes — track centreline and cant derivation, clearance envelope generation to the applicable gauge standard, and exceedance reporting by location with the measured intrusion. Cross-sections at your specified interval come as part of it.

Through tightly coupled trajectory processing, control tie-in at intervals through the affected section, and strip adjustment between overlapping passes. Where accuracy still cannot meet the specification, that section is flagged with its achieved accuracy rather than delivered silently.
Step 4 of 4 in LiDAR

Send one mobile mapping job and see how we work

Scope, price and programme come back in writing before anything starts. Most first projects are a single deliverable so you can judge us on output, not on a pitch.

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