LiDAR — Light Detection And Ranging — is the sensor technology that lets engineers reconstruct the real world in centimetres instead of approximations. This guide walks through how an airborne laser scanner actually works, why it produces terrain models a camera physically can't, and what that means for projects where the ground matters.
An airborne LiDAR sensor emits hundreds of thousands of laser pulses every second toward the ground. When a pulse hits a surface — a leaf, a roof, a road, a rock — some of its energy reflects back. The sensor measures the exact time elapsed between emission and return, then converts that interval into a distance using the speed of light.
Combined with the aircraft's position (RTK / PPK GNSS) and orientation (inertial measurement unit) at the instant of emission, every return becomes a 3D coordinate in real-world space. Repeat that 500,000 times a second from a moving drone and you have a dense, geo-referenced point cloud of the entire site.
LiDAR generates its own illumination — it works at night, in shadow, under cloud cover, and through smoke.
Round-trip measurements are timed to better than a nanosecond, which is why range accuracy is measured in centimetres rather than metres.
A single emitted pulse can return multiple times from a vegetation canopy and again from the ground beneath — the feature that makes terrain modelling under tree cover possible.
Schematic, not to scale. A typical airborne mapping mission operates at 80–120 m AGL over a survey area, with the sensor firing 500,000+ pulses per second across a swathe that's several hundred metres wide.
Light can't pass through opaque leaves — but a dense laser scan doesn't need every pulse to reach the ground. It only needs enough of them to. Classification algorithms then separate ground returns from everything above, leaving a bare-earth surface beneath the canopy.
Every return. The raw point cloud captures both canopy surface and ground — useful for context, but the canopy obscures the bare-earth surface that engineering deliverables depend on.
The sensor records every detectable return — first, intermediate and last — for each emitted pulse.
Software algorithms (CSF, progressive TIN, etc.) iteratively distinguish ground returns from vegetation, buildings and noise.
Ground-classified points are interpolated into a DTM. Add canopy and structures back in and you get a DSM.
Photogrammetry stitches overlapping aerial photographs into a 3D surface using computer vision. It's excellent for bare, hard-edged sites — quarries, urban areas, completed earthworks — and produces photorealistic textures. But it fundamentally cannot see through any surface it can't image, which means vegetation, shadow and reflective water are blind spots.
LiDAR is the opposite: no texture, no colour by default, but a direct geometric measurement of every surface a pulse reached — including the ground beneath canopy, the edges of overhead powerlines, and detail under shadow.
The raw cloud is just the start. Engineering value comes from what we extract, classify and refine — and from how that flows into the CAD, BIM and GIS systems your team actually uses.
Geo-referenced LAS/LAZ — every classified return, ready for inspection and downstream extraction.
Bare-earth and surface raster/TIN models for design, modelling and visualisation workflows.
Survey-grade contours and 3D linework, delivered ready for Civil 3D, 12d and BricsCAD.
Cut/fill, stockpile volumes and cross sections against design surfaces or prior captures.
Answer six quick questions about your site, accuracy needs and required deliverables — we'll recommend LiDAR, photogrammetry, traditional survey or a hybrid workflow.