Every demo on this page is a live, working visualisation built from real spatial logic. Drag the slider below to wipe between what a camera captures (DSM with canopy) and what multi-return LiDAR recovers (bare-earth DTM). Then scroll for the rest of the capability gallery.
Same site, same flight, same point cloud. The DSM on the left is everything the laser hit first — canopy tops, building roofs, parapets. The DTM on the right is the bare-earth surface recovered by multi-return capture and ground classification. The DTM is what civil, hydrology and design teams actually work from.
Each visualisation below is the real, working interactive from its home page — interact directly, or follow the link to see it framed by its full engineering context.
An airborne LiDAR sensor fires laser pulses at the ground and times the return. Range derives directly from elapsed nanoseconds and the speed of light — the physics is simple, the engineering is in doing it half a million times per second from a moving drone.
Open the LiDAR primerToggle existing surface → design overlay → cut/fill with live cubic-metre readouts. This is what an estimator, earthworks contractor or QS wants — a quantified bill of earthworks from two captured surfaces, not a spreadsheet estimate.
See in civil construction contextExisting surface. A LiDAR-derived DTM samples the ground every few centimetres across the entire site — no GPS tracks, no missed swales, no assumptions.
“Can LiDAR see through trees?” isn't the right question. Multi-return LiDAR doesn't need every pulse to reach ground — it just needs enough of them to. The toggle here surfaces the DSM-vs-DTM distinction every spatial buyer needs to understand.
Read the full classification explainerEvery 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.
D8 steepest-descent flow direction computed per cell from the captured DTM. Toggle modes to switch from base DTM to flow direction to a derived stream network. Click any cell in catchment mode — the upstream contributing area appears with a rational-method peak flow estimate.
Open the drainage applicationStream network. Cells with flow accumulation above threshold rendered as a defined channel network. Brighter / thicker = more upstream area contributing.
The complete list. Each card jumps to the page where the visualisation is framed by its engineering and commercial context.
Animated 25k-point terrain with elevation-coded sweep — the homepage hero.
Schematic LiDAR pulses with metric readouts — range, round-trip ns, pulse rate.
Toggle between all returns, vegetation only, and ground-classified DTM.
Six-question wizard recommending LiDAR vs photogrammetry vs traditional vs hybrid.
Existing surface vs design surface with cut/fill regions and live volumetrics.
Four monthly captures of an evolving open pit — auto-play through reconciliation.
Same pile, three baselines, three volumes — visualising the base-assumption gap.
Plan view + cross-section across five station types (cut, fill, bridge, culvert).
Static + kinematic gauge envelopes across at-grade, overbridge and tunnel sections.
Three sag profiles + ground clearance + vegetation breach for a single span.
Substation yard with seven togglable LiDAR-derived layers.
Same field, four lenses — CHM, fuel hazard, clearance breach, biomass.
AEP presets + scrubbing slider, with cross-section + FFL breach flagging.
D8 stream network + click-anywhere catchment delineation + rational-method Q.
Slope class → buildable area → indicative lot yield from one DTM.
Conveyor gallery with raw cloud, classified, dimensions, defect modes.
Four-capture rehabilitation timeline with delta-vs-baseline change detection.
Tell us about your project. We'll scope the capture and pick the deliverable mix that lands in your design / operations workflow.