How Leica Pegasus TRK helps infrastructure teams map roads and highways

As urban environments grow denser and civil infrastructure ages, managing buried utilities has become just as important as mapping what sits at the surface. Transport authorities, municipalities, and engineering firms are moving away from fragmented, single-asset surveys in favour of complete 3D digital twins that capture surface and subsurface assets together.

However, running separate surface surveying and subsurface utility engineering (SUE) workflows doubles exposure to live traffic, increases operational costs, and frequently produces misalignment between surface features (like manholes, valves, kerbs) and the pipes, cables, and ducts that lie beneath them.

The alternative is an integrated, non-intrusive approach. By combining a mobile mapping system like the Leica Pegasus TRK with a vehicle-mounted ground-penetrating radar (GPR) system like the IDS GeoRadar Stream UP, survey teams can capture high-density 3D point clouds, 360° imagery, and subsurface utility networks simultaneously in a single drive at normal traffic speeds. This unified workflow eliminates operational silos, protects field crews, and delivers a complete, survey-grade 3D model above and below the ground.

Synchronised above- and below-ground workflow

Combining mobile mapping with GPR follows an integrated workflow designed to maximise coverage while maintaining survey-grade accuracy and positioning.

Setting up the system

The Pegasus TRK unit is mounted to the rear roof or roof rack of the vehicle, while the Stream UP attaches directly to the vehicle’s rear tow bar, hovering just above the road surface without touching the ground. A single cable connects the Stream UP to the Pegasus TRK’s external sync port.

Before the drive, operators perform a spatial lever arm calculation to define the precise 3D distance offset (Dx, Dy, Dz) between the reference point on the Pegasus TRK (VLP rear) and the Stream UP antenna. Because the TRK serves as the core positioning engine for the Stream UP GPR, this offset ensures underground radar data is mapped to the exact same spatial coordinates as the surface point cloud. If the lever arm calculation is incorrect, underground features will be spatially shifted out of position.

Dry road conditions without rain or snow are optimal for GPR data collection.

Capture all data in a single drive

Traditional GPR systems rely on orthogonal scanning. A cart is pushed back and forth along the X and Y axes to detect pipes running parallel and perpendicular to the road.
The Stream UP instead uses a multi-frequency, multi-channel, dual-polarised antenna array, enabling it to capture longitudinal and transversal pipes simultaneously. Because of its dual-polarisation, the Stream UP does the equivalent work of traditional GPR in a quarter of the time.

However, whereas the Pegasus TRK fires LiDAR out in all directions, the Stream UP only surveys directly down. So, this requires a slightly different driving style to a normal mobile mapping survey.

To cover the whole road surface, drivers need to make parallel passes down each driving lane to cover the full width of the corridor, as though they are “brushing” the road. Data collection is typically performed at recommended speeds up to 60 km/h (37 mph), eliminating the need for lane closures or traffic stoppages.

^{Vehicle-mounted GPR maps in parallel lane swaths to capture complete 3D subsurface data without lane closures.}  

The two separate systems then feed into two separate software controllers in the vehicle cab. The Pegasus TRK imaging and LiDAR data feeds into Leica Pegasus FIELD on a tablet or laptop controller, while the Stream UP GPR data feeds into uMap running on a separate tablet or laptop. Both Pegasus FIELD and uMap display real-time coverage indicators of LiDAR and GPR data respectively, enabling users to spot any gaps in the data and rescan areas while still out in the field (so long as there is a good GNSS signal).

Combining the two datasets

Overcoming GNSS-denied environments

Standalone mobile GPR systems often struggle in urban environments. Narrow alleys, high-rise buildings, and tree-lined avenues block GNSS satellite signals, causing severe trajectory drift and rendering subsurface radar data spatially unreliable

The integrated Pegasus TRK and Stream UP solution solves this through multi-sensor trajectory fusion:

1. IMU bridging: The Pegasus TRK’s Inertial Measurement Unit (IMU) continuously tracks vehicle orientation and motion when there’s no satellite signal.
2. Post-processed kinematic (PPK): In Pegasus OFFICE, multi-pass trajectory optimisation corrects for IMU drift, delivering a smoothed, highly accurate trajectory line (accurate to 2-5 cm).
3. Shared subsurface georeferencing: The optimised trajectory file (.gga) is exported directly into IQMaps software to georeference the underground GPR data.
4. DMI / Odometer integration: In dense urban environments, with limited access to open sky due to tall buildings or long tunnels, it’s advised to mount a Distance Measurement Instrument (DMI) to constrain IMU drift during times of poor GNSS visibility.

^{One project in Hong Kong deployed a wheel-mounted DMI to maintain precise positioning in the city’s dense urban landscape and tall skyscrapers}

^{GNSS RTK alone produces poor trajectory data (left). Pegasus PPK calculation combines data from different sensors during data capture, requiring at least one GNSS reference station (centre). After a PPK calculation, a cloud-to-cloud adjustment can be processed in any multipass areas (right).}

^{Trajectory comparison in a dense urban environment showing that standard GNSS RTK suffers from high signal variance and total data dropouts (left), whereas Pegasus PPK uses GNSS and IMU sensor fusion to maintain a continuous, survey-grade trajectory (right).}

Core deliverables: above and below the surface

By capturing underground utilities alongside 3D surface infrastructure, survey teams can produce comprehensive digital twins and SUE-compliant deliverables from a single drive.

Automated pipe tracing

Processing raw GPR radar tomographies historically required specialised experts to manually interpret radar data frame by frame.

AiMaps is a cloud-based AI SaaS solution that introduces deep learning algorithms directly into the IQMaps workflow. It automatically analyses raw radar data, filters background noise, and produces clean tomography with automated pipe traces, reducing manual interpretation workload by up to 50% on complex, large-scale projects. Pipe geometries and depth profiles are extracted automatically, and because processing runs in the background on Hexagon GeoCloud, surveyors can continue other office work while the data is being handled.

SUE quality level validation and legacy record comparison

Legacy utility records are frequently wrong as ownership changes hands and changes get made without updating the drawings. Old and inaccurate records dramatically increase the risk of unsafe utility strikes, causing project delays and budget overruns.

The digitised utility model from AiMaps/IQMaps (.dxf) and the Pegasus TRK surface point cloud (.lgsx) are then imported directly into Leica Cyclone 3DR, where the radar findings sit alongside the existing utility records for direct comparison.

New, unrecorded pipes then become visible and wrong pipe depths show as discrepancies. Proposed construction and civil works can then be checked for spatial clashes against the real utility network before a potential incident, avoiding delays and additional costs downstream.

Subsurface void detection and water leakage

When GPR data flags a suspected underground void, operators can analyse the precise surface profile for early relative settlement. Smaller subsurface voids can be identified in the GPR data well before visible surface deformation occurs, giving asset owners an early warning to perform preventative maintenance.