Mobile Mapping Survey of East Midlands Airport Runway

Mobile Mapping Survey of East Midlands Airport Runway

Location:

East Midlands Airport, Castle Donington, Derby

Client:

Arup (on behalf of East Midlands Airport / MAG)

Industry:

Aviation Infrastructure/ Airport / Asset Management

Background

East Midlands Airport is the UK’s largest dedicated cargo airport and operates on a 24/7 basis, handling significant overnight freight movements for major operators including DHL and UPS. The runway is subject to heavy usage, resulting in ongoing wear and the need for regular inspection and maintenance.

This project formed part of a wider programme of essential runway upgrades and maintenance works being delivered under Arup’s long-term airfield management contract. Historically, runway condition assessments have relied heavily on visual inspections, limiting the level of measurable, repeatable data available.

Malcolm Hughes was commissioned to carry out a high-resolution mobile mapping survey of the runway and associated taxiways, capturing detailed geometric data to support condition analysis and enhance defect identification.

Services provided included:

• Mobile mapping survey of runway surface
• GPS ground control survey
• High-resolution imagery capture
• Topographic data acquisition of taxiway connections

Challenges

The project presented several logistical and technical challenges:

• Restricted access window: Survey work had to be completed within a 4–5 hour  runway closure, with strict deadlines before final safety inspections.
• Live operational environment: The airport operates continuously, requiring careful coordination to avoid construction zones and ensure compliance with airfield safety protocols. Working around the other maintenance and road resurfacing teams to access parts of the runway needed for data capture.
• High-traffic infrastructure: The runway experiences significant wear due to heavy cargo aircraft, necessitating highly accurate data capture to identify subtle surface deformations.
• Precise coverage requirements: Full surface coverage of the 60m-wide runway required carefully planned survey routes with consistent spacing and alignment.
• Integration with existing workflows: Data needed to complement ongoing asset management strategies and future analytical processes, including potential machine learning applications.

Value to Client

• Introduction of objective, measurable data to supplement traditional visual inspections
• Enhanced ability to detect and monitor surface deformation over time
• Improved decision-making for maintenance and repair prioritisation
• Reduced reliance on subjective condition assessments
• Creation of a digital dataset suitable for future analysis and automation

Client Deliverables

• High-density mobile mapping point cloud of the runway surface
• High-resolution georeferenced imagery
• GPS-controlled survey dataset aligned to project coordinates
• Coverage of taxiway links
• Data suitable for deformation analysis and asset management integration

Our Approach

Malcolm Hughes implemented a structured and efficient mobile mapping methodology to maximise data quality within the limited runway closure window.

Survey control was established using identifiable ground features, including runway markings and lettering, providing a reliable framework for georeferencing all captured data.

The runway was surveyed using the Leica Pegasus TRK EVO mobile mapping system, mounted to a survey vehicle. To ensure full coverage, the team carried out 12 survey runs along the runway, maintaining consistent 5-metre spacing to capture the entire 60-metre width.

Predefined survey routes were uploaded to the system and followed via an onboard tablet, ensuring accuracy in alignment and repeatability. Simultaneously, integrated cameras captured high-resolution imagery alongside LiDAR data, enabling both geometric and visual analysis.

Two distinct survey areas were captured:

• Area 1: Taxiways Alpha to Golf, including runway link roads
• Area 2: Main runway surface, coordinated to align with construction programme progress

The resulting dataset provides a comprehensive and highly accurate digital representation of the runway surface, enabling detailed inspection and long-term condition monitoring.

Added Value

• Data provides a foundation for future advanced analysis, including possibilities for AI-driven defect detection
• Repeatable methodology allows for consistent long-term monitoring
• Minimised disruption to airport operations through efficient survey execution
• Supports integration into wider asset management and maintenance planning systems

Summary

This project demonstrates Malcolm Hughes’ capability to deliver high-precision survey solutions within complex, time-critical aviation environments. By combining mobile mapping technology with robust survey control, the team delivered a comprehensive digital dataset that enhances visibility of runway condition and supports more informed asset management decisions.

The survey represents a significant step forward from traditional inspection methods, enabling the client to move towards data-driven maintenance strategies and future-ready analytical approaches.