Tunnel Progress

Combine satellite, LiDAR, and photogrammetry data to detect excavation fronts, measure advance rates, and optimize scheduling in tunnel construction projects.

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How does it work?

Manual tunnel progress surveys rely on time-consuming field measurements and are vulnerable to human error and site hazards. Automated geospatial analysis accelerates progress tracking, providing accurate, near real-time excavation metrics that improve decision-making and safety.

Real-Time Monitoring: Automated processing of satellite and drone imagery delivers near real-time excavation front positions. This enables immediate adjustments to operations, reducing idle time and enhancing site coordination.
Accurate Volume Estimation: 3D point clouds from LiDAR and photogrammetry compute precise excavation volumes. Construction teams can validate contractor claims and optimize material transport plans.
Safety Risk Reduction: Early detection of unexpected ground conditions or overbreak zones triggers prompt inspections. This proactive approach minimizes worker exposure to hazardous conditions and unplanned stoppages.
Resource Optimization: Up-to-date progress metrics inform allocation of machinery and workforce based on actual excavation rates. This reduces equipment idling and labor costs while maintaining project momentum.
Schedule Compliance: Progress detection integrates with project management tools to compare actual versus planned excavation timelines. Deviations are flagged automatically, enabling schedule corrections and stakeholder reporting.
Historical Trend Analysis: Archival geospatial datasets allow analysis of excavation rates over time and across different tunnel sections. Insights support continuous improvement and risk assessment for future projects.

Frequently asked questions

Have a different question and can’t find the answer you’re looking for? Reach out to our support team by sending us an email and we’ll get back to you as soon as we can.

How does geospatial progress detection compare to manual surveys?: Geospatial detection automates data capture and processing, reducing field time and human error compared to manual surveying. It offers more frequent updates and integrates multiple data sources for comprehensive analysis.
Why is this method gaining popularity in tunnel construction?: Contractors and engineers value its ability to deliver accurate, near real-time insights without interrupting site activities. The integration with existing BIM and project management systems streamlines reporting and decision-making.
Can this solution replace LiDAR-only approaches?: While LiDAR provides high-precision 3D models, combining it with satellite and photogrammetry data increases spatial coverage and update frequency. This hybrid approach balances resolution, cost, and operational continuity.
How often can progress maps be generated?: Update frequency depends on the data acquisition schedule—satellite revisits occur daily to weekly, while drone and terrestrial scans can be conducted on demand. Our platform automates processing immediately after each data upload.
Are there limitations under complex geology?: Highly reflective or water-filled surfaces can introduce noise in photogrammetric data, requiring filtering or supplemental sensors. In such cases, integrating ground-penetrating radar or enhanced LiDAR scans can improve detection accuracy.
What alternatives exist for tunnel progress monitoring?: Alternative methods include total station surveys, laser scanning, and manual tape measurements, each with varying labor and accuracy trade-offs. Geospatial analytics stands out for its automation, scalability, and multi-sensor fusion capabilities.

Geospatial AI Platform

Intelligence

AI & foundation models

Deep-learning and foundation models turn raw imagery into ready-to-use insights, so you ship answers instead of training pipelines.

Experience

Conversational workflow

Ask questions in plain language and the platform responds with charts, visualizations, and next step suggestions.

Speed

GPU-accelerated cloud

Cloud-native architecture spins up on-demand GPU clusters that scale from a single scene to global archives—no manual ops, no bottlenecks.

Data

Any sensor, any format

Optical, SAR, drone, IoT, vector or raster—ingest, fuse, and analyze without conversion headaches.

Visualization

Insight you can see

Real-time 2D / 3D maps and export-ready plots make results clear for engineers, execs, and clients alike.

Boost your productivity. Experience Geospatial AI.

Turn satellite, drone, and sensor data into clear, real-time insights using powerful AI – no complex setup, just answers you can see and act on.

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