SGAM: The Innovative Geotechnical Asset Management for Large Transport Networks
A smarter way to manage geotechnical risk across infrastructure networks
SGAM is NHAZCA’s solution for infrastructure asset managers who need to move from reactive maintenance to risk-based decision making. Instead of focusing only on known critical points, SGAM helps screen large transport networks, identify priority areas and support maintenance planning with a clearer picture of geotechnical risk.
This geotechnical asset management approach helps infrastructure teams move from isolated inspections to network-wide risk prioritization
What is SGAM?
SGAM, Smart Geotechnical Asset Management, is a decision-support solution for the maintenance and management of geotechnical assets such as embankments, slopes and tunnels. It helps asset managers assess current and potential impacts from landslides, floods, subsidence and seismic vulnerability, so they can prioritize interventions where they matter most.
How SGAM works
- Satellite and Earth observation data
- Global and regional geo-hazard databases
- Field survey data
- Structural, geotechnical and geomorphological monitoring systems
- Artificial intelligence for data fusion and prioritization
- Expert validation and consultancy
SGAM helps decision makers and asset managers prioritize maintenance activities using a risk-based, network-wide geotechnical asset management approach.
The result is a more comprehensive view of infrastructure health, including not only where risk exists, but also how reliable the available evidence is.
Why SGAM is different from traditional geotechnical asset management
Traditional geotechnical asset management often focuses on limited areas where risk is already known. SGAM expands that approach by screening large infrastructure networks, combining multiple data sources and supporting more strategic maintenance planning across the whole asset system.
Network-wide visibility
Move beyond isolated critical points and gain a broader understanding of geotechnical risk across roads, railways and related assets.
Better prioritization
Use integrated, multi-source evidence to identify where intervention is most urgent and where deeper investigation is needed.
Predictive maintenance support
Anticipate emerging issues earlier and support safer, more cost-effective maintenance strategies over time.
What you get
- Satellite and Earth observation data
- Reliability rating of results
- Automatic identification of areas subject to differential movements
- Expert interpretation and technical reporting
- Preliminary technical and economic proposals for critical issues
- Site-specific in-depth analysis for the most critical areas
Who SGAM is for
Water transmission infrastructure
Assess the vulnerability of distributed assets and support maintenance planning with a clearer understanding of ground movement and related hazards.
Transportation companies
Identify landslide-prone areas, ground deformation and seismic vulnerability along roads and railways to improve safety and reduce service disruption.
Electricity transmission infrastructure
Prioritize interventions and reduce the risk of outages by monitoring terrain instability and other geotechnical threats affecting network continuity.
Business benefits
Smarter maintenance prioritization
Move from reactive interventions to a risk-based maintenance approach that helps teams identify where action is most urgent and where deeper investigation is needed.
Reduced disruption and downtime
Anticipate geotechnical issues earlier to minimize closures, avoid service interruptions and reduce the operational impact of unexpected events across critical routes and assets.
Better use of budgets and resources
Focus technical effort and maintenance spending where risk is higher, helping organizations reduce inefficiencies, avoid unnecessary interventions and support more cost-effective planning.
Stronger asset resilience
Improve the long-term safety, reliability and resilience of infrastructure networks by combining hazard screening, vulnerability analysis and data-backed decision support.