Asset Management & Pipeline Leakage
Earth Observation Data Analytics for Water Infrastructure Asset Intelligence
Every year, water pipeline leakage causes a significant amount of potable water to be wasted. This seriously impacts revenue for utility companies by reducing the billable amount of water in the network. In the fight against non-revenue water (NRW), ground teams are deployed to monitor pipeline networks but this is often not efficient or cost-effective when faced with large, rural, and often remote, networks. Pipeline stress that causes leaks can arise from terrain motion, soil movement, vegetation incursion and anthropogenic influences that are all detectable from space, as well as leakage detection and critical asset monitoring. To better manage revenue losses and rising maintenance costs, water companies can now utilise our satellite-derived landscape intelligence to detect, monitor and predict leakage events.
Using Satellite-Derived Intelligence for Water Infrastructure Asset Management
We can produce highly valuable asset insights from geospatial imagery and data with our unique data processing techniques.
How can I use this insight?
- Reduce non-revenue water lost through leaks by detecting unknown leakage events using satellite data to identify hotspots of terrain movement and soil saturation
- Reduce operational cost by prioritising the deployment of ground-based maintenance activity
- Plan infrastructure investment based on asset intelligence prioritising the worst leak-affected or high risk pipelines
- Substantially reduce the cost of monitoring vast pipelines compared to ground monitoring
- Predict likely leakage over very wide areas that can’t be covered by ground based observation or sensor networks
- Drill down on high risk areas for early detection of possible leakage due to soil moisture content in rural areas and subsidence in urban areas
- Mitigate risk of damage to pipelines and disruption to communities with pre-emptive repairs based on predictive analysis
- Reduce the risk of liability and regulatory fines