TWIST: NGI develops a digital twin for landslide risk along transport corridors.
The NGI project TWIST combines real-time data from satellites, weather stations, and ground monitoring to create a virtual replica of Norwegian infrastructure. The aim is to give decision-makers a precise, scientifically grounded picture of landslide risk, updated in real time.
Illustration generated using the AI tool DALL-E.
Thousands of kilometers of roads and railways run along Norwegian mountainsides and through valleys. Many of these routes are exposed to natural hazards, including avalanches, rockfalls, and flooding. The challenge is knowing precisely where the danger lies, and when.
That is the core of TWIST, funded through the basic funding from the Research Council of Norway. The project brings together NGI’s expertise in geotechnics, digital development, and risk assessment into a single shared tool: a digital twin of terrain and infrastructure.
– We gather all the data that matters for making a geotechnical assessment. That can include satellite data, remote sensing methods, climate data, and meteorological data with frequent updates, says Jessica Ka Yi Chiu, researcher at NGI and project manager of TWIST.
A virtual copy of the terrain
A digital twin is, in simple terms, a virtual copy of a physical location. In the context of TWIST, this means a model of a slope or an infrastructure corridor that is continuously updated with real-world data.
– If we can bring all this data together and incorporate our geotechnical understanding of how the processes unfold, we can update the numerical model against real data and reflect actual conditions. The digital twin is a virtual copy of how we see a slope, and of how it changes under different conditions, Chiu explains.
In this way, it becomes possible to build a digital tool that shows the actual status of a slope or a stretch of infrastructure in real time, where sufficient data are available. The result is a digital dashboard that operators and partners can use to view the risk picture along a corridor, with color-coded indicators for different hazard levels.
Many data streams, one picture
One of the biggest technical challenges in the project is managing the volume of data. A long infrastructure corridor generates enormous amounts of information from various sensors and sources. TWIST aims to make this data usable.
– It requires expertise to collect this data and maintain good data governance. The solution must be applicable as a foundation and transferable to other projects and other corridors, Chiu points out.
The platform is also designed to connect with other systems. Through open interfaces, it can be integrated into tools that infrastructure owners already use for asset management and incident handling.
– Right now, no platform handles geotechnical natural hazards and provides a scaled risk picture like this, Chiu states.
Jessica Ka Yi Chiu er prosjektleder for TWIST. ( Per Olav Solberg / NGI)
Pilot corridors in place before summer
The project is underway, and the team is actively seeking partners for pilot testing. The goal is to identify one or more corridors along roads or railways that include multiple types of natural hazards and documented incidents, so that the models can be calibrated against real-world conditions.
– We want a partner we can collaborate with, one who can give us access to data and tell us what they actually need. I hope we’ll have that in place before summer, she says.
TWIST also has synergies with ResiTrans, NGI’s large research center for resilient transport infrastructure. While ResiTrans covers a broader scope, including cybersecurity, TWIST can contribute to the digital twin component on the natural hazard side.
Jessica Ka Yi Chiu
Senior Engineering Geologist Rock Engineering jessica.ka.yi.chiu@ngi.no+47 968 77 853