A cost-effective early warning system to detect and prevent landslides and slope incidents

Summary

Developed by Madrid-based company Detektia, EyeRADAR integrates advanced technologies to revolutionise the way we control linear infrastructure. Utilising satellite radar and artificial intelligence (AI), EyeRADAR enables scalable monitoring of slope stability in near real-time, making it possible to detect slope instability before it results in catastrophic failure.

The solution exponentially increases the volume of information on ground and slope stability, helping decisionmakers to make informed maintenance and risk prevention decisions in road infrastructure.

Need and use case for the technology

The parameters that characterise linear infrastructure such as roads and highways are a complicated mixture of diverse materials with different rheological properties. Analysing the individual contribution and influence of terrain parameters such as permeability, resistance, or elasticity to the behaviour of the ground is a difficult task. It is not feasible to monitor slope and slope stability in real-time through laboratory analysis, instrumentation, or in situ sensing. Additionally, current slope and slope stability control technologies lack scalability, hindering their application to large-scale projects.

EyeRADAR solves these problems by providing real-time and historical data, enabling more informed system-level decisionmaking related to slope stability. The solution provides highly accurate and precise results, estimates, and scenarios in areas with high geotechnical complexity and strong seasonal rainfall patterns. This enables cost-effective early warning systems for slope incidents such as landslides and slope failures, to protect communities and save lives.

InSAR, the technology behind EyeRADAR, utilises global satellite coverage and does not require ground personnel or instrumentation, making it easily scalable to support decisionmaking at regional, national, and international levels. By providing data on a global scale, decisionmakers can identify potential hotspots for landslides and prioritise resources for prevention and mitigation efforts, regardless of the location.

The solution can be applied across the entire linear infrastructure lifecycle, from planning and design to construction, operation, and maintenance. During the planning and design phase, it can advise on modifications to the road layout to save money and avoid disasters. During construction, it helps to improve safety at the construction site, while in the operation and maintenance phase, it can predict where and when there will be problems, days in advance, improving the operation of the asset.

Overview of the technology

EyeRADAR generates early warning systems based on the analysis of deformation time series using non-intrusive radar satellite (InSAR) technologies. The satellite data are combined with other parameters such as rainfall, geology, digital elevation models, and geometry of slopes and embankments, to produce high-resolution cartography of landslide susceptibility.

The solution offers both static and dynamic landslide susceptibility cartography. The static maps show the probability of landslides independent of current conditions and are useful when designing and planning new routes. In contrast, the dynamic maps consider dynamic variables such as rainfall, allowing for possible landslide problems or events to be predicted several days in advance.

To further support system-level decisionmaking, EyeRADAR provides near real-time and historical data on ground deformation and precipitation, so that decisionmakers can analyse trends and patterns in slope behaviour and landslide occurrence. This information can be used to inform long-term planning and policy decisions related to land use, infrastructure development, and emergency preparation.

The solution's integration with Building Information Modelling (BIM), Geographic Information System (GIS) mapping, and data management platforms allows the generated data to be seamlessly integrated into existing decisionmaking processes. This ensures a comprehensive and holistic approach to risk management through existing tools and procedures that decisionmakers are already familiar with.

The solution integrates local, regional, and global information, such as the Digital Elevation Model of the Shuttle Radar Topography Mission, global or regional maps of tree cover and land use, available geological information, climate information derived from precipitation data, and an inventory of landslides. All landslide events are continuously stored and updated in a single database, allowing for the continuous calibration of landslide models, and providing accessible and standardised information.

EyeRADAR’s dynamic landslide susceptibility dashboard

Overview of the company

Established in November 2019, Detektia develops highly scalable and global solutions for the monitoring and controlling of millimetric ground movements and infrastructure from space. The company utilises advanced AI algorithms and Differential Interferometry with Synthetic Aperture Radar (InSAR) technology to provide early warnings of infrastructure deformation throughout the entire lifespan of an asset.

Detektia is a spin-off of the Civil Engineering School at the Technical University of Madrid, which has more than 35 years of experience in developing innovative solutions for analysing and controlling ground and infrastructure deformation.

Over the next five years, Detektia plans to expand the usage of EyeRADAR into new markets and regions and aims to monitor 10,000 infrastructure assets across five continents by 2028. By expanding its reach into new markets and regions, Detektia hopes to be part of the paradigm shift in infrastructure management and bring satellite data into decisionmaking processes.

Transformative outcomes of the technology

EyeRADAR provides a game-changing and cost-effective solution for managing slope stability, enhancing safety, and reducing the risks associated with linear infrastructure projects.

Dynamic susceptibility maps are an essential tool for disaster and climate adaptation, allowing decisionmakers to identify high-risk areas for natural hazards and disasters. By utilising these maps to pinpoint the areas that are most susceptible to landslides, local authorities can prioritise resources toward measures such as slope stabilisation, drainage improvements, or reforestation, ultimately protecting communities from devastating consequences such as loss of life and widespread destruction.

This leads to improved outcomes for businesses and communities, contributes to sustainable and resilient linear infrastructure development, and plays a crucial role in the digitalisation of infrastructure management.

Example applications

EyeRADAR is highly adaptable and scalable, thanks to its use of advanced technology such as InSAR and machine learning models, as well as its global coverage and cloud computing capabilities. This enables the solution to be easily replicable and deployed in a variety of ways, including in different terrains and markets. It has been successfully deployed in Spain, Mexico, and Colombia to monitor critical infrastructure such as highways, dams, ports, and railways.

In Colombia, the solution’s static and dynamic landslide susceptibility cartographies are used by global infrastructure construction company, Sacyr, to anticipate the geotechnical behaviour of the ground. These cartographies are created by combining InSAR deformation results with other site variables, such as Digital Elevation Model (DEM), geology, and rainfall, using AI models to generate high-resolution mapping of slope landslide susceptibility.

The solution’s application connects to meteorological APIs to automatically calculate and provide high-resolution daily landslide probability in the analysis area, with information displayed in a map with a traffic-light colour scheme. Based on the forecast, Sacyr can develop preventative maintenance plans, and relocate machinery close to the endangered slope to make the process of clearing the road faster and more efficient if a landslide occurs.