Researchers from the University of Cambridge are using AI to speed up landslide detection following major earthquakes and extreme rainfall events—buying valuable time to coordinate relief efforts and reduce humanitarian impacts.
On 3 April 2024, a magnitude 7.4 quake—Taiwan’s strongest in 25 years—shook the country’s eastern coast. Stringent building codes spared most structures, but mountainous and remote villages were devastated by landslides.
When disasters affect large and inaccessible areas, responders often turn to satellite images to pinpoint affected areas and prioritise relief efforts.
But mapping landslides from satellite imagery by eye can be time-intensive, said Lorenzo Nava, who is jointly based at Cambridge’s Departments of Earth Sciences and Geography. “In the aftermath of a disaster, time really matters,” he said. Using AI, he identified 7,000 landslides after the Taiwan earthquake, and within three hours of the satellite imagery being acquired.
Since the Taiwan earthquake, Nava has been developing his AI method alongside an international team. By employing a suite of satellite technologies—including satellites that can see through clouds and at night—the researchers hope to enhance AI’s landslide detection capabilities.
Multiplying hazards
Triggered by major earthquakes or intense rainfall, landslides are often worsened by human activities such as deforestation and construction on unstable slopes. In certain environments, they can trigger additional hazards such as fast-moving debris flows or severe flooding, compounding their destructive impact.
Nava’s work fits into a larger effort at Cambridge to understand how landslides and other hazards can set off cascading ‘multihazard’ chains. The CoMHaz group, led by Maximillian Van Wyk de Vries, Professor of Natural Hazards in the Departments of Geography and Earth Sciences, draws on information from satellite imagery, computer modelling and fieldwork to locate landslides, understand why they happen and ultimately predict their occurrence.
They’re also working with communities to raise landslide awareness. In Nepal, Nava and Van Wyk de Vries teamed up with local scientists and the Climate and Disaster Resilience in Nepal (CDRIN) consortium to pilot an early warning system for Butwal, which sits beneath a massive unstable slope.