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How Can We Forecast Landslides?

Writer's picture: GeofemGeofem

Updated: Feb 25

Landslides are sudden, but they rarely happen without warning. With the right tools and data, decision makers can spot signs of instability in near real time. This helps us predict when and where a landslide might happen. We can do this before it disrupts infrastructure or puts lives at risk.

mountain with variable soil

Understanding the Warning Signs of Landslides

Indicators of imminent landslide hazard include:


  • Ground Movements: Slow, subtle shifts in the earth's surface that precede a collapse.

  • Heavy Rainfall or Soil Moisture: Waterlogged slopes lose strength, increasing the risk of failure.

  • Seismic Activity: Earthquakes can destabilise slopes, acting as a trigger for landslides.


The Power of Satellite Remote Sensing


At Geofem, we use Interferometric Synthetic Aperture Radar (InSAR) and other remote sensing techniques to monitor these indicators.

  • Ground Displacement: High resolution InSAR measures surface movements as small as a few millimetres, detecting early signs of slope stability.

  • Soil Moisture Levels: By analysing satellite-derived soil moisture data, we identify areas at risk of water-induced landslides.

  • Geohazard Susceptibility Mapping: Combining topographic, geological, and hydrological data, we produce landslide susceptibility maps to pinpoint high-risk zones.


Forecasting in Action

For infrastructure managers, this data is critical. By monitoring slopes around roads, railways, and dams we can:


  • Identify emerging risks before they escalate.

  • Prioritise maintenance in areas showing ground instability.

  • Safeguard infrastructure and minimise costly disruptions.

Aerial view of extraordinary meadow with many paths

Turning Data into Actionable Insights

Forecasting landslides is not about predicting the future with certainty. Using science and data helps lower uncertainty and make better decisions. At Geofem, our satellite monitoring solutions help infrastructure managers see landslide risks early.


Want to read a case study of how these susceptibility maps can be used in real-life infrastructure cases? Read this article next.

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