Predicting Landslides

  • Released Monday, July 1, 2019
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If a slope's underlying foundation is unstable, heavy rainfall could be all it takes to trigger a landslide. In fact, rainfall is the most common catalyst for landslides. An open sourced computer model developed at NASA's Goddard Space Flight Center uses precipitation data to identify areas all over the globe that are potential landslide hazards. The model first looks at areas that have recently experienced heavy rainfall using data from the Global Precipitation Measurement (GPM) mission. When the rainfall estimates are unusually high, the model checks other known conditions of the area that may encourage landslides, such as recent road construction, steep hills, and other factors. A "nowcast" map then combines the rainfall data and these other factors to mark areas that might have landslides. Scientists have used these models to conduct studies on long term landslide patterns and landslide warning signs. Watch the video to learn more.

The purple dots show the distribution of fatalities between 2007 and 2018 that are related to rain-fall triggered landslides.

The purple dots show the distribution of fatalities between 2007 and 2018 that are related to rain-fall triggered landslides.

Southeast Asia’s potential landslide activity in any given July shows high risk areas (red) associated with reported fatalities.

Southeast Asia’s potential landslide activity in any given July shows high risk areas (red) associated with reported fatalities.

Landslides on N. America’s West Coast in July 2018 are associated with low fatalities and consistent with a history of non-fatal landslides.

Landslides on N. America’s West Coast in July 2018 are associated with low fatalities and consistent with a history of non-fatal landslides.

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NASA's Scientific Visualization Studio

Release date

This page was originally published on Monday, July 1, 2019.
This page was last updated on Wednesday, May 3, 2023 at 1:45 PM EDT.