Multi-Satellite imaging for Space-based Landslide Occurrence and Warning Service

“We are working with satellite data for this,” says Prof. Dr. Mahdi Motagh of the Helmholtz-Centre Potsdam – GFZ German When a landslide occurs, it often comes as a complete surprise – despite the fact that, in most cases, slopes only gradually pick up speed after a long period of initial creep. This project aims to develop a method that detects even the tiniest of changes in the earth’s surface. Such a method would then provide the basis for early warning systems and for rapid emergency mapping if it ever comes to a landslide.

Research Centre for Geosciences. Satellite photos have long been used in practice, but there are many problems to this: if a region of concern is under a layer of cloud cover, it can take days or even weeks for the clouds to part and allow the satellites to take useful photos of a torrential rain or flood event, for example. “We are therefore working with radar images from satellites, since radar delivers reliable images irrespective of the weather,” Mahdi Motagh explains.

They will now be developing an automated method to be tested in example regions in China around the Three Gorges dam, in Kirgizstan, and in Iran. The key to the approach is data fusion: radar data and optical satellite images will be combined to map the status quo and subsequently to detect even the slightest of changes. “The radar images are on such a fine scale that they can detect movements in the order of centimetres or even millimetres, as well as minor changes in vegetation, resulting from a landslide,” says Mahdi Motagh. Computers will be trained using machine learning methods to recognise these miniscule changes.


Motagh, M., & Wang, W. (n.d.). Towards a deep-learning-based approach for improving  landslide detection using Synthetic Aperture Radar Data. Helmholtz Imaging Conference 2021.

Other projects


HIT Permafrost

The Hidden Image of Thawing Permafrost

The project aims to develop a method for determining just how extensively thaw processes have already progressed in permafrost regions. The machine learning approach to be developed will be used to analyse radar images from aircraft in order to learn more about the properties of the subsurface permafrost.
Image: DLR


On the trail of the mystery of the laws of calving

Researchers still face a mystery when it comes to the laws by which glaciers calve. This project aims to use satellite imagery, artificial intelligence, mathematical optimisation and a new data processing pipeline to track the movements of glacier fronts in Antarctica to get closer to solving the mystery.
Decorative image with blue, green, pink and yellow colors


Breaking resolution limit of electron microscopy for magnetic materials

A new method will make it possible to take images of the magnetic properties of materials under the electron microscope and to correlate these properties with their atomic structure. In order to achieve high resolution, a special algorithm must be developed to compute the magnetic properties from the microscope data.