In the context of anticipated climate change, meteorologists expect an increase in extreme weather events in Austria, which may serve as precursors of gravitational mass movements such as landslides. As such, landslides represent a safety risk for people and infrastructure, and often cause great damage. Consequently, their detection is crucial in order to be able to act promptly and to avert potential damage at an early stage.

A high-quality and complete data inventory is an essential prerequisite for a better understanding of landslides and for the creation of maps, risk analyses or the development of an early warning system. So far, this consists of data from historical archives, results from field mapping, data derived from remote sensing, as well as combined inventories.

We propose to supplement these inventories by exploiting information from new digital elevation models and earth observation data from the Sentinel missions. These are large amounts of valuable data, which have only been used to a very limited extent up to now. This is mainly attributable to the lack of methods to analyse these data in a timely manner, which could be used to create an improved data inventory as a basis for determining the occurrence probability of mass movements.

The aim of gAIa is to utilize methods of modern artificial intelligence (AI) to provide policymakers with this essential basis for their decisions. More specifically, gAia will employ Machine Learning techniques for harmonizing and fusing heterogeneous data sources, while Deep Learning architectures are applied for modelling the occurrence probability of landslides. In this way, circumstances, which may lead to landslides, can be detected automatically and the extended data inventory used to provide improved hazard risk maps.

Project partners:

• Zentralanstalt für Meteorologie und Geodynamik (ZAMG)
• Austrian Institute of Technology (AIT)
• GeoVille Information Systems and Data Processing GmbH (GeoVille)
• Disaster Competence Network Austria (DCNA)
• Geologische Bundesanstalt (GBA)
• Bundesministerium für Landesverteidigung (BMLV)

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