Projects

The primary objective of IDEAtlas, an ESA funded project, is to develop, implement, validate and showcase advanced AI-based methods to automatically map and characterize the spatial extent of slums from Earth Observation (EO) data.

Maps are quickly becoming outdated, about 10% of the objects change annually. This project focuses on methods to automatically interpret newly acquired sensor data to detect and to update the changed objects in the digital map.

In MASSIVE, the project team aims to improve glacier mapping and surface glacier mass balance estimation techniques with the help of machine learning, especially deep learning.

The project aims to develop a spatially explicit agricultural database in support of agricultural planning. The considered study areas are in Cambodia and Viet Nam, where rice paddy occupy a substantial portion of the agricultural area.

This research project develops a novel way to identify and monitor landslides, even when cloud cover obscures traditional satellite images. This breakthrough could significantly improve landslide warning systems and save lives around the world.