Geoinformation derived from Earth observation satellite data is indispensable for tackling grand societal challenges. Among them energy, urbanization, climate change, ecology, food security and environment are crucial for shaping a sustainable future. Furthermore, Earth observation has irreversibly arrived in the Big Data era, e.g. with ESA’s Sentinel satellites and with the blooming of NewSpace companies. This requires not only new technological approaches to manage and process large amounts of data, but also new analysis methods. Here, methods of data science and artificial intelligence (AI), such as machine learning, become indispensable.


The research of our lab focuses on artificial intelligence and data science in Earth observation. We develop innovative signal processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth observation data. Our team aims at tackling societal grand challenges, e.g. Global Urbanization, UN’s SDGs and Climate Change, thus, works on solutions that can scale up for global applications. 

 

Globalization: A view from space

Global urbanization has lead to new challenges for urban planners aiming to reduce poverty and ensure sustainability. To overcome these challenges, we need sufficient data on a global scale.

AI and data science in EO

We develop signal processing and machine learning algorithms to fuse Peta bytes of remote sensing data from different satellite missions with massive image data and text files from social networks.