EO Data Science Department

Besides the expertise pools at IMF in the three sensor technologies, namely synthetic aperture radar (SAR), optical imaging and atmospheric spectrometry, algorithms crossing sensor technologies, e.g. for data fusion, have been gaining importance for years. Furthermore, Earth observation (EO) has irreversibly arrived in the Big Data era with the Sentinel satellites (and in the future with Tandem-L). This requires not only new technological approaches to manage large amounts of data (as pursued by DFD), but also new analysis methods.

Here, methods of data science and artificial intelligence (AI), such as machine learning, become indispensable. Deep Learning in particular has led to a revolution in AI in recent years. Motivated by these facts, IMF has placed one of its research foci on EO Data Science.

Our vision is listed as follows:

Our expertise lies in the research of artificial intelligence for remote sensing (AI4EO).

The current focus is particularly on the development of artificial intelligence for multimodal data, georeferenced remote sensing data, images from time series recordings and large-scale data.

We have defined two major focus areas: Efficiency in AI4EO and Trustworthy AI4EO.

Furthermore, we are researching the possibilities of solving complex problems in the field of earth observation with the help of Quantum Computing.

Our SWAT (Software and Tools) team supports our department with in-depth knowledge of programming, knowledge discovery, high performance computing (HPC) and applications in the geosciences.

The department is divided into the following working groups:

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Contact

Dr. Anja Rösel

Acting Head of Department EO Data Science
German Aerospace Center (DLR)
Remote Sensing Technology Institute (IMF)
EO Data Science
Oberpfaffenhofen, 82234 Weßling
Tel: +49 8153 28-4330

Dr. Andrés Camero Unzueta

Acting Head of Department EO Data Science
German Aerospace Center (DLR)
Remote Sensing Technology Institute (IMF)
EO Data Science
Oberpfaffenhofen, 82234 Weßling
Tel: +49 8153 28-1033