New possibilities for global Earth observation using multi-sensor data and transferable machine learning models
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Earth observation has seen a tremendous boom in the recent years. From a discipline that was formerly almost only used for scientific or military purposes and whose data products were expensive and hard to get, nowadays new public satellite missions as well as a commercial startup companies provide an almost unlimited amount of images to anyone who is interested. Paired with advances in machine learning, most notably in the field of deep neural networks, this has lead to new possibilities for the extraction of geoinformation. This talk will show some of these new possibilities with a focus on the exploitation of multi-sensor satellite data, coming both from optical and synthetic aperture radar (SAR) sensors.