Big Satellite Data: Opportunities and Challenges
Title: "Big Satellite Data: Opportunities and Challenges"
Speaker: Fabian Gieseke is a Professor at the Department of Information Systems of the University of Münster in Germany. His research focus is on machine learning and data engineering as well as on a variety of applications such as modern energy systems, smart cities, remote sensing, or physics. He received his PhD degree at the University of Oldenburg (Germany). Before joining the Department of Information Systems in April 2020, Fabian Gieseke was an Assistant Professor (TT) for Data Science at the University of Copenhagen. Currently, he is a director of the European Research Center for Information Systems (ERCIS) and is head of the Machine Learning and Data Engineering group of the Department of Information Systems in Münster.
Abstract: The field of data science has gained considerable attention over the past years. One reason for this phenomenon is the fact that the data volumes in various domains have increased dramatically. This is the case, for instance, in remote sensing, where current satellites already produce data volumes in the petabyte range. Upcoming projects will produce such data volumes per month, per week, or even per day. Machine learning techniques aim at extracting knowledge in an automatic manner and have been identified as one of the key drivers for future discoveries and innovation in in this field. Processing and analyzing the massive amounts of data can, however, still become extremely challenging from a computational perspective. The presentation will cover some of our current research activities that are related to this line of research. In particular, I will sketch the potential of modern deep learning models and efficient change detection methods in the context of global Earth observation.