Learning outcomes

• HPC requirements and best practices in EO Basic EO data systems and tools architectures
• Introduction in quantum information
• Physical implementation of quantum computers: basics and state of the art
• Quantum resources: the potential for EO

Overview of the

Lecture content

From its very beginning the field of Earth Observation (EO) became a driving force for the data processing, storage or transmission. During the last decades satellite and airborne sensors are collecting and transmitting to receiving stations several terabytes of data every day. With the increasing spatial resolution not only the data volume is growing, but also the image information content is exploding. This became a challenge for the data exploitation and information dissemination methods: how to enlarge the usability of the millions of EO images acquired and stored in archives to a larger user community.

The lecture will overview the computational requirements emerging from the EO technology and applications. The basic computer architectures will be introduced and explaining their evolution related to the EO particularities. Examples will be provided for multispectral and Synthetic Aperture Radar (SAR) data, encompassing the chain from the Payload Ground Segment data preprocessing, data distribution systems, EO data platforms to specialized AI tools. The presentation will continue with the basics of quantum information processing and physical principles of the quantum computers. The today most popular quantum computing resources will be comparatively overviewed analyzing their potential impact in EO data analysis. The lecture will introduce elements of quantum machine learning and their perspectives. The field of secure communications will also be introduced in relation to EO technology. Finally, the lecture will discuss the future impact of quantum imaging for space applications.

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The Instructors

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Prof. Mihai Datcu

Bio

Mihai Datcu received the M.S. and Ph.D. degrees in Electronics and Telecommunications from the University Politechnica Bucharest (UPB), Romania, in 1978 and 1986. In 1999 he received the title Habilitation à diriger des recherches in Computer Science from University Louis Pasteur, Strasbourg, France. Currently, he is Senior Scientist and Image Mining research group leader with the Remote Sensing Technology Institute of the German Aerospace Center (DLR), and Professor with the Department of Applied Electronics and Information Engineering, Faculty of Electronics, Telecommunications and Information Technology, UPB. From 1992 to 2002 he had a longer Invited Professor assignment with the Swiss Federal Institute of Technology, ETH Zurich. From 2005 to 2013 he has been Professor holder of the DLR-CNES Chair at ParisTech, Paris Institute of Technology, Telecom Paris. His interests are in Data Science, Machine Learning and Artificial Intelligence, and Computational Imaging for space applications. He is involved in Big Data from Space European, ESA, NASA and national research programs and projects. He is a member of the ESA Big Data from Space Working Group. In 2006, he received the Best Paper Award of the IEEE Geoscience and Remote Sensing Society. He is holder of a 2017 Blaise Pascal Chair at CEDRIC, CNAM, France.