Part ISat, 10 Jul, 12:00 - 16:00 (UTC)
Sat, 10 Jul, 20:00 - 00:00 China Standard Time (UTC +8)
Sat, 10 Jul, 14:00 - 18:00 Central Europe Summer Time (UTC +2)
Sat, 10 Jul, 05:00 - 09:00 Pacific Daylight Time (UTC -7)
Part IISun, 11 Jul, 12:00 - 16:00 (UTC)
Sun, 11 Jul, 20:00 - 00:00 China Standard Time (UTC +8)
Sun, 11 Jul, 14:00 - 18:00 Central Europe Summer Time (UTC +2)
Sun, 11 Jul, 05:00 - 09:00 Pacific Daylight Time (UTC -7)
The digital and sensing technologies, i.e. Big Data, are revolutionary developments massively impacting the Earth Observation (EO) domains. While, Artificial Intelligence (AI) is providing now the methods to valorize the Big Data. Today the accepted trends assume more data we analyze, the smarter the analysis paradigms will perform. However, the data deluge, diversity, or the broad range of specialized applications are posing new major challenges. From the perspective of the data valorization and applications the multi-mission and related data use for global applications still need more efforts. From the methodological side the challenges are related to, the reproducibility, the trustworthiness, physics awareness, and over all, the explainability of the methods and results.
The tutorial introduces and explains solution based on the concept of Digital Twins. A Digital Twin is the convergence of the remote sensing physical mechanisms tightly connected, communicating and continuously learning, from data and mathematical models, data analytics, simulations and user interaction.
The presentation covres the major developments, of hybrid, physics aware AI paradigms, at the convergence of forward modelling, inverse problem and machine learning, to discover causalities and make prediction for maximization of the information extracted from EO and related non-EO data. The tutorial explains how to automatize the entire chain from multi-sensor EO and non-EO data, to physical parameters, required in applications by filling the gaps and generating a relevant, understandable layers of information.
Digital Twins are technologies looking o the evolution of EO at least for the horizons of next two decades. The explosive present advance of AI methods was obtained thanks to mainly two factors, the advancement of theoretical bases and performance evolution of the IT, i.e. computation, storage and communication. Today we are the edge of a Quantum revolution, impacting technologies in communication, computing, sensing, or metrology. Quantum computers and simulators are and continuously become largely accessible. Thus, definitely impacting the EO domains. In this context the tutorial puts the bases of information processing from the perspective of the quantum computing and algorithms for EO. The presentation will cover an introduction in quantum information theory, quantum algorithms and computers, presenting the first results and analysing the main perspectives for EO applications.