AI for Earth Observation: From Petabytes to Actionable Insights by Prof Xiaoxiang Zhu

Abstract

Geoinformation derived from Earth observation (EO) satellite data is indispensable for tackling grand societal challenges, such as urbanization, climate change, and the United Nations Sustainable Development Goals (SDGs). Furthermore, Earth observation has irreversibly entered the Big Data era, with initiatives like ESA's Sentinel satellites and the rise of NewSpace companies. This evolution brings both tremendous opportunities and unprecedented analytical challenges.

This talk showcases how innovative AI methods and big data analytics solutions can significantly enhance the retrieval of large-scale geo-information from EO data, leading to breakthroughs in geoscientific and environmental research. It also explores emerging frontiers where AI, Earth Observation, and sustainability converge to support actionable insights for a more resilient planet.

Biography

Xiaoxiang Zhu is Chair Professor for Data Science in Earth Observation at the Technical University of Munich, Germany. She directs the national center of excellence ML4Earth, the international AI future lab AI4EO, and the Munich Data Science Institute. Her research focuses on artificial intelligence and data science in Earth observation. She develops innovative signal processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big EO data. Her team aims at tackling societal grand challenges, such as Global Urbanization, Climate Change, and the UN's Sustainable Development Goals (SDGs), working on solutions that can scale up for global impact.