Abstract

Abstract

Our planet is facing unprecedented environmental challenges, including rapid urbanization, deforestation, pollution, biodiversity loss, and climate change. At the same time, extreme events such as floods, heatwaves, and wildfires are increasing in frequency and severity, with far-reaching human, economic, and environmental impacts. Earth Observation (EO), combined with advances in Artificial Intelligence (AI), provides powerful tools for understanding these processes and supporting evidence-based decision-making.

In this seminar, Professor Ban will discuss recent research at the intersection of EO and AI, with a focus on deep learning methods for monitoring environmental change at scale. She will present selected results from EO-AI4GlobalChange, a collaborative research project developing novel, globally-applicable deep learning approaches for analysing multi-sensor, multi-modal EO data. The talk will cover examples including 2D and 3D urban mapping, urban change detection, wildfire detection and near-real-time monitoring, flood mapping, and multi-hazard building damage detection.

The seminar will also briefly introduce PANGAEA , a global benchmark for Geospatial Foundation Models, and discuss insights from the systematic evaluation of widely used foundation models across multiple geospatial domains. Finally, Professor Ban will briefly outline the objectives of the recently established AI4EO Working Group within Group on Earth Observations (GEO), which aims to advance GEO ’s vision of Earth Intelligence for All through AI-driven Earth observation research, innovation, and collaboration.

Bio

Dr. Yifang Ban is the Professor and Director of the Division of Geoinformatics at KTH Royal Institute of Technology, and an Associate Director at Digital Futures in Stockholm, Sweden. Before joining KTH as a full professor in 2004, Dr. Ban was a tenured Associate Professor at York University in Toronto, Canada. She received her PhD in 1997 from the University of Waterloo in Canada. In 2023, she earned a certificate in Leading Sustainability: High Impact Leadership from the University of Cambridge.

Her research has been focused on Earth observation big data analytics, machine learning/deep learning for urban mapping, urbanization monitoring and wildfire and flood detection to support sustainable and resilient development. She has published extensively on these topics and has been ranked by Stanford/Elsevier among the World’s top 2% of scientists in 2020-2025. Professor Ban is Principal Investigator for a number of impactful projects, including EO-AI4GlobalChange, EO-AI4ResilientCities, SAR4 Wildfire, and Climate Change Induced Disaster Management in Africa.

Professor Ban is the recipient of the 2025 Group on Earth Observations (GEO) Lifetime Achievement Award and the 2023 Google Geo for Good Impact Award for her contributions to AI-driven Earth observation for disaster risk reduction and urban resilience. She serves as an invited expert to UN-Habitat on SDG indicators and as an expert contributor to UNDRR , leads the GEO AI4EO Working Group, and is an Associate Editor of IEEE Transactions on Geoscience and Remote Sensing, as well as a scientific committee member of major international remote sensing conferences.