Global urbanization has lead to new challenges for urban planners aiming to reduce poverty and ensure sustainability. To overcome these challenges, we need sufficient data on a global scale. Xiaoxiang Zhu combines satellite and social media data with machine learning to generate a global model of all urban areas. Her models depict 3D shapes and illustrate the functions of buildings, as well as temporal changes, in cities. By providing open access to this data, Xiaoxiang's research group will enable broad impacts globally, from helping authorities improve slum conditions, providing evidence for a more accurate census, and numerous other end goals.

About Xiaoxiang Zhu

Xiaoxiang Zhu is the professor for Signal Processing in Earth Observation at TUM. Xiaoxiang has always been fascinated by space and enjoyed solving mathematically demanding tasks as a child, which are perfectly entwined in the field of satellite Earth observation.