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Proposing Institution

Professur für Signalverarbeitung in der Erdbeobachtung
Project Manager

Prof. Dr. Xiaoxiang Zhu
Arcisstr. 21
80333 München
By 2050, around three quarters of the world’s population will live in cities. However, the urbanization does not automatically lead to a golden future of mankind, but the ongoing new dimension of urbanization poses fundamental challenges to our societies across the globe. This transition inherently alters the physical dimensions and configurations of cities at all scales. New phenomena of globalization’s new urban scale and form emerge, such as urban corridors, megaregions, informal settlements, refugee camps. Among many others, they have raced too far ahead of our current understanding of urbanization which is mostly based on the United Nation’s population figure.For instance, although one third of the global population live in slums, we have no global knowledge on the dimensions, patterns, morphologies and locations of those. Beyond this, even the population densities in slums are suspected to be grossly underestimated by current official statistics. This is an example of the immense spatial knowledge gaps we are and will be facing. Therefore, the scientific question that this project tries to answer is how does the global urban geographic figures, including geometry, thematic, population density, evolve over time, and in what detail can we observe and measure them. By exploiting the recent advances in signal processing and computer vision, the aim of this project is to for the first time systematically fuse the remote sensing data acquired by sensors mounted on diverse platforms, in particular from Earth observation satellites, and the massive data available from GIS and social media to map 3D urban infrastructures and their evolution over time, i.e. 4D, in high resolution and on a global scale. The outcome of this project will create a first and unique global and consistent 3D/4D spatial data set on the urban morphology of settlements, and a multidisciplinary application derivate assessing population density. This is seen as a giant leap for urban geography research as well as for formation of opinions for stakeholders based on resilient data.

Impressum, Conny Wendler