Human & Data centric approach of Green Spaces in Shanghai



A green spaces of Shanghai dataset that was two-years in the making allows for a series of human centric analysis of how green is spread out, used and ultimately affecting our lifes. Green Infrastructures refers to components of the built environment, encompassing various shapes and functions from leisure to utilitarian through aesthetics, including elements entirely natural to entirely artificial. In this spectrum of intrinsic natures, purposes, and sizes, green infrastructures are mainly defined as static objects placed into an environment. As such, the definition fails to depict the influence such infrastructures exert on urban dwellers.

In this study, we propose the concept of “exposure” as a metric that considers green infrastructures not as static outcomes of planning and design but rather as a component of a dynamic relationship involving the citizens. To assess the green exposure, we used urban data analysis using a large variety of methods to harvest, clean, explore and build green influence models on society.


Fabien PFAENDER is an urban data scientist. His research focuses on exploring urban systems using a wide range of interdisciplinary methods mixing quantitative & qualitative approaches. The research put a strong emphasis on data as a common language between experts of different fields. Since 2011 he is working in UTSEUS, an elite Sino-French engineering institute in Shanghai University where he is currently acting French Director. He is leading an international workgroup to develop urban data exploration and mining strategy for interdisciplinary scientist. He is also visualization and data science expert for various Big Data and Smart Cities related companies in France and in China. His latest project is massive data powered comparative framework of cities in the world.

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