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Green Exposure as a People-Centered Metric for Green Infrastructures: A Shanghai Case Study.

Fabien Pfaender, Francesa Valsecchi, Xiulin Sun & Wei Chen

Abstract

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 chapter, 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. Exposure recognises how many and which kind of infrastructures exist, and, most importantly, how accessible they are and where they are placed in ordinary commuting and living patterns. To validate the concept of exposure, we use a twofold data-driven methodology that combines a Quantitative space analysis approach (from the domain and the tools of urban data science) and a Qualitative Space observation approach (from the field and tools of design and planning). The chapter details the methodology and the quantitative and qualitative data used for the analysis, considering Shanghai as a proof of concept: we provide exposure assessment of 5,000 communities in Shanghai, integrated with fieldwork to detail the nature of each infrastructure and their capacity for interaction. Through this twofold exposure concept and assessment method, we look at the green infrastructures, their presence, and meaning, and understand their role for the community to better inform planning and design solutions from a dynamic perspective.

Keywords

  • Green exposure
  • People-centric metric
  • Green infrastructure
  • Data-driven
  • Shanghai
  • Quantitative space
  • Qualitative space

Link

https://link.springer.com/chapter/10.1007/978-981-16-9174-4_10

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