Handbook of Planning Support Science
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Handbook of Planning Support Science

Edited by Stan Geertman and John Stillwell

Encompassing a broad range of innovative studies on planning support science, this timely Handbook examines how the consequences of pressing societal challenges can be addressed using computer-based systems. Chapters explore the use of new streams of big and open data as well as data from traditional sources, offering significant critical insights into the field.
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Chapter 6: Methodology and application of data augmented design: a case study of urban redevelopment design for the Panyu-Xinhua Area, Shanghai

Tianyu Su, Shihui Li, Jing Li, Hungyu Chou and Ying Long

Abstract

With the rise of city science and data science, big data such as records of bike-sharing, mobile phone signalling, public transportation records and open data from various sources, jointly promote the formation of a new data environment, which provides a stable underpinning for the emergence of innovative planning and design methodologies. Also, historical areas in the existing built environment require renewal and redevelopment to adjust to the spatial requirements of the twenty-first century. Given this situation, this chapter delivers a new quantitative methodology for urban planning and design, termed data augmented design (DAD), and tests its application in an urban redevelopment design project. The main steps and two primary methods of DAD for urban redevelopment design – existing condition analysis and spatial parameter extraction – are introduced. The chapter applies these methods in the urban redevelopment design for the Panyu-Xinhua Area in Shanghai, China. Their effectiveness is evaluated from the perspective of planners, officers and citizens. I addition to the academic and practical contributions, potential applications, potential bias and future research using DAD methods are also discussed.

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