Resident Effect Perception in Urban Spaces to Inform Urban Design Strategies

Zichen Zhao, Zhiqiang Wu (), Shiqi Zhou (), Wen Dong, Wei Gan, Yixuan Zou and Mo Wang
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Zichen Zhao: College of Design and Innovation, Tongji University, Shanghai 200093, China
Zhiqiang Wu: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Shiqi Zhou: College of Design and Innovation, Tongji University, Shanghai 200093, China
Wen Dong: Department of Civil, Environment & Geomatics Engineering, University College London, 22 Gordon St, London WC1E 6BT, UK
Wei Gan: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Yixuan Zou: Department of Civil, Environment & Geomatics Engineering, University College London, 22 Gordon St, London WC1E 6BT, UK
Mo Wang: College of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China

Land, 2023, vol. 12, issue 10, 1-24

Abstract: In the field of urban design, current research has shifted towards resident preference perception and computer-aided design methods that rely on deep learning techniques. In this study, we aimed to provide a quantitative design method for urban space design that could take into account the preferences of different populations. Through empirical research, we collected real urban space and population data, which we then quantified using advanced intelligent recognition tools based on deep learning techniques. Our ensuing analysis illuminated the intricate interplay between constituent elements of urban spaces and the structural and emotional changes of residents. By taking into account the specific driving relationships between each element and residents, we proposed a new evaluation methodology for constructing an intelligent design evaluation model for urban spaces. This intelligent design evaluation model was subsequently used to evaluate the urban space both pre- and post-design. The standard deviation of the difference results demonstrated that the design option (SD value = 0.103) and the desired option for Space 1 were lower than the current option (SD value = 0.129) and the expected scheme. Our findings provide quantitative configuration strategies and program evaluation for urban space design, thus helping designers to design urban spaces that are more popular with residents.

Keywords: resident effect; intelligent evaluation; urban space; space elements; emotion perception (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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