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A Systematic Measurement of Street Quality through Multi-Sourced Urban Data: A Human-Oriented Analysis

1
Department of Urban Planning and Design, Faculty of Architecture, The University of Hong Kong, Hong Kong, China
2
College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2019, 16(10), 1782; https://doi.org/10.3390/ijerph16101782
Received: 16 April 2019 / Revised: 14 May 2019 / Accepted: 15 May 2019 / Published: 20 May 2019
(This article belongs to the Section Environmental Health)
Many studies have been made on street quality, physical activity and public health. However, most studies so far have focused on only few features, such as street greenery or accessibility. These features fail to capture people’s holistic perceptions. The potential of fine grained, multi-sourced urban data creates new research avenues for addressing multi-feature, intangible, human-oriented issues related to the built environment. This study proposes a systematic, multi-factor quantitative approach for measuring street quality with the support of multi-sourced urban data taking Yangpu District in Shanghai as case study. This holistic approach combines typical and new urban data in order to measure street quality with a human-oriented perspective. This composite measure of street quality is based on the well-established 5Ds dimensions: Density, Diversity, Design, Destination accessibility and Distance to transit. They are combined as a collection of new urban data and research techniques, including location-based service (LBS) positioning data, points of interest (PoIs), elements and visual quality of street-view images extraction with supervised machine learning, and accessibility metrics using network science. According to these quantitative measurements from the five aspects, streets were classified into eight feature clusters and three types reflecting the value of street quality using a hierarchical clustering method. The classification was tested with experts. The analytical framework developed through this study contributes to human-oriented urban planning practices to further encourage physical activity and public health. View Full-Text
Keywords: systematic measurement; street quality; multi-sourced urban data; urban design; human-oriented; Shanghai systematic measurement; street quality; multi-sourced urban data; urban design; human-oriented; Shanghai
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Zhang, L.; Ye, Y.; Zeng, W.; Chiaradia, A. A Systematic Measurement of Street Quality through Multi-Sourced Urban Data: A Human-Oriented Analysis. Int. J. Environ. Res. Public Health 2019, 16, 1782.

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