Measuring Urban Spatial Activity Structures: A Comparative Analysis

Lihua Xu, Huifeng Xu, Tianyu Wang, Wenze Yue, Jinyang Deng and Liwei Mao
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Lihua Xu: School of Landscape Architecture, Zhejiang Agriculture & Forestry University, Hangzhou 311311, China
Huifeng Xu: School of Landscape Architecture, Zhejiang Agriculture & Forestry University, Hangzhou 311311, China
Tianyu Wang: Department of Land Management, Zhejiang University, Hangzhou 310058, China
Wenze Yue: Department of Land Management, Zhejiang University, Hangzhou 310058, China
Jinyang Deng: Division of Forestry & Natural Resources, West Virginia University, Morgantown, WV 26506, USA
Liwei Mao: Hangzhou City Planning & Design Academy, Hangzhou 310012, China

Sustainability, 2019, vol. 11, issue 24, 1-17

Abstract: Human activity recognition has been of interest in the field of urban planning. This paper established a general framework by which expected human activity intensity (HAI) measured by the built environment and factual HAI measured by the Baidu thermal chart were estimated and comparatively analyzed so as to identify abnormal human activities in Hanghzou, China. Three elements of the built environment (i.e., residential density, road connectivity, and land-use mixing degree) from multi-source data with high precision are selected to assess the expected HAI. Results indicate Hangzhou has evolved into a polycentric city with three urban clusters. In addition, a significant positive correlation exists between the two types of HAIs. However, there are areas with spatial mismatches, particularly in the “urban village” and new towns, suggesting human activities are not equally distributed all over the city. Research implications, limitations, and future research needs are discussed.

Keywords: human activity intensity; built environment; big data; Baidu thermal chart; land-use mixing degree; road connectivity; residential density (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
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