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作者

Wei Liu;Wenjie Wu;Piyushimita Thakuriah;Jianghao Wang

来源

CITIES,Vol.97,Issue1,Article 102523

语言

英文

关键字

Big data;Human activity;Land use

作者单位

School of Computer Science and Engineering, University of New South Wales, Sydney, NSW 2052, Australia;Research Centre for Integrated Transport Innovation, School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW 2052, Australia;College of Economics, Jinan University, Guangzhou, 510632, China;School of Planning and Public Policy, Rutgers University, New Brunswick, NJ 08901, USA;Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;School of Computer Science and Engineering, University of New South Wales, Sydney, NSW 2052, Australia;Research Centre for Integrated Transport Innovation, School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW 2052, Australia;College of Economics, Jinan University, Guangzhou, 510632, China;School of Planning and Public Policy, Rutgers University, New Brunswick, NJ 08901, USA;Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

摘要

The application of location-based social media big data in urban contexts offers new and alternative strategies for understanding city liveliness in developing countries where traditional census data are poor. This paper demonstrates how the spatial-temporal distribution of China's Tencent social media usage intensities can be effectively used as a proxy for modelling the geographic patterns of human activity at fine scales. Our results suggest that the spatially-temporally contextualized nature of human activity is dependent upon land use mixing characteristics. With billions of social media data being collected in the virtual world, findings of this study suggest that land use policies to delineating the density, orderly or disorderly geographic patterns of human activity are important for city liveliness.