移动定位大数据视角下的人群移动模式及城市空间结构研究进展

doi:10.18306/dlkxjz.2018.07.002

Abstract

Abstract:

Understanding human mobility patterns and spatial structure is of great important to urban planning, traffic management, emergence response, and so on. With the development of information and communication technologies, it is possible to collect large-scale, long-term human tracking data, which brings great opportunities and challenges for human mobility behavior studies. This article first introduces the main datasets being used for studying human mobility patterns, then reviews the recent progress from the perspectives of human travel behavior and urban spatial structure respectively. We found that most studies follow the route of "data-human travel behavior-urban spatial structure," mining and understanding human mobility patterns from the datasets and further giving insights on the characteristics of urban spatial structures. However, there exist few studies on the influence of urban spatial structure on human travel behavior. In the future, it is necessary to integrate multi-source spatiotemporal data to understand the interaction between human mobility and urban spatial structure, develop spatiotemporal analysis theory and models for dealing with mobile location big data, and focus on understanding the coupling relationship between human mobility and urban spatial structure.

Key words: mobile location big data, human mobility, urban spatial structure, progress

Xiping YANG, Zhixiang FANG. Recent progress in studying human mobility and urban spatial structure based on mobile location big data[J].PROGRESS IN GEOGRAPHY, 2018, 37(7): 880-889.

Figures/Tables 1

References 37

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Recent progress in studying human mobility and urban spatial structure based on mobile location big data

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