期刊
HABITAT INTERNATIONAL
卷 115, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.habitatint.2021.102397
关键词
Urban center; subcenter; Identification methodology; Literature review
资金
- National Natural Science Foundation of China [71901082]
- Leverhulme Trust [ECF-2019-536]
The global urbanization has led to the emergence of metropolises with complex urban spatial structures characterized by multiple urban centers/subcenters (UCSs). The formation and development of UCSs are influenced by various factors, and their planning plays a crucial role in shaping the future development of a city. Research on UCSs has shown mixed findings due to conceptual ambiguity, diverse data types, spatial scales, and identification methods, highlighting the need for objective, context-appropriate, theoretically supported, and data-based approaches.
The global urbanization has produced a number of metropolises with complex urban spatial structures. Compared with monocentric cities, these metropolises typically have multiple urban centers/subcenters (UCSs). The formation and development of UCSs is driven by physical, economic and human-activity-related factors. The planning of UCSs can significantly affect the future development of a city. Considerable research has been conducted to investigate the different morphologies and functions of UCSs. Mixed findings have been reported for the identification of UCSs, which is mainly due to the ambiguity of their conceptualizations, variety of data types, different spatial scales, and diverse identification methods. Therefore, existing approaches must be evaluated to clarify their use in different social, economic and environmental contexts. In this study, we conducted a systematic literature review of 70 journal papers published from 1990 to 2020 with respect to the concepts, data, analytical units, and methods used to identify UCSs. By comparing their strengths and weaknesses, the critical issues of these methodological frameworks are identified. The findings suggest that the preferred path for identifying UCSs is one that is objective, context-appropriate, theoretically supported, and based on data.
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