地理学视角下城市复杂性研究综述——基于近20年文献回顾

doi:10.18306/dlkxjz.2022.01.014

Abstract

Abstract:

As an open human-natural system with a complex organizational structure, the urban system has always been the core object of geographic research. Using the published literature from 2000 to 2020 as the data, we developed a new approach by combing quantitative and qualitative analyses to investigate related research results from the perspective of geography in terms of conceptual connotations, research themes, and technical methods, and put forward the future research needs. Over the past 20 years, urban complexity research in China has gradually shifted from single-scale pattern, process, and mechanism research to integrated and comprehensive research on complex interaction processes at multiple scales, and has gradually formed four major themes, including urban facility networks, urban habitat, urban economic activities, and urban spatial governance. In terms of data analysis methodology, the research has gradually shifted to multi-dimensional scenario analysis supported by spatial technology and social computing with panoramic whole-life cycle data. In the future, urban complexity research from the perspective of geography needs to further strengthen the construction of urban digital infrastructure and life cycle information collection capability, deepen the comprehensive measurement and monitoring of urban ecological-economic systems from the perspective of geospatial pattern, and study the urban flow space under the influence of cross-regional development mechanism.

Key words: urban complexity, human-natural system, urban geography, urban spatial structure, urban governance

XUE Bing, ZHAO Bingyu, LI Jingzhong. Urban complexity studies from the perspective of geography:A review based on the literature in the past 20 years[J].PROGRESS IN GEOGRAPHY, 2022, 41(1): 157-172.

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研究方法	原理	主要参数	应用场景
分形理论	复杂现象内部的自相似性,分为多个相对独立的部分,根据分形维度和分形元特征刻画现象内部、现象间的互动行为,探究混沌事物内部的结构^[135]	长度、分支及盒子维数	土地利用、城市边界、城市化空间过程
元胞自动机	复杂系统通过相对简单的决策准则演化而成^[134]		细节模拟、分形模拟、城市增长机制
复杂网络	复杂网络是指具有自组织、自相似、吸引子、小世界、无标度中部分或全部性质的网络,简而言之即呈现高度复杂性的网络。其复杂性主要体现在结构复杂、网络演化、节点和连接多样性、动力学复杂性等方面^[136]	特征路径长度、聚合系数	城市群、多级道路、公共交通(公交、地铁、高铁)、产业、流空间
空间句法	空间句法是将大尺度复杂网络分割成大量小尺度的基本单元,以量化的方式描述节点间的几何、距离和拓扑等,说明空间分异特征^[137]	连接值、集成度、深度值、智能值和可达性评价值	城市群、多级道路、公共交通(公交、地铁、高铁)、产业、流空间
机器学习	机器学习是一类综合的方法,通过模拟人类的学习行为,获取新的知识或技能,进行复杂系统的分类、辨别和推演。主要模型有决策树、随机森林、人工神经网络与贝叶斯学习等^[138]		智慧城市、数字孪生城市

Urban complexity studies from the perspective of geography:A review based on the literature in the past 20 years

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