High-speed railway (HSR) stations play an important role in shaping the development/redevelopment of the surrounding areas. While different studies have been conducted to explore station area development, they tend to simplify the conceptualisation of station area development and lack a comprehensive perspective that captures how different variables at multiple levels are interacted with station area development. This research proposes the ‘node-place-network-city’ framework, an innovative extension of the traditional ‘node-place’ model, to analyse station area development. Focusing on 123 HSR station areas in the Yangtze River Delta as of 2018, this research employs spatial big data to explore the intricate relationships between various city and network indicators and station area development. Unlike previous studies that have typically simplified station area development and treated the relationships as linear, this study adopts a decision tree model. This method effectively identifies diverse typologies of HSR stations and facilitates the formulation of tailored development strategies for each type. This research significantly contributes to the theoretical understanding of HSR station area development and provides valuable and actionable insights for urban planners and policymakers. It marks a step forward in comprehensively assessing and guiding the development of HSR station areas, thereby offering a robust framework for both academic research and practical application in spatial planning.

中文翻译：

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研究高铁站区发展动态的“节点-地点-网络-城市”框架：车站类型和发展策略


高速铁路（HSR）车站在塑造周边地区的开发/再开发方面发挥着重要作用。虽然已经进行了不同的研究来探索站区开发，但它们往往简化了站区开发的概念，并且缺乏全面的视角来捕捉多个层面的不同变量如何与站区开发相互作用。本研究提出了“节点-场所-网络-城市”框架，这是传统“节点-场所”模型的创新延伸，用于分析站区发展。本研究以截至2018年长三角地区123个高铁站区为研究对象，利用空间大数据探讨各类城市及网络指标与站区发展之间的错综复杂关系。与以往的研究通常简化站区开发并将关系视为线性不同，本研究采用决策树模型。该方法有效地识别了高铁车站的不同类型，并有助于为每种类型制定量身定制的发展策略。这项研究极大地促进了对高铁站区发展的理论理解，并为城市规划者和政策制定者提供了有价值且可操作的见解。它标志着在全面评估和指导高铁站区发展方面向前迈出了一步，从而为空间规划的学术研究和实际应用提供了坚实的框架。