【摘要】 科学、客观地评估地铁站区协同发展水平并进行分类，对轨道交通运营效率的提升、城市土地开发与资源配置的集约发展具有重要意义。本文基于地理信息系统技术（GIS）与多源大数据，利用“节点—场所”扩展模型对西安地铁2号线25个站区进行科学评估与系统化分类。研究结果显示，西安地铁2号线各站区的协同性及发展水平存在较大差异，尚未实现节点、场所和功能属性的动态协调发展。本研究通过扩展模型及指标评估技术，构建了一套便于规划建设者因地制宜、精准施策的地铁站区评估分类方法，为地铁站区的更新再开发及新建站区的规划建设提供决策支撑，助力相关工作科学、有序地开展。更多还原

【Abstract】 Based on the extended "node-place-function" model, combined with Geographic Information System(GIS) spatial analysis technology and multi-source big data mining methods, this paper conducts a systematic evaluation and scientific classification of the transportation-land-function collaborative development level of all 25 station areas along Xi’an Metro Line 2. Against the backdrop of the continuous advancement of rapid urbanization in China and the widespread application of the Transit-Oriented Development(TOD) model in major cities, metro station areas, as key nodes of urban space, are confronted with an increasingly prominent imbalance between traffic supply capacity and land use demand. Addressing this contradiction is of crucial practical significance for optimizing urban spatial structure and improving the comprehensive carrying capacity of cities.The traditional two-dimensional "node-place" model is extended by incorporating a "function" dimension, encompassing walkability, road texture, facility density, and environmental suitability. A comprehensive evaluation system is established, consisting of 3 primary dimensions, 11 sub-indicators, and 17 specific metrics. Data sources include land use data from Xi’an Municipal Bureau of Natural Resources and Planning, POI data from Amap, architectural and road network data from OpenStreetMap, real estate prices from Lianjia.com, and crowd thermal data from Baidu Maps. Entropy weight method is employed to determine indicator weights, ensuring the objectivity of evaluations. K-Means clustering algorithm is then applied to classify the station areas into six distinct TOD types: Low-Value Dependent, Low-Value Place-Dominant, Medium-Value Balanced, Medium-Value Function-Dominant, High-Value Node-Deficient, and High-Value Pressured. Spatial analysis reveals a concentric circle distribution pattern, with performance decreasing radially from the city center(centered at Zhonglou Station) to the suburban terminals.The research results indicate that there are significant differences in the collaborative development level of each station area along Xi’an Metro Line 2. Benefiting from mature location advantages, urban core station areas exhibit high place value and high function value, but they are simultaneously faced with the development dilemma of insufficient node traffic carrying capacity. Restricted by location conditions and development foundation, suburban station areas have a generally low level of collaborative development, with relatively lagging infrastructure construction. The introduction of the "function" dimension has effectively enhanced the model’s ability to capture the complexity of TOD development, and more accurately reflects the collaborative coupling relationship among traffic supply, land use and functional services compared with the traditional model. The scientific evaluation and classification framework for metro station areas constructed in this study provides practical decision-making basis for urban planners and policymakers. The proposed research methods and results can offer scientific guidance for the functional renewal and quality improvement of existing metro station areas as well as the planning, design, development and construction of new metro station areas, thereby promoting the intensive and efficient utilization of urban land resources and the sustainable development of rail transit systems. Future research will further focus on optimizing the evaluation index system, introducing more advanced machine learning classification algorithms, and combining long-time series dynamic data to improve the accuracy and timeliness of evaluation and classification results.更多还原