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To effectively and objectively evaluate the spatial efficiency of rail transit station areas, seventeen typical rail station areas in Xi'an were selected as the research object. An evaluation system for spatial efficiency was constructed based on data from field research, satellite images, Baidu heat maps, and station passenger flow statistics. Key factors such as land use, transportation systems, social aspects, and spatial efficiency are considered in the framework. A data envelopment analysis (DEA) method was used to evaluate the spatial efficiency of these sample station areas. The results are as follows. ① An incomplete symmetric relationship exists between the Constant Returns to Scale Technical Efficiency (Crste) and the Variable Returns to Scale Technical Efficiency (Vrste) of station area spatial efficiency. The keys to improving station area spatial efficiency include reducing redundant resource investments and establishing a rational resource allocation structure. ② For high-efficiency station areas, the Crste and Vrste are relatively high, with an overall increasing return to scale efficiency (Scale). In medium-efficiency station areas, the Crste is relatively high, but either Vrste or Scale is low. In low-efficiency station areas, the Crste is moderate, and both Vrste and Scale are low. The findings provide a reference for the intensive use of land around Xi'an rail stations, as well as support for the sustainable operation of rail transit. [ABSTRACT FROM AUTHOR]

Rail transit station areas (RSAs) are heralded as a transformative approach to urban planning, emphasizing the integration of transportation, housing, and commercial development to foster sustainable and inclusive cities. This study presents a comprehensive exploration of the interplay between transit-oriented development (TOD) economic performance and social equity in RSAs, employing advanced methodologies, like eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAPs), to decipher the complex relationships between TOD characteristics and social equity outcomes. Focused on Dalian's urban center, this study integrates diverse datasets, including mobile location, geospatial, and economic price data, to construct a nuanced analysis framework within the NPE (node–place–economic) model. The results indicate that economic factors significantly impact overall social equity, particularly influencing key variables, such as weekday and weekend commuter population densities. Local explanatory plots reveal that economic performance variables associated with transportation development exhibit a broad non-linear impact on social equity in RSAs. This study advances equitable urban development through TOD by stressing the importance of factoring in multiple variables in RSA planning. This approach is vital for creating synergistic effects, fostering equitable spatial planning, and has both theoretical and practical benefits for improving residents' well-being. [ABSTRACT FROM AUTHOR]

To effectively and objectively evaluate the spatial efficiency of rail transit station areas, seventeen typical rail station areas in Xi’an were selected as the research object. An evaluation system for spatial efficiency was constructed based on data from field research, satellite images, Baidu heat maps, and station passenger flow statistics. Key factors such as land use, transportation systems, social aspects, and spatial efficiency are considered in the framework. A data envelopment analysis (DEA) method was used to evaluate the spatial efficiency of these sample station areas. The results are as follows. ① An incomplete symmetric relationship exists between the Constant Returns to Scale Technical Efficiency (Crste) and the Variable Returns to Scale Technical Efficiency (Vrste) of station area spatial efficiency. The keys to improving station area spatial efficiency include reducing redundant resource investments and establishing a rational resource allocation structure. ② For high-efficiency station areas, the Crste and Vrste are relatively high, with an overall increasing return to scale efficiency (Scale). In medium-efficiency station areas, the Crste is relatively high, but either Vrste or Scale is low. In low-efficiency station areas, the Crste is moderate, and both Vrste and Scale are low. The findings provide a reference for the intensive use of land around Xi’an rail stations, as well as support for the sustainable operation of rail transit.

For the intensive, efficient, and sustainable utilization of land resources, it is of great significance to optimize the spatial allocation of different types of land use intensity in rail transit station areas. The current land use optimization model has some shortcomings in objective function, constraint conditions, and the solution process. In response to this, a new multi-objective optimization model for rail transit station land use was built. With station space efficiency as the starting point, the three objectives of the model optimization were the traffic volume, environment quality, and land balance of the rail transit station, and the constraint conditions were the plot ratio, environment quality, and efficiency level. Lingo was used to solve the optimal plot ratio of different types of land use intensity. Compared with the non-inferior solution of the rail transit station area multi-objective original model, the ideal plot ratio of various land uses obtained by the optimized new model was more reasonable. There was a relatively large gap between the non-inferior solutions of some original models and the actual conditions. In contrast, the optimized new model had stronger maneuverability. The deviation ranges of the two models were −0.4% to 0.9% on the residential land plot ratio adjustment index, −3.2% to 4.8% on the public land plot ratio adjustment index, and 1.1% to 1.9% on the commercial land plot ratio adjustment index. This research aimed to provide a basis and reference for the land use and planning of Xi'an rail transit station. [ABSTRACT FROM AUTHOR]

For the intensive, efficient, and sustainable utilization of land resources, it is of great significance to optimize the spatial allocation of different types of land use intensity in rail transit station areas. The current land use optimization model has some shortcomings in objective function, constraint conditions, and the solution process. In response to this, a new multi-objective optimization model for rail transit station land use was built. With station space efficiency as the starting point, the three objectives of the model optimization were the traffic volume, environment quality, and land balance of the rail transit station, and the constraint conditions were the plot ratio, environment quality, and efficiency level. Lingo was used to solve the optimal plot ratio of different types of land use intensity. Compared with the non-inferior solution of the rail transit station area multi-objective original model, the ideal plot ratio of various land uses obtained by the optimized new model was more reasonable. There was a relatively large gap between the non-inferior solutions of some original models and the actual conditions. In contrast, the optimized new model had stronger maneuverability. The deviation ranges of the two models were −0.4% to 0.9% on the residential land plot ratio adjustment index, −3.2% to 4.8% on the public land plot ratio adjustment index, and 1.1% to 1.9% on the commercial land plot ratio adjustment index. This research aimed to provide a basis and reference for the land use and planning of Xi’an rail transit station.