Multifunctional development patterns and driving mechanisms of high-speed rail station areas in the Yangtze River Delta, China

High-speed rail (HSR) stations play an important role in shaping urban spaces and propelling regional development. Amid rapid urbanization and expansion of HSR networks, HSR station areas tend to transition from singular transport nodes into multifunctional urban spaces. Although previous studies have assessed the vitality and development potential of station areas, they tend to overlook the diversity in functional characteristics and the varied factors shaping these areas. This study investigates the evolution and differentiation of 197 HSR station areas in the Yangtze River Delta (YRD), China in 2022, focusing on identifying dominant functional types and their determinants of functional differentiation. Offering a novel approach, this study develops a quantitative framework to classify the dominant functional types within HSR station areas, bridging a gap in the literature that has primarily relied on qualitative classifications. The Random Forest algorithm combined with SHAP (SHapley Additive exPlanations) analysis is employed to reveal the mechanisms that influence each functional type, providing a nuanced understanding of their dynamic characteristics. Results reveal the spatial scope of HSR station areas across various hierarchies and identify four dominant functional types: transportation function-dominant, business function-dominant, residential function-dominant, and comprehensive service function-dominant station areas. Each type exhibits distinct economic and geographic characteristics, reflecting specific urban development needs and growth patterns shaped by different factors. Based on these findings, this study proposes policy recommendations aimed at optimizing station area functions, thereby supporting the high-quality development of urban spaces induced by HSR development. • The dominant functional types of the 197 HSR station areas in the China’s Yangtze River Delta (2022) were identified. • The Random Forest algorithm combined with SHAP (SHapley Additive exPlanations) analysis was used to reveal key factors. • Four dominant functional types of transportation, business, residential, and comprehensive service were examined. • Each type exhibits distinct economic geographic characteristics shaped by factors at station area, urban and regional scales.