Comparison of PCA and fractal analysis approaches in the evaluation of air-HSR intermodal network

Abstract

The importance of air transport and high-speed rail (HSR) in building comprehensive transportation systems has grown substantially in recent years. Evaluating the air-HSR intermodal network is essential in identifying the developmental hurdles and charting a course for its progress. This paper compares alternative methods for evaluating the performance of air-high-speed rail (HSR) intermodal networks, with a focus on developing a comprehensive index framework that considers multiple perspectives. Ten Chinese cities with viable air-HSR connectivity are assessed using principal component analysis (PCA) and Fractal Analysis. The study finds that while PCA provides a valuable high-level overview of air-HSR intermodal network integration by identifying major trends and key components, Fractal Analysis offers a complementary and more detailed evaluation by capturing local characteristics and complex spatial interactions. The combined use of PCA and Fractal Analysis ensures a comprehensive assessment, highlighting that Fractal Analysis is particularly effective for evaluating complex intermodal networks when spatial coherence and local variations are critical. The analysis provides decision-makers with a more balanced understanding of the intricate interrelationships between various aspects of the air-HSR intermodal network, which can inform policy decisions related to transportation infrastructure investment and development.