Quantitative assessment method on urban vitality of metro-led underground space based on multi-source data: A case study of Shanghai Inner Ring area

Abstract

Unprecedented rail transit development in China’s megacities has boosted the utilization of metro-led underground space (MUS). Vigorous MUS is critical for sustainable underground space use and urban development. To date, the urban vitality of MUS based on multi-source big data has been far less researched. Although the mechanism and influence factors of MUS vitality have been revealed in previous studies, its quantitative assessment method still remains an important challenge. In this paper, the assessment indicator system was established, considering driving factors of the spatial accessibility, coordination of MUS and ground space, and development scale. MUS samples in Shanghai Inner Ring Area were evaluated regarding urban vitality using the technique for order preference by similarity to an ideal solution (TOPSIS) method. K-means cluster analysis was adopted to mine the features of vitality distribution, and three types of MUS as well as their characteristics were systematically summarized. Based on the spatial function, the MUS was further regrouped to investigate the regularities of MUS vitality in distinct categories. To validate the proposed method, regression analysis was conducted using location-based service data and smart card data. The results show that the assessment results basically accord with the validation data. However, there is still some room for improvement concerning MUS vitality. The proposed assessment method provides an efficient tool for planning and design of MUS in different scenarios, and the practical understanding of MUS development was strengthened.