Quantitative research on the capacity of urban underground space – The case of Shanghai, China

This paper presents a case study on predicting demand for Urban Underground Space use (UUS) using recent data from Shanghai, China. Building on recent research that quantifies UUS, we analyze the relationship between the amount of UUS and other urbanization factors including population density, annual GDP per capita, and real estate price. Specifically, we utilize multivariate regression analysis with a Box–Cox transformation to construct a predictive model that assesses the demand for underground space in urban districts. The model indicates that population density and GDP per capita both have independent positive predictive power on the density of UUS use. The effect of real estate price is offset by these two factors. This model can serve as a foundation for developing urban master plans as well as conducting future comparative studies.

► We examine and model the relationship between UUS and its affecting factors to forecast the future UUS demand.
► Population density as a main factor stimulates greatly UUS.
► GDP/(cap year) as a minor factor plays a weak positive role in UUS.
► Real estate price has no effect on UUS.
► The predicting model conforms to multiple linear model.