Abstract:

As a useful spatial interaction modeling method, gravity models have been widely applied in geographic research. The results of gravity models are sensitive to model parameters, which may lead to significant variation in modeling results when different sets of parameters are used. Therefore accurate parameters are essential to the application of gravity models. Although there have been various studies on the calibration of gravity model parameters, spatial heterogeneity of model parameters has not been carefully considered due to the lack of necessary data for such analysis. In this study we took the volume of China's railway passengers between city pairs in 2010 as the indicator of the magnitude of spatial interaction between cities. Nodal attraction of cities was depicted by the total disposable income of residents in the city areas, which represents the attraction of a city. Compared to the existing literature, this study modified the basic form of gravity model and introduced frequency of trains as a variable into the model, representing the spatial separation between city pairs along with travel time. This adjustment produced improved goodness-of-fit result. Three parameters in the modified gravity model were tested: nodal attraction, α; travel time, β; and frequency, γ. Spatial heterogeneity of each parameter was analyzed by means of regression analysis and GIS. The results show that β has the largest range, followed by α and γ. The research indicates that remarkable spatial heterogeneity exists and cannot be overlooked. Using a single set of parameters of gravity model for different regions may not be appropriate.

Key words: railway passenger flow, distance decay parameter, gravity model parameter, spatial distribution, China