Inversion and Spatial Heterogeneity of Regression Coefficients of Gravity Model for Population Flow in the Wuhan Metropolitan Area

Based on the Baidu migration data of 9 cities in the Wuhan metropolitan area during the Spring Festival in 2022, this paper cultivates the regression coefficients of the explanatory variables of the population flow gravity model at a multi-scale. Then the spatial heterogeneity analysis of these coefficients is performed to reveal the spatial features. The conclusions are drawn: 1. The regression coefficients of such variables as GDP, fiscal revenue, total retail consumer goods, and spatial distance are different, which proves that there is a large error in the estimation when simply using the Newtonian gravity model formula. The regression coefficient of spatial distance is the variable with the greatest impact on the strength of population flow. 2. The complexity of the regression coefficients at city scale increases significantly, and we find that the sum of the coefficients of each city is negatively associated with its economic strength, representing the realistic relationship between the coefficients and the variables. 3. The semivariograms fitting indicates that the described four variables at city scale exhibit obvious spatial heterogeneity that is caused by spatial auto-correlation.