Table 1.
Variable introduction and descriptive statistics.
Fig 1.
This figure illustrates the evolution trend of SDIGE from 2000 to 2019 in China, as well as in its eastern, central, western, and northeastern regions.
The SDIGE values are represented by stacked columns for each region, while the corresponding growth rates are depicted by dashed lines. The dark blue columns represent the SDIGE values for the eastern region, blue columns for the central region, yellow columns for the western region, and brown columns for the northeastern region. The red dashed line represents the SDIGE growth rate for China, the dark blue dashed line for the eastern region, the blue dashed line for the central region, the yellow dashed line for the western region, and the brown dashed line for the northeastern region. The SDIGE values are plotted on the left vertical axis, the growth rates are plotted on the right vertical axis, and the years are plotted on the horizontal axis.
Fig 2.
This figure, created using ArcGIS software, illustrates the spatial distribution characteristics of SDIGE in China for the years 2000, 2006, 2013, and 2019.
In the figure, the white areas indicate missing data, the red areas represent SDIGE values between 0 and 0.5, the pink areas represent SDIGE values between 0.5 and 0.8, the light apple green areas represent SDIGE values between 0.8 and 1.2, the teal areas represent SDIGE values between 1.2 and 2.0, and the leaf green areas represent SDIGE values greater than 2.
Fig 3.
This figure, created using ArcGIS software, illustrates the migration paths of SDIGE in China.
The yellow dots and circles represent the centroid and standard deviation ellipse of SDIGE in 2000, respectively. The red dots and circles represent the centroid and standard deviation ellipse of SDIGE in 2004, the green dots and circles for 2008, the purple dots and circles for 2011, the blue dots and circles for 2015, and the tan dots and circles for 2019.
Fig 4.
This figure, created using Stata software, illustrates the temporal evolution characteristics of SDIGE in China and its four major regions.
The horizontal axis represents the range of SDIGE values, and the vertical axis represents the probability density at corresponding values. The kernel function is specified for kernel regression, and the bandwidth indicates the degree of smoothing in the estimation. The green line represents the density distribution of SDIGE in 2000, the red line represents 2006, the blue line represents 2013, and the yellow line represents 2019.
Fig 5.
This figure shows the nested decomposition of China’s SDIGE Theil index into three stages from 2000 to 2019.
The SDIGE Theil index is represented by stacked columns, while the corresponding growth rates are depicted by dashed lines. The purple columns represent the inter-regional differences in China’s SDIGE, the blue columns represent the inter-provincial differences within regions, the yellow columns represent the inter-municipal differences within provinces, and the green columns represent the inter-county differences within municipalities. The purple dashed line represents the contribution rate of inter-regional differences to the overall differences, the blue dashed line represents the contribution rate of inter-provincial differences within regions, the yellow dashed line represents the contribution rate of inter-municipal differences within provinces, and the green dashed line represents the contribution rate of inter-county differences within municipalities. The SDIGE Theil index is plotted on the left vertical axis, the contribution rates are plotted on the right vertical axis, and the years are plotted on the horizontal axis.
Table 2.
Moran’s I Index of the SDIGE values of China’s counties.
Fig 6.
This figure, created using ArcGIS software, illustrates the LISA clustering maps of SDIGE in China for the years 2000, 2006, 2013, and 2019.
In the figure, white areas indicate no significant differences, red areas represent high-value clusters, pink areas represent high-value outliers surrounded mainly by low values, light blue areas represent low-value outliers surrounded mainly by high values, and dark blue areas represent low-value clusters.
Table 3.
The ordinary least squares analysis results of county SDIGE drivers in China.
Table 4.
VIF results of each driver.
Table 5.
GWR model parameters.
Fig 7.
This figure, created using origin software, shows the changing trends of the coefficients of the driving factors of SDIGE in China.
The influence coefficients of each variable on SDIGE are plotted on the vertical axis, while the years are plotted on the horizontal axis. The red color represents the influence coefficient and its time variation of lnPGDP on SDIGE, the green color represents lnPD, the blue color represents lnIS, the yellow color represents lnFD, and the purple color represents lnTR.
Fig 8.
This figure, created using ArcGIS software, illustrates the spatial distribution characteristics of the mean coefficients of lnPGDP, lnPD, lnIS, lnFD, and lnTR on SDIGE.
The colors red, pink, yellow, leaf green, and fir green represent increasing mean coefficients.