Research on the Spatial Differences and Influencing Factors of Regional Economic Development-Taking 21 Cities in Guangdong Province as Examples

Firstly, Moran's I in the spatial autocorrelation analysis method is used, and Geoda software is applied to sequentially analyze the spatial distribution of GDP per capita of 21 cities in Guangdong Province in 2018, the global autocorrelation test, the local autocorrelation test, as well as explore its spatial correlation and spatial heterogeneity. It is concluded that there is a significant spatial autocorrelation of GDP per capita of 21 cities in Guangdong Province in 2018. Secondly, the trend surface analysis method of ArcGIS is applied to conduct a three-dimensional trend analysis of the GDP per capita of each city in Guangdong Province in 2018. Finally, a spatial regression model is used to calculate the influencing factors of the spatial differences of GDP per capita of 21 cities in Guangdong Province in 2018, and it is concluded that the three factors of total retail sales of consumer goods, foreign exchange income from international tourism, internal expenditure of R&D funds have a positive relationship with GDP per capita, however the number of employed persons at the end of the year has a negative relationship with GDP per capita in Guangdong province in 2018.