Abstract:

Economic density is one of the most important indicators of regional economic development and agglomeration.We studied 38 counties in Chongqing City,China and developed a model for a comprehensive measure based on per capita and land factors.The weights of measure indicators were determined by principal component analysis.Principle component analysis with the technique for order preference by similarity to ideal solution was applied to measure economic density.Our metric of economic density was based on the Euclidean distance between the object value and its optimal value and worst value.The economic density composite index and ranking were obtained for each object.We used GIS to generate maps of economic density distributions in Chongqing City,which revealed changes in the spatial patterns of economic density over time.We used the rule of spatiotemporal variation of global and local spatial autocorrelation on county economic density as an opportunity to discuss the main factors affecting the levels of economic density.We identified three major findings: (1) the comprehensive economic density indices were calculated and ranked for 38 counties during four time periods.Economic density generally increased over time,while internal differences gradually decreased.(2) In terms of its overall distribution,economic density in Chongqing decreased from the center and northwest to the northeast and southeast.The distributions in areas with high economic density in the central region were significantly different from those with low density in the surrounding areas.(3) From the perspective of spatial autocorrelation,the Moran’s I index was greater than 0,showing a positive correlation,suggesting that economic density tended to gather in space.Moreover,the urban areas characterized by LH-type gradually decreased,and economic density became more spatially polarized.Hotspots and sub-hotspots of economic density were mainly distributed in the western part of Chongqing,while the secondary coldspots and sub-coldspots were mainly distributed in the east.The results of this study provide a scientific basis for the city’s strategies for long-term development.

Key words: economic density, comprehensive measure, spatiotemporal evolution, PCA-TOPSIS, county