Abstract:

The spatial distribution of world population varies considerably from region to region due to differences in geography and economic development, which requires a specific scale of population grid for population spatialization in different regions. A uniform grid scale can only represent the spatial distribution of population at one grid scale, which leads to poor representation for more densely or sparsely populated areas. In order to express the spatial distribution of the population more accurately and determine the appropriate scale of the population grid for a given area, this paper proposes a method to determine the scale of suitable grids based on a multi-indicator analysis. We construct an innovative index system based on the shape-centered difference distance, by combining spatial suitability, numerical suitability, and spatial relationship suitability, and use spatial autocorrelation, coefficient of variation, and geographic detector model to get rid of the scale effect of landscape index from the spatial and numerical perspectives. In this paper, the process of population spatialization employs geographic country data combined with occupancy spatial attributes (i.e., number of building floors and floor area). The suitable scale threshold of the grid under each index is determined based on the analysis of the change of the characteristic points of each index, and then the common scale threshold is identified as the overall suitable grid scale. The geometric mean of the absolute relative error against the real population value is calculated to verify the index analysis results and the suitable scale of population grid. This paper takes the Guye District of Tangshan city in the Capital Economic Circle as the empirical analysis area. The results of the index system analysis show that the differences between clusters of population patches gradually become smaller and their distribution patterns become less expressive as the scale of the girds increases, and the overall expressiveness of the population grid gradually decreases as the scale increases. From perspectives of spatial suitability, distribution morphology suitability, numerical suitability, and spatial relationship suitability, 90 m and 100 m are identified as the suitable grid scales, under which the population spatialization could obtain better quality. The validation analysis demonstrates that the method of determining suitable grid scale for population spatialization in this study has a certain degree of validity and reliability.

Key words: population spatialization, appropriate grid scale, spatial analysis, indicator systems, shape-centered differences, population grids, spatial difference