Spatial distribution characteristics and patterns of daily consumption places in Kunming main city based on POI data

Guiquan Sun; Yang Wang

doi:10.1117/12.2667666

10 February 2023 Spatial distribution characteristics and patterns of daily consumption places in Kunming main city based on POI data

Guiquan Sun, Yang Wang

Author Affiliations +

Proceedings Volume 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022); 1255207 (2023) https://doi.org/10.1117/12.2667666
Event: International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 2022, Kunming, China

Abstract

In the paper, it makes use of 20546 daily consumption places in the main urban area of Kunming in 2021 as the basic data. Moreover, such places are divided into four categories: shopping service consumption places, living service consumption places, sports and leisure service consumption places and living service consumption places. On the basis of GIS analysis software (ArcGIS), the methods of average nearest neighbor analysis, nuclear density analysis, spatial autocorrelation analysis and spatial pattern abstraction are used to study the spatial clustering characteristics, spatial differentiation and distribution patterns of daily consumption in the main urban area of Kunming. The results show that 1) daily consumption places in the main urban area of Kunming are highly clustered in the core area and generally unevenly distributed; 2) Daily consumption places in the main urban area of Kunming show a decreasing-rising-decreasing “slanting spoon” curve spatial pattern from the center to the periphery; 3) Daily consumption places and the four categories of consumption places have the same spatial distribution pattern generally and the spatial heterogeneity of the density of consumption places in the core area and the second ring area is the most significant.

Citation Download Citation

Guiquan Sun and Yang Wang "Spatial distribution characteristics and patterns of daily consumption places in Kunming main city based on POI data", Proc. SPIE 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 1255207 (10 February 2023); https://doi.org/10.1117/12.2667666

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