Study on the coupling of public service facilities and population based on multi-source geographical data: Hongshan District, Wuhan City as an example

Yuxiang Cao; Gewei Zheng; Xin Zhou

doi:10.1117/12.2667362

10 February 2023 Study on the coupling of public service facilities and population based on multi-source geographical data: Hongshan District, Wuhan City as an example

Yuxiang Cao, Gewei Zheng, Xin Zhou

Author Affiliations +

Proceedings Volume 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022); 125521D (2023) https://doi.org/10.1117/12.2667362
Event: International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 2022, Kunming, China

Abstract

Taking Hongshan District, Wuhan City as the research area, using remote sensing data, POI data and Baidu heat map data, we used kernel density and two-factor mapping method to analyse the coupling degree of public service facilities and population in space and time. The remote sensing map and the population heat density from the distribution, there are differences, using multiple sources of data for validation can compensate, the shortcomings caused by a single data source. It is also possible to analyse the coupling between public service facilities and population distribution from two latitudes in time and space. Taking the Hongshan District as an example, we can conclude that: 1. Spatially, public service facilities in Hongshan District show a pattern of one main centre and two to three secondary centres, with a relatively uneven spatial distribution; 2 .Spatially, the population is coupled with public service facilities in a primary and secondary manner, with better coupling concentrated in the areas south of Hongshan Square and Liyuan Street area; 3. From the analysis of the population heat map, the demand for transportation facilities is greater on weekdays than on weekends, and the demand for shopping facilities is greater on weekends than on weekdays.

Citation Download Citation

Yuxiang Cao, Gewei Zheng, and Xin Zhou "Study on the coupling of public service facilities and population based on multi-source geographical data: Hongshan District, Wuhan City as an example", Proc. SPIE 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 125521D (10 February 2023); https://doi.org/10.1117/12.2667362

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