Identifying the uneven distribution of health and education services in China using open geospatial data

Abstract

Growing attention has been directed to the use of satellite imagery and open geospatial data to understand large-scale sustainable development outcomes. Health and education are critical domains of the Unites Nations’ Sustainable Development Goals (SDGs), yet existing research on the accessibility of corresponding services focused mainly on detailed but small-scale studies. This means that such studies lack accessibility metrics for large-scale quantitative evaluations. To address this deficiency, we evaluated the accessibility of health and education services in mainland China in 2021 using point-of-interest data, OpenStreetMap road data, land cover data, and WorldPop spatial demographic data. The accessibility metrics used were the least time costs of reaching hospital and school services and population coverage with a time cost of less than 1 h. On the basis of the road network and land cover information, the overall average time costs of reaching hospital and school were 20 and 22 min, respectively. In terms of population coverage, 94.7% and 92.5% of the population in China has a time cost of less than 1 h in obtaining hospital and school services, respectively. Counties with low accessibility to hospitals and schools were highly coupled with poor areas and ecological function regions, with the time cost incurred in these areas being more than twice that experienced in non-poor and non-ecological areas. Furthermore, the cumulative time cost incurred by the bottom 20% of counties (by GDP) from access to hospital and school services reached approximately 80% of the national total. Low-GDP counties were compelled to suffer disproportionately increased time costs to acquire health and education services compared with high-GDP counties. The accessibility metrics proposed in this study are highly related to SDGs 3 and 4, and they can serve as auxiliary data that can be used to enhance the evaluation of SDG outcomes. The analysis of the uneven distribution of health and education services in China can help identify areas with backward public services and may contribute to targeted and efficient policy interventions.

Keywords

Accessibility / Poverty / Geospatial data / Point of interest / OpenStreetMap

Declaration of Competing Interests

The authors declare that there are no known competing financial interests or personal relationships that influenced the work reported in this paper.

Acknowledgements

This work was supported by the National Natural Science Foundation for Distinguished Young Scholars of China (Grant No. 41725006).

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