Spatial and Temporal Dynamics of Transportation Accessibility in China: Insights from Sustainable Development Goal Indicators from 2015 to 2022

SDG 9.1.1 and SDG 11.2.1 are significant evaluation indicators of the United Nations Sustainable Development Goals related to transportation accessibility and are used to measure the proportion of the population facilitating the use of road services in rural areas and the proportion of the population facilitating the use of public transportation services in urban areas, respectively. However, there are currently challenges related to incomplete data and the inadequate interpretation of the indicators. In this study, we therefore evaluate the spatiotemporal patterns of the indicators and the number of disadvantaged groups in 337 Chinese cities from 2015 to 2022 based on multi-source data, and explore the spatial aggregation of the indicators and the driving factors. The results demonstrate that the indicator values of SDG 9.1.1 and SDG 11.2.1 reached 99.36% and 90.00%, respectively, in 2022, and the number of vulnerable groups decreased to approximately 1.89 million and 2.82 million. The indicator values of SDG 9.1.1 are high in the eastern part of China and low in the western part of the country, whereas the indicator values of SDG 11.2.1 exhibit spatial agglomeration in regions such as the Pearl River Delta. The average rural elevation and the density of urban public transportation stops are the most influential factors for these two indicators, respectively. The insights and data from this study provide support for improving transportation infrastructure and inequality in China, contributing to the achievement of the 2030 Sustainable Development Goals.

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Publication Details

Journal
Remote Sensing
Published
2024-11-27
DOI
https://doi.org/10.3390/rs16234452
Primary Topic
Urban Transport and Accessibility
Type
article
Field-Weighted Citation Impact
0.00

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article

Spatial and Temporal Dynamics of Transportation Accessibility in China: Insights from Sustainable Development Goal Indicators from 2015 to 2022

Xiaoying Ouyang, Hongwei Li, Dinoo Gunasekera, Minshu Yang et al.
Remote Sensing
Urban Transport and Accessibility
article

Spatial and Temporal Dynamics of Transportation Accessibility in China: Insights from Sustainable Development Goal Indicators from 2015 to 2022

Xiaoying Ouyang, Hongwei Li, Dinoo Gunasekera, Minshu Yang, Zhongchang Sun, Youmei Han
article en

Abstract

SDG 9.1.1 and SDG 11.2.1 are significant evaluation indicators of the United Nations Sustainable Development Goals related to transportation accessibility and are used to measure the proportion of the population facilitating the use of road services in rural areas and the proportion of the population facilitating the use of public transportation services in urban areas, respectively. However, there are currently challenges related to incomplete data and the inadequate interpretation of the indicators. In this study, we therefore evaluate the spatiotemporal patterns of the indicators and the number of disadvantaged groups in 337 Chinese cities from 2015 to 2022 based on multi-source data, and explore the spatial aggregation of the indicators and the driving factors. The results demonstrate that the indicator values of SDG 9.1.1 and SDG 11.2.1 reached 99.36% and 90.00%, respectively, in 2022, and the number of vulnerable groups decreased to approximately 1.89 million and 2.82 million. The indicator values of SDG 9.1.1 are high in the eastern part of China and low in the western part of the country, whereas the indicator values of SDG 11.2.1 exhibit spatial agglomeration in regions such as the Pearl River Delta. The average rural elevation and the density of urban public transportation stops are the most influential factors for these two indicators, respectively. The insights and data from this study provide support for improving transportation infrastructure and inequality in China, contributing to the achievement of the 2030 Sustainable Development Goals.

Remote SensingVol. 16(23)
Chinese Academy of Sciences (CN), Beijing Institute of Big Data Research (CN), Aerospace Information Research Institute (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 81%
Urban Transport and Accessibility
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