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 populatio...
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MDPI AG
2024-11-01
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| author | Minshu Yang Zhongchang Sun Xiaoying Ouyang Hongwei Li Youmei Han Dinoo Gunasekera |
| author_facet | Minshu Yang Zhongchang Sun Xiaoying Ouyang Hongwei Li Youmei Han Dinoo Gunasekera |
| author_sort | Minshu Yang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-4a3a47c18e244e87b734a98f7ebd819b |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-4a3a47c18e244e87b734a98f7ebd819b2024-12-13T16:30:54ZengMDPI AGRemote Sensing2072-42922024-11-011623445210.3390/rs16234452Spatial and Temporal Dynamics of Transportation Accessibility in China: Insights from Sustainable Development Goal Indicators from 2015 to 2022Minshu Yang0Zhongchang Sun1Xiaoying Ouyang2Hongwei Li3Youmei Han4Dinoo Gunasekera5School of Marine Technology and Geomatics, Jiangsu Ocean University, Lianyungang 222005, ChinaInternational Research Center of Big Data for Sustainable Development Goals (CBAS), Beijing 100094, ChinaInternational Research Center of Big Data for Sustainable Development Goals (CBAS), Beijing 100094, ChinaInternational Research Center of Big Data for Sustainable Development Goals (CBAS), Beijing 100094, ChinaSchool of Marine Technology and Geomatics, Jiangsu Ocean University, Lianyungang 222005, ChinaInternational Research Center of Big Data for Sustainable Development Goals (CBAS), Beijing 100094, ChinaSDG 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.https://www.mdpi.com/2072-4292/16/23/4452sustainable development goals (SDGs)transportation accessibilitySDG 9.1.1SDG 11.2.1spatial and temporal patterns |
| spellingShingle | Minshu Yang Zhongchang Sun Xiaoying Ouyang Hongwei Li Youmei Han Dinoo Gunasekera Spatial and Temporal Dynamics of Transportation Accessibility in China: Insights from Sustainable Development Goal Indicators from 2015 to 2022 Remote Sensing sustainable development goals (SDGs) transportation accessibility SDG 9.1.1 SDG 11.2.1 spatial and temporal patterns |
| title | Spatial and Temporal Dynamics of Transportation Accessibility in China: Insights from Sustainable Development Goal Indicators from 2015 to 2022 |
| title_full | Spatial and Temporal Dynamics of Transportation Accessibility in China: Insights from Sustainable Development Goal Indicators from 2015 to 2022 |
| title_fullStr | Spatial and Temporal Dynamics of Transportation Accessibility in China: Insights from Sustainable Development Goal Indicators from 2015 to 2022 |
| title_full_unstemmed | Spatial and Temporal Dynamics of Transportation Accessibility in China: Insights from Sustainable Development Goal Indicators from 2015 to 2022 |
| title_short | Spatial and Temporal Dynamics of Transportation Accessibility in China: Insights from Sustainable Development Goal Indicators from 2015 to 2022 |
| title_sort | spatial and temporal dynamics of transportation accessibility in china insights from sustainable development goal indicators from 2015 to 2022 |
| topic | sustainable development goals (SDGs) transportation accessibility SDG 9.1.1 SDG 11.2.1 spatial and temporal patterns |
| url | https://www.mdpi.com/2072-4292/16/23/4452 |
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