Chengyuan Wang , Ling Wang , Junjie Zhai , Tiantian Feng , Yuzhou Lei , Shanfu Li , Yuan Liu , Yuwen Liu , Zhibo Hu , Kun Zhu , Yupeng Chang , Shuai Cui , Xuegang Mao
{"title":"按地区可持续发展指数评估中国国家以下各级可持续发展的进展情况","authors":"Chengyuan Wang , Ling Wang , Junjie Zhai , Tiantian Feng , Yuzhou Lei , Shanfu Li , Yuan Liu , Yuwen Liu , Zhibo Hu , Kun Zhu , Yupeng Chang , Shuai Cui , Xuegang Mao","doi":"10.1016/j.horiz.2024.100099","DOIUrl":null,"url":null,"abstract":"<div><p>Quantifying progress towards the United Nations (UN) Sustainable Development Goals (SDGs) requires countries to make profound changes and major efforts in monitoring and measurement. However, there is still a need for a simple and easy-to-use means to quantify subnational SDGs performance and to determine the applicability of remote sensing big data tools, such as night-time lighting, for tracking the sustainable development process. This study used hierarchical clustering and principal component analysis (PCA), to construct a regional sustainable development index (RSDI), which aims to quantify China's progress towards the SDGs at the subnational level in 2013–2020. The average R<sup>2</sup> of the linear regression between China's subnational RSDIs from 2013 to 2020 is 0.9. The average R<sup>2</sup> of the RSDI and the Average Night-light Index (ANLI) is 0.57, and the average R<sup>2</sup> of the RSDI and Gross Domestic Product per capita (CGDP) is 0.85. The RSDI has remained stable over time as an observation framework and is suitable for tracking China's sustainable development in the long term, with a strong link to the CGDP and ANLI, which reflect economic development and big data method. The RSDI in China's eastern region reduces by 0.32 % annually, while the RSDI in central and western regions grows by 1.26 % annually. The RSDI in China's northern region reduces by 0.14 % annually, while the RSDI in China's southern regions grows by 2.62 % annually. We also attempted to incorporate ANLI and CGDP into the RSDI framework to capture potential application scenarios for tracking sustainability by using nighttime lighting. The RSDI can track how the SDGs are implemented and can be used in other countries subnational areas to analyze the spatial-temporal dynamics of SDGs achievement.</p></div>","PeriodicalId":101199,"journal":{"name":"Sustainable Horizons","volume":"11 ","pages":"Article 100099"},"PeriodicalIF":0.0000,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772737824000117/pdfft?md5=0e548f7b3cadc5b6beb84faa54d27de8&pid=1-s2.0-S2772737824000117-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Assessing progress toward China's subnational sustainable development by Region Sustainable Development Index\",\"authors\":\"Chengyuan Wang , Ling Wang , Junjie Zhai , Tiantian Feng , Yuzhou Lei , Shanfu Li , Yuan Liu , Yuwen Liu , Zhibo Hu , Kun Zhu , Yupeng Chang , Shuai Cui , Xuegang Mao\",\"doi\":\"10.1016/j.horiz.2024.100099\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Quantifying progress towards the United Nations (UN) Sustainable Development Goals (SDGs) requires countries to make profound changes and major efforts in monitoring and measurement. However, there is still a need for a simple and easy-to-use means to quantify subnational SDGs performance and to determine the applicability of remote sensing big data tools, such as night-time lighting, for tracking the sustainable development process. This study used hierarchical clustering and principal component analysis (PCA), to construct a regional sustainable development index (RSDI), which aims to quantify China's progress towards the SDGs at the subnational level in 2013–2020. The average R<sup>2</sup> of the linear regression between China's subnational RSDIs from 2013 to 2020 is 0.9. The average R<sup>2</sup> of the RSDI and the Average Night-light Index (ANLI) is 0.57, and the average R<sup>2</sup> of the RSDI and Gross Domestic Product per capita (CGDP) is 0.85. The RSDI has remained stable over time as an observation framework and is suitable for tracking China's sustainable development in the long term, with a strong link to the CGDP and ANLI, which reflect economic development and big data method. The RSDI in China's eastern region reduces by 0.32 % annually, while the RSDI in central and western regions grows by 1.26 % annually. The RSDI in China's northern region reduces by 0.14 % annually, while the RSDI in China's southern regions grows by 2.62 % annually. We also attempted to incorporate ANLI and CGDP into the RSDI framework to capture potential application scenarios for tracking sustainability by using nighttime lighting. The RSDI can track how the SDGs are implemented and can be used in other countries subnational areas to analyze the spatial-temporal dynamics of SDGs achievement.</p></div>\",\"PeriodicalId\":101199,\"journal\":{\"name\":\"Sustainable Horizons\",\"volume\":\"11 \",\"pages\":\"Article 100099\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2772737824000117/pdfft?md5=0e548f7b3cadc5b6beb84faa54d27de8&pid=1-s2.0-S2772737824000117-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sustainable Horizons\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772737824000117\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Horizons","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772737824000117","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Assessing progress toward China's subnational sustainable development by Region Sustainable Development Index
Quantifying progress towards the United Nations (UN) Sustainable Development Goals (SDGs) requires countries to make profound changes and major efforts in monitoring and measurement. However, there is still a need for a simple and easy-to-use means to quantify subnational SDGs performance and to determine the applicability of remote sensing big data tools, such as night-time lighting, for tracking the sustainable development process. This study used hierarchical clustering and principal component analysis (PCA), to construct a regional sustainable development index (RSDI), which aims to quantify China's progress towards the SDGs at the subnational level in 2013–2020. The average R2 of the linear regression between China's subnational RSDIs from 2013 to 2020 is 0.9. The average R2 of the RSDI and the Average Night-light Index (ANLI) is 0.57, and the average R2 of the RSDI and Gross Domestic Product per capita (CGDP) is 0.85. The RSDI has remained stable over time as an observation framework and is suitable for tracking China's sustainable development in the long term, with a strong link to the CGDP and ANLI, which reflect economic development and big data method. The RSDI in China's eastern region reduces by 0.32 % annually, while the RSDI in central and western regions grows by 1.26 % annually. The RSDI in China's northern region reduces by 0.14 % annually, while the RSDI in China's southern regions grows by 2.62 % annually. We also attempted to incorporate ANLI and CGDP into the RSDI framework to capture potential application scenarios for tracking sustainability by using nighttime lighting. The RSDI can track how the SDGs are implemented and can be used in other countries subnational areas to analyze the spatial-temporal dynamics of SDGs achievement.