可持续发展
校长(计算机安全)
环境规划
城市规划
地理
计算机科学
政治学
土木工程
工程类
计算机安全
法学
作者
Lu Chen,Chenyang Shuai,Xi Chen,Jingran Sun,Bu Zhao
标识
DOI:10.1002/adsu.202400894
摘要
Abstract Urban transformation plays a decisive role in China's achievement of the United Nations 2030 Agenda for Sustainable Development. However, a comprehensive and authoritative sustainable development goal (SDG) indicator framework is currently lacking at the city level. To address this gap, we first developed an integrated framework comprising 357 indicators for 297 Chinese cities through a literature review. Nevertheless, the sheer number of reviewed indicators presents significant challenges in data collection. The study then used principal component analysis and multiple regression to identify a small set of SDG indicators (principal indicators) with the consideration of data collection difficulty. Finally, we tested their effectiveness up to 2030. The key findings of our study are as follows: 1) 187 principal indicators are identified to explain the 90% variance of all the 357 indicators with lowest data collection difficulty, providing comprehensive coverage of the SDGs and achieving efficient information aggregation; 2) these principal indicators demonstrated good variance effectiveness and data availability in the vast majority of cities (284 out of 297), highlighting priority areas for future data infrastructure development; 3) the continued applicability of these principal indicators up to 2030 is validated. This study offers insights to guide investments in data infrastructure supporting China's sustainable urban development.
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