Capturing spatio-temporal variations in SDG interactions and prioritizations
Yizhong Huan，Xiaoyun Li，Pengfei Li，Xin Li，Yang Lan，Linjiang Ji，Yifei Lei，Yiming Su，Mingyuan Wang，Siyuan Tao，Xinming Xia，Riqi Zhang，Lingqing Wang，Tao Liang，Guangjin Zhou
Applied Geography 186（2026）103830
Abstract：Understanding the varying degrees of synergies and trade-offs among Sustainable Development Goals (SDGs), as well as the influential goals within these interactions, is crucial for identifying transformative governance actions. However, the spatiotemporal dynamics of SDG interactions and priorities remain unclear. Here, we analyzed global and regional variations in SDG interactions, synergistic performance, and key contributing goals from 2000 to 2022 using network methodology, index analysis, and machine learning. Europe exhibited high SDG synergies, low synergy-network modularity, and strong synergistic performance, while Western Asia showed the opposite pattern. Despite overall improvement in SDG synergy proportions and synergistic performance, global progress was constrained by declining synergies related to SDG 5 (gender equality) and increasing fragmentation of the SDG synergy network. We also observed substantial spatio-temporal changes in the impact of each SDG within the interaction network and in its contribution to overall synergistic performance. Furthermore, we applied an ensemble random forest model to assess SDG mentions and co-occurrences in 1944 SDG interaction studies. SDGs 13 (climate action) and 9 (industry, innovation and infrastructure) emerged as the most and least frequently discussed goals, respectively. Interactions among seven SDGs (2, 6, 7, 8, 12, 13, 15) formed a typical SDG nexus, reflecting a critical human-nature relationship chain. Overall, to advance global SDG attainment, we emphasize the importance of accelerating progress on SDG 3 (good health and well-being). Our study enhances understanding of global development patterns and priorities and supports efforts to rescue the 2030 Agenda.
Keywords: Sustainable development；Spatio-temporal variations；Network analysis；Machine learning；SDG interactions；Global governance
Full text download：
Capturing spatio-temporal variations in SDG interactions and prioritizations Yizhong Huan，Xiaoyun Li，Pengfei Li.pdf
编辑：宋雨萱
Capturing spatio-temporal variations in SDG interactions and prioritizations
Yizhong Huan，Xiaoyun Li，Pengfei Li，Xin Li，Yang Lan，Linjiang Ji，Yifei Lei，Yiming Su，Mingyuan Wang，Siyuan Tao，Xinming Xia，Riqi Zhang，Lingqing Wang，Tao Liang，Guangjin Zhou
Applied Geography 186（2026）103830
Abstract：Understanding the varying degrees of synergies and trade-offs among Sustainable Development Goals (SDGs), as well as the influential goals within these interactions, is crucial for identifying transformative governance actions. However, the spatiotemporal dynamics of SDG interactions and priorities remain unclear. Here, we analyzed global and regional variations in SDG interactions, synergistic performance, and key contributing goals from 2000 to 2022 using network methodology, index analysis, and machine learning. Europe exhibited high SDG synergies, low synergy-network modularity, and strong synergistic performance, while Western Asia showed the opposite pattern. Despite overall improvement in SDG synergy proportions and synergistic performance, global progress was constrained by declining synergies related to SDG 5 (gender equality) and increasing fragmentation of the SDG synergy network. We also observed substantial spatio-temporal changes in the impact of each SDG within the interaction network and in its contribution to overall synergistic performance. Furthermore, we applied an ensemble random forest model to assess SDG mentions and co-occurrences in 1944 SDG interaction studies. SDGs 13 (climate action) and 9 (industry, innovation and infrastructure) emerged as the most and least frequently discussed goals, respectively. Interactions among seven SDGs (2, 6, 7, 8, 12, 13, 15) formed a typical SDG nexus, reflecting a critical human-nature relationship chain. Overall, to advance global SDG attainment, we emphasize the importance of accelerating progress on SDG 3 (good health and well-being). Our study enhances understanding of global development patterns and priorities and supports efforts to rescue the 2030 Agenda.
Keywords: Sustainable development；Spatio-temporal variations；Network analysis；Machine learning；SDG interactions；Global governance
Full text download：Capturing spatio-temporal variations in SDG interactions and prioritizations Yizhong Huan，Xiaoyun Li，Pengfei Li.pdf
编辑：宋雨萱
