Considering the UN sustainable development goals (SDGs) released in 2015, this article constructed an SDGoriented land use simulation (SDG-LUS) model incorporating SDG-oriented system dynamics (SDG-SD) and SDG-oriented cellular automata (SDG-CA), and utilized it to simulate land use changes in the Yangtze river delta region. The SDG-SD model was developed to predict the land use demands from 2021 to 2030 under the constraints of multiple SDG indicators, including economic indicators (SDG2.3.1 and SDG8.1.1), social indicators (SDG3.c.1, SDG4.1.2, SDG5.b.1, SDG9.C.1, SDG 9.1.2, SDG11.2.1, and SDG11.7.1) and environmental indicators (SDG6.3.1 and SDG11.6.2). Four sustainable development scenarios, including reference, economic development, environmental protection and social progress scenarios, were established by utilizing the index and indicator board of the SDG indicators in 2030. Then, the SDG-CA model was applied to spatialize and simulate the land use evolution from 2021 to 2030 under different sustainable development scenarios. The results validate the applicability of the SDG-LUS model, and confirm that scenario simulations of different sustainability levels are conducive to supporting the formulation of sustainable land use plans.
Extensive efforts have been dedicated to deciphering the interactions associated with Sustainable Development Goals (SDGs). However, these developments are hampered by a lack of efficient strategies to avoid beneficial synergies being offset by harmful trade-offs. To fill these gaps, we used causal diagnosis and network analysis methods to construct 1302 directed networks of SDGs for 31 provinces in China from 2000 to 2020. We observed a dramatic offsetting effect of SDG synergies and trade-offs in China from 2000 to 2020, with approximately 27% of trade-off indicator pairs turning into synergies and about 25% of the synergy indicator pairs turning into trade-offs. However, our findings suggested that prioritising the progress of high-frequency indicators in virtuous cycles could multiply the positive systemic effects of the SDGs. Moreover, controlling the transition from passive to active in the trade-off network of SDGs remains a challenge in advancing the SDGs holistically.
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