Quantifying the Safe Operating Space for Land-System SDG Achievement via Machine Learning and Scenario Discovery
Summary: Future land use is highly uncertain based on economic developments, climate change, population growth, technological advancement, and their impacts. Computer-based simulation models have been used to generate a number of scenarios to show these uncertain futures. However, current models are complex, and exploring the whole scenario space considering uncertainties takes untenable amounts of time. My research tries to develop fit-for-purpose land-use models by integrating machine learning within an exploratory modelling framework to address the uncertainties through rapid scenario generation and understand the robustness of policy interventions for future land use and sustainability.
https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2022EF003083/
