Yongling Zhao

Interpretable machine learning for urban heat mitigation: Attribution and weighting of multi-scale drivers

Abstract Strategies to mitigate urban heat are often analysed using complex models. Here, we propose a machine learning method for highly interpretable emulators of such models to efficiently inform actionable levers to mitigate urban heat. We first pre-classify parameters accord...