Guangdong
China
Peking University - Shenzhen Graduate School
Extreme events, Carbon emission, Power system, Explainable machine learning, SHAP, Extreme cold days, Extreme hot days
Critical canopy temperature, evapotranspiration, Evaporative Cooling, Leaf thermoregulation, Remote Sensing, Surface energy balance model
Climate Change, Ficus concinna, high temperature, multiple timescales, nocturnal sap flow, regulatory parameters
Urban evapotranspiration, spatiotemporally seamless, geospatial foundation embeddings, transformer, Machine Learning, Shenzhen
Ground heat flux, surface energy balance, Multi-scale memory, Long short-term memory, Explainable Machine Learning, eddy covariance
