Exploring the relationship between 2D/3D landscape pattern and land surface temperature based on explainable eXtreme Gradient Boosting tree: A case study of Shanghai, China

With more record-breaking skyscrapers built in big cities around the world, horizontal urban sprawl no longer dominates the research of urbanization rather than the vertical growth of cities. In such a context, the urban heat island problem cannot be understood by solely studying the impact of the horizontal urban expansion because the 3D structure of the urban landscape could severely alter the natural heat flux transport over the land surface and thus lead to bigger heat island problems. In addition to our current knowledge of impact of 2D landscape changes on urban thermal dynamics, it is crucial to understand the effects of 3D landscape pattern on the thermal environment, in order to maintain a sustainable and eco-friendly urban development. This study investigated the 2D/3D landscape pattern metrics and their association with the land surface temperature (LST) changes in a case study area of Shanghai City using the extreme gradient boosting (XGBoost) regression model and Sharpley Additive exPlanations (SHAP) interpretation method based on datasets of land cover and digital surface model (DSM). Major findings include, 1) 3D landscape pattern metrics could better describe the undulation and heterogeneity of urban surface and were essential when explaining the variation of LST compared with conventional 2D landscape pattern metrics, 2) Low-rise and high-rise buildings tend to alleviate LST while buildings with medium height heating the surroundings; 3) the cooling effect of vegetation was significantly strong; 4) different urban functional types impact the surface temperature in the way determined by their 3D urban landscape pattern. These findings may help urban planners and landscape designers achieve the goal of minimizing urban heat island using computer models of 3D urban structure.