Xiaoling Wang: Using forest inventory and LiDAR observations to uncover plant traits cooling and humidifying effects
Shortlisted for the 2025 Southwood Prize About the research Overview Our paper investigates how to maximize the cooling effect of urban forests. We wanted to know whether a tree’s leaf traits (like nutrient content) are more important than its physical structure (like canopy size) for reducing air temperature and increasing humidity in cities. By combining traditional forest surveys with advanced LiDAR technology in Shanghai, we sought … Continue reading Xiaoling Wang: Using forest inventory and LiDAR observations to uncover plant traits cooling and humidifying effects