China has emerged as one of the global leaders in greening, achieved through human land use management practices, particularly afforestation projects. However, accurately calculating the energy balance processes of vegetated areas remains challenging because of the complexity of physical mechanisms, parameterization schemes, and driving dataset used in current research. In this study, we address these challenges by employing moving window methods in space inspired by space-for-time. This approach allows us to eliminate the influence of climate signals on vegetation development over long periods and determine the sensitivity of seasonal contributions of Land Surface Temperature (LST) to Leaf Area Index (LAI) in China from 2001 to 2018. Our findings reveal that the sensitivity of LST to LAI in the climatology period is approximately -0.085 K & BULL;m2 & BULL;m-2, indicating a cooling effect. Moreover, the climatological trend remains negative, suggesting that Chinese vegetation greening is playing an increasingly important role in cooling the land surface. Considering the energy balance equation, we further investigate the underlying mechanisms. It is observed that the radiative feedback consistently contributes positively, while the non-radiative feedback always exerts a negative influence on the sensitivity. These results provide valuable insights into the complex interactions between vegetation greening and land surface temperature in China, providing informed land management and climate adaptation strategies. Understanding these trends and mechanisms is essential for sustainable and effective environmental planning and decision making.
Qian, ZH; Sun, YX; Chen, Z; Ji, F; Feng, GL; Ma, QR
Analysis of Land Surface Temperature Sensitivity to Vegetation in China
Remote Sensing