Long‐Term and Fine‐Scale Surface Urban Heat Island Dynamics Revealed by Landsat Data Since the 1980s: A Comparison of Four Megacities in China

Abstract Long‐term and fine‐scale monitoring of surface urban heat island (SUHI) is critical for the design of heat mitigation strategies. Landsat series offer long‐term (since the 1980s) and fine‐scale land surface temperature (LST) observations for such SUHI analysis. However, Landsat data are characterized by a long revisit period (16 days) and are seriously impacted by cloud contamination and stripe gaps, making the Landsat‐derived long‐term SUHI trends across cities incomparable. To address this issue, here we applied the Prophet model to reconstruct temporally consistent long‐term (∼1985–2019) clear‐sky Landsat LSTs over four megacities in China (Beijing, Chongqing, Shanghai, and Shenzhen). The results show that the mean absolute error of the SUHI intensity (SUHII) estimated using the reconstructed LSTs ranges from 0.2 to 0.6°C. The reliability of the reconstructed LSTs is further evidenced by the general consistency between the reconstructed Landsat and original Moderate Resolution Imaging Spectroradiometer LSTs. Our analysis further demonstrates that the overall SUHII has been increasing slowly over Beijing but has been increasing rapidly in the other three megacities since the 1980s. Local SUHII trends also varied between urban regions. Urban core is characterized by an initial increase and then a slight decrease in the local SUHII, while a continuously increasing trend is observed for the urban fringe. For the new urban development, the interannual SUHII trend lies somewhere between these trends. Overall, our study provides a practical approach to reconstruct long‐term clear‐sky Landsat LSTs, and delivers a better understanding of long‐term and fine‐scale SUHI variations across cities.