标题：Estimation of Ultrahigh Resolution PM_2.5 in Urban Areas by Using 30 m Landsat-8 and Sentinel-2 AOD Retrievals

作者：Hao Lin, Siwei Li, Jiqiang Niu, Jie Yang, Qingxin Wang, Wenqiao Li and Shengpeng Liu

来源出版物：Remote Sensing

DOI：10.3390/rs17152609

出版年：2025

文献类型：Article

语种：英文

摘要：Ultrahigh resolution fine particulate matter (PM_2.5) mass concentration remote sensing products are crucial for atmospheric environmental monitoring, pollution source verification, health exposure risk assessment, and other fine-scale applications in urban environments. This study developed an ultrahigh resolution retrieval algorithm to estimate 30 m resolution PM_2.5 mass concentrations over urban areas from Landsat-8 and Sentinel-2MSL measurements, The algorithm utilized aerosol optical depth (AOD) products retrieved from the Landsat-8 OLI and Sentinel-2MSl measurements from 2017 to 2020, combined with multi-source auxiliary data to establish a PM_2.5-AOD relationship model across China. The results showed an overall high coefficient of determination (R²) of 0.82 and 0.76 for the model training accuracy based on samples and stations, respectively, The model prediction accuracy in Beijing and Wuhan reached R² values of 0.86 and 0.85. Application sin both cities demonstrated that ultrahigh resolution PM_2.5 has significant advantages in re-solving fine-scale spatial patterns of urban air pollution and pinpointing pollution hotspots.Furthermore, an analysis of point source pollution at a typical heavy pollution emission enterprise confirmed that ultrahigh spatial resolution PM_2.5 can accurately identify the diffusion trend of point source pollution, providing fundamental data support for refined monitoring of urban air pollution and air pollution prevention and control.

关键词：fine particulate matter; remote sensing; ultrahigh spatial resolution; random forest

影响因子：4.1

论文链接：https://doi.org/10.3390/rs17152609

（地理科学学院 刘媛心/撰稿 崔向超/初审 闫军辉/复审 韩勇/终审）