標題:Estimation of Ultrahigh Resolution PM2.5 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
來源出版物:Remote Sensing
DOI:10.3390/rs17152609
出版年:2025
文獻類型:Article
語種:英文
摘要:Ultrahigh resolution fine particulate matter (PM2.5) 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 PM2.5 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 PM2.5-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 PM2.5 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 PM2.5 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.
關(guān)鍵詞:fine particulate matter; remote sensing; ultrahigh spatial resolution; random forest
影響因子:4.1
論文鏈接:https://doi.org/10.3390/rs17152609
(地理科學(xué)學(xué)院 劉媛心/撰稿 崔向超/初審 閆軍輝/復(fù)審 韓勇/終審)