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Article

Estimation of Ultrahigh Resolution PM2.5 in Urban Areas by Using 30 m Landsat-8 and Sentinel-2 AOD Retrievals

1
College of Geographic Science, Xinyang Normal University, Xinyang 464000, China
2
Henan Key Laboratory for Synergistic Prevention of Water and Soil Environmental Pollution, Xinyang Normal University, Xinyang 464000, China
3
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
4
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
5
Perception and Effectiveness Assessment for Carbon-Neutrality Efforts, Engineering Research Center of Ministry of Education, Institute for Carbon Neutrality, Wuhan University, Wuhan 430072, China
6
College of Geographic and Environmental Science, Zhejiang Normal University, Jinhua 321004, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(15), 2609; https://doi.org/10.3390/rs17152609 (registering DOI)
Submission received: 16 June 2025 / Revised: 16 July 2025 / Accepted: 24 July 2025 / Published: 27 July 2025

Abstract

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-2A/B satellite measurements. The algorithm utilized aerosol optical depth (AOD) products retrieved from the Landsat-8 OLI and Sentinel-2 MSI 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. Applications in both cities demonstrated that ultrahigh resolution PM2.5 has significant advantages in resolving 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.
Keywords: fine particulate matter; remote sensing; ultrahigh spatial resolution; random forest fine particulate matter; remote sensing; ultrahigh spatial resolution; random forest

Share and Cite

MDPI and ACS Style

Lin, H.; Li, S.; Niu, J.; Yang, J.; Wang, Q.; Li, W.; Liu, S. Estimation of Ultrahigh Resolution PM2.5 in Urban Areas by Using 30 m Landsat-8 and Sentinel-2 AOD Retrievals. Remote Sens. 2025, 17, 2609. https://doi.org/10.3390/rs17152609

AMA Style

Lin H, Li S, Niu J, Yang J, Wang Q, Li W, Liu S. Estimation of Ultrahigh Resolution PM2.5 in Urban Areas by Using 30 m Landsat-8 and Sentinel-2 AOD Retrievals. Remote Sensing. 2025; 17(15):2609. https://doi.org/10.3390/rs17152609

Chicago/Turabian Style

Lin, Hao, Siwei Li, Jiqiang Niu, Jie Yang, Qingxin Wang, Wenqiao Li, and Shengpeng Liu. 2025. "Estimation of Ultrahigh Resolution PM2.5 in Urban Areas by Using 30 m Landsat-8 and Sentinel-2 AOD Retrievals" Remote Sensing 17, no. 15: 2609. https://doi.org/10.3390/rs17152609

APA Style

Lin, H., Li, S., Niu, J., Yang, J., Wang, Q., Li, W., & Liu, S. (2025). Estimation of Ultrahigh Resolution PM2.5 in Urban Areas by Using 30 m Landsat-8 and Sentinel-2 AOD Retrievals. Remote Sensing, 17(15), 2609. https://doi.org/10.3390/rs17152609

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