Estimation of Ultrahigh Resolution PM<sub>2.5</sub> in Urban Areas by Using 30 m Landsat-8 and Sentinel-2 AOD Retrievals
Ultrahigh resolution fine particulate matter (PM<sub>2.5</sub>) 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 s...
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MDPI AG
2025-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/15/2609 |
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| author | Hao Lin Siwei Li Jiqiang Niu Jie Yang Qingxin Wang Wenqiao Li Shengpeng Liu |
| author_facet | Hao Lin Siwei Li Jiqiang Niu Jie Yang Qingxin Wang Wenqiao Li Shengpeng Liu |
| author_sort | Hao Lin |
| collection | DOAJ |
| description | Ultrahigh resolution fine particulate matter (PM<sub>2.5</sub>) 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<sub>2.5</sub> 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 PM<sub>2.5</sub>-AOD relationship model across China. The results showed an overall high coefficient of determination (R<sup>2</sup>) 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 R<sup>2</sup> values of 0.86 and 0.85. Applications in both cities demonstrated that ultrahigh resolution PM<sub>2.5</sub> 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 PM<sub>2.5</sub> 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. |
| format | Article |
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| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj-art-4b7f6369ac3a40caa0cf5f5741fccf5a2025-08-20T03:36:27ZengMDPI AGRemote Sensing2072-42922025-07-011715260910.3390/rs17152609Estimation of Ultrahigh Resolution PM<sub>2.5</sub> in Urban Areas by Using 30 m Landsat-8 and Sentinel-2 AOD RetrievalsHao Lin0Siwei Li1Jiqiang Niu2Jie Yang3Qingxin Wang4Wenqiao Li5Shengpeng Liu6College of Geographic Science, Xinyang Normal University, Xinyang 464000, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, ChinaCollege of Geographic Science, Xinyang Normal University, Xinyang 464000, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, ChinaCollege of Geographic and Environmental Science, Zhejiang Normal University, Jinhua 321004, ChinaCollege of Geographic Science, Xinyang Normal University, Xinyang 464000, ChinaCollege of Geographic Science, Xinyang Normal University, Xinyang 464000, ChinaUltrahigh resolution fine particulate matter (PM<sub>2.5</sub>) 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<sub>2.5</sub> 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 PM<sub>2.5</sub>-AOD relationship model across China. The results showed an overall high coefficient of determination (R<sup>2</sup>) 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 R<sup>2</sup> values of 0.86 and 0.85. Applications in both cities demonstrated that ultrahigh resolution PM<sub>2.5</sub> 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 PM<sub>2.5</sub> 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.https://www.mdpi.com/2072-4292/17/15/2609fine particulate matterremote sensingultrahigh spatial resolutionrandom forest |
| spellingShingle | Hao Lin Siwei Li Jiqiang Niu Jie Yang Qingxin Wang Wenqiao Li Shengpeng Liu Estimation of Ultrahigh Resolution PM<sub>2.5</sub> in Urban Areas by Using 30 m Landsat-8 and Sentinel-2 AOD Retrievals Remote Sensing fine particulate matter remote sensing ultrahigh spatial resolution random forest |
| title | Estimation of Ultrahigh Resolution PM<sub>2.5</sub> in Urban Areas by Using 30 m Landsat-8 and Sentinel-2 AOD Retrievals |
| title_full | Estimation of Ultrahigh Resolution PM<sub>2.5</sub> in Urban Areas by Using 30 m Landsat-8 and Sentinel-2 AOD Retrievals |
| title_fullStr | Estimation of Ultrahigh Resolution PM<sub>2.5</sub> in Urban Areas by Using 30 m Landsat-8 and Sentinel-2 AOD Retrievals |
| title_full_unstemmed | Estimation of Ultrahigh Resolution PM<sub>2.5</sub> in Urban Areas by Using 30 m Landsat-8 and Sentinel-2 AOD Retrievals |
| title_short | Estimation of Ultrahigh Resolution PM<sub>2.5</sub> in Urban Areas by Using 30 m Landsat-8 and Sentinel-2 AOD Retrievals |
| title_sort | estimation of ultrahigh resolution pm sub 2 5 sub in urban areas by using 30 m landsat 8 and sentinel 2 aod retrievals |
| topic | fine particulate matter remote sensing ultrahigh spatial resolution random forest |
| url | https://www.mdpi.com/2072-4292/17/15/2609 |
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