Exploiting the Matched Filter to Improve the Detection of Methane Plumes with Sentinel-2 Data
Existing research indicates that detecting near-surface methane point sources using Sentinel-2 satellite imagery can offer crucial data support for mitigating climate change. However, current retrieval methods necessitate the identification of reference images unaffected by methane, which presents c...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-03-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/16/6/1023 |
| _version_ | 1797239470304526336 |
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| author | Hongzhou Wang Xiangtao Fan Hongdeng Jian Fuli Yan |
| author_facet | Hongzhou Wang Xiangtao Fan Hongdeng Jian Fuli Yan |
| author_sort | Hongzhou Wang |
| collection | DOAJ |
| description | Existing research indicates that detecting near-surface methane point sources using Sentinel-2 satellite imagery can offer crucial data support for mitigating climate change. However, current retrieval methods necessitate the identification of reference images unaffected by methane, which presents certain limitations. This study introduces the use of a matched filter, developing a novel methane detection algorithm for Sentinel-2 imagery. Compared to existing algorithms, this algorithm does not require selecting methane-free images from historical imagery in methane-sensitive bands, but estimates the background spectral information across the entire scene to extract methane gas signals. We tested the algorithm using simulated Sentinel-2 datasets. The results indicated that the newly proposed algorithm effectively reduced artifacts and noise. It was then validated in a known methane emission point source event and a controlled release experiment for its ability to quantify point source emission rates. The average estimated difference between the new algorithm and other algorithms was about 34%. Compared to the actual measured values in the controlled release experiment, the average estimated values ranged from −48% to 42% of the measurements. These estimates had a detection limit ranging from approximately 1.4 to 1.7 t/h and an average error percentage of 19%, with no instances of false positives reported. Finally, in a real case scenario, we demonstrated the algorithm’s ability to precisely locate the source position and identify, as well as quantify, methane point source emissions. |
| first_indexed | 2024-04-24T17:52:03Z |
| format | Article |
| id | doaj.art-bbf75c7d32af401d8e1337dc2fa3d17e |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-04-24T17:52:03Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-bbf75c7d32af401d8e1337dc2fa3d17e2024-03-27T14:02:39ZengMDPI AGRemote Sensing2072-42922024-03-01166102310.3390/rs16061023Exploiting the Matched Filter to Improve the Detection of Methane Plumes with Sentinel-2 DataHongzhou Wang0Xiangtao Fan1Hongdeng Jian2Fuli Yan3Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaKey Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaKey Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaKey Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaExisting research indicates that detecting near-surface methane point sources using Sentinel-2 satellite imagery can offer crucial data support for mitigating climate change. However, current retrieval methods necessitate the identification of reference images unaffected by methane, which presents certain limitations. This study introduces the use of a matched filter, developing a novel methane detection algorithm for Sentinel-2 imagery. Compared to existing algorithms, this algorithm does not require selecting methane-free images from historical imagery in methane-sensitive bands, but estimates the background spectral information across the entire scene to extract methane gas signals. We tested the algorithm using simulated Sentinel-2 datasets. The results indicated that the newly proposed algorithm effectively reduced artifacts and noise. It was then validated in a known methane emission point source event and a controlled release experiment for its ability to quantify point source emission rates. The average estimated difference between the new algorithm and other algorithms was about 34%. Compared to the actual measured values in the controlled release experiment, the average estimated values ranged from −48% to 42% of the measurements. These estimates had a detection limit ranging from approximately 1.4 to 1.7 t/h and an average error percentage of 19%, with no instances of false positives reported. Finally, in a real case scenario, we demonstrated the algorithm’s ability to precisely locate the source position and identify, as well as quantify, methane point source emissions.https://www.mdpi.com/2072-4292/16/6/1023Sentinel-2methanematched filtergas plumes |
| spellingShingle | Hongzhou Wang Xiangtao Fan Hongdeng Jian Fuli Yan Exploiting the Matched Filter to Improve the Detection of Methane Plumes with Sentinel-2 Data Remote Sensing Sentinel-2 methane matched filter gas plumes |
| title | Exploiting the Matched Filter to Improve the Detection of Methane Plumes with Sentinel-2 Data |
| title_full | Exploiting the Matched Filter to Improve the Detection of Methane Plumes with Sentinel-2 Data |
| title_fullStr | Exploiting the Matched Filter to Improve the Detection of Methane Plumes with Sentinel-2 Data |
| title_full_unstemmed | Exploiting the Matched Filter to Improve the Detection of Methane Plumes with Sentinel-2 Data |
| title_short | Exploiting the Matched Filter to Improve the Detection of Methane Plumes with Sentinel-2 Data |
| title_sort | exploiting the matched filter to improve the detection of methane plumes with sentinel 2 data |
| topic | Sentinel-2 methane matched filter gas plumes |
| url | https://www.mdpi.com/2072-4292/16/6/1023 |
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