Monitoring 2019 Forest Fires in Southeastern Australia with GNSS Technique
From late 2019 to early 2020, forest fires in southeastern Australia caused huge economic losses and huge environmental pollution. Monitoring forest fires has become increasingly important. A new method of fire detection using the difference between global navigation satellite system (GNSS)-derived...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/3/386 |
| _version_ | 1797408212089044992 |
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| author | Jinyun Guo Rui Hou Maosheng Zhou Xin Jin Chengming Li Xin Liu Hao Gao |
| author_facet | Jinyun Guo Rui Hou Maosheng Zhou Xin Jin Chengming Li Xin Liu Hao Gao |
| author_sort | Jinyun Guo |
| collection | DOAJ |
| description | From late 2019 to early 2020, forest fires in southeastern Australia caused huge economic losses and huge environmental pollution. Monitoring forest fires has become increasingly important. A new method of fire detection using the difference between global navigation satellite system (GNSS)-derived precipitable water vapor and radiosonde-derived precipitable water vapor (ΔPWV) is proposed. To study the feasibility of the new method, the relationship is studied between particulate matter 10 (PM10) (2.5 to 10 microns particulate matter) and ΔPWV based on Global Positioning System (GPS) data, radiosonde data, and PM10 data from 1 June 2019 to 1 June 2020 in southeastern Australia. The results show that before the forest fire, ΔPWV and PM10 were smaller and less fluctuating. When the forest fire happened, ΔPWV and PM10 were increasing. Then after the forest fire, PM10 became small with relatively smooth fluctuations, but ΔPWV was larger and more fluctuating. Correlation between the 15-day moving standard deviation (STD) time series of ΔPWV and PM10 after the fire was significantly higher than that before the fire. This study shows that ΔPWV is effective in monitoring forest fires based on GNSS technique before and during forest fires in climates with more uniform precipitation, and using ΔPWV to detect forest fires based on GNSS needs to be further investigated in climates with more precipitation and severe climate change. |
| first_indexed | 2024-03-09T03:55:08Z |
| format | Article |
| id | doaj.art-f946f2fad0274f3baa7955f3f30e01c8 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T03:55:08Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-f946f2fad0274f3baa7955f3f30e01c82023-12-03T14:22:43ZengMDPI AGRemote Sensing2072-42922021-01-0113338610.3390/rs13030386Monitoring 2019 Forest Fires in Southeastern Australia with GNSS TechniqueJinyun Guo0Rui Hou1Maosheng Zhou2Xin Jin3Chengming Li4Xin Liu5Hao Gao6College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, ChinaChinese Academy of Surveying and Mapping, Beijing 100036, ChinaCollege of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, ChinaFrom late 2019 to early 2020, forest fires in southeastern Australia caused huge economic losses and huge environmental pollution. Monitoring forest fires has become increasingly important. A new method of fire detection using the difference between global navigation satellite system (GNSS)-derived precipitable water vapor and radiosonde-derived precipitable water vapor (ΔPWV) is proposed. To study the feasibility of the new method, the relationship is studied between particulate matter 10 (PM10) (2.5 to 10 microns particulate matter) and ΔPWV based on Global Positioning System (GPS) data, radiosonde data, and PM10 data from 1 June 2019 to 1 June 2020 in southeastern Australia. The results show that before the forest fire, ΔPWV and PM10 were smaller and less fluctuating. When the forest fire happened, ΔPWV and PM10 were increasing. Then after the forest fire, PM10 became small with relatively smooth fluctuations, but ΔPWV was larger and more fluctuating. Correlation between the 15-day moving standard deviation (STD) time series of ΔPWV and PM10 after the fire was significantly higher than that before the fire. This study shows that ΔPWV is effective in monitoring forest fires based on GNSS technique before and during forest fires in climates with more uniform precipitation, and using ΔPWV to detect forest fires based on GNSS needs to be further investigated in climates with more precipitation and severe climate change.https://www.mdpi.com/2072-4292/13/3/386Australian forest firesglobal navigation satellite system (GNSS)precipitable water vapor (PWV)PM10radiosonde |
| spellingShingle | Jinyun Guo Rui Hou Maosheng Zhou Xin Jin Chengming Li Xin Liu Hao Gao Monitoring 2019 Forest Fires in Southeastern Australia with GNSS Technique Remote Sensing Australian forest fires global navigation satellite system (GNSS) precipitable water vapor (PWV) PM10 radiosonde |
| title | Monitoring 2019 Forest Fires in Southeastern Australia with GNSS Technique |
| title_full | Monitoring 2019 Forest Fires in Southeastern Australia with GNSS Technique |
| title_fullStr | Monitoring 2019 Forest Fires in Southeastern Australia with GNSS Technique |
| title_full_unstemmed | Monitoring 2019 Forest Fires in Southeastern Australia with GNSS Technique |
| title_short | Monitoring 2019 Forest Fires in Southeastern Australia with GNSS Technique |
| title_sort | monitoring 2019 forest fires in southeastern australia with gnss technique |
| topic | Australian forest fires global navigation satellite system (GNSS) precipitable water vapor (PWV) PM10 radiosonde |
| url | https://www.mdpi.com/2072-4292/13/3/386 |
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