Near real-time mapping of burned area by synergizing multiple satellites remote-sensing data
Wildfires have significant impacts on human lives, critical infrastructures, and Earth’s ecosystems. Accurate and timely information on burned area (BA) affected by wildfires is vital to better understand the drivers of wildfire events, as well as its relevance for biogeochemical cycles, climate, an...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-12-01
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| Series: | GIScience & Remote Sensing |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/15481603.2022.2143690 |
| _version_ | 1827811745568129024 |
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| author | Lipeng Jiao Yanchen Bo |
| author_facet | Lipeng Jiao Yanchen Bo |
| author_sort | Lipeng Jiao |
| collection | DOAJ |
| description | Wildfires have significant impacts on human lives, critical infrastructures, and Earth’s ecosystems. Accurate and timely information on burned area (BA) affected by wildfires is vital to better understand the drivers of wildfire events, as well as its relevance for biogeochemical cycles, climate, and air quality, and to aid wildfire management. Single satellite data have been used to detect the characteristics of wildfires, retrospectively mapping BAs at a variety of spatial resolutions in previous studies. However, due to the trade-off between spatial and temporal resolutions, single-source satellite data are not sufficient to characterize the explicit dynamics of BAs at high resolutions in both space and time. Thus, a two-stage near real-time BA mapping method was developed in this study to take advantage of the high temporal frequency of coarse resolution sensors and the fine spatial resolution of medium resolution sensors in BA mapping by synergizing freely available coarse and medium spatial resolution (MSR) sensors. First, high temporal frequency sensors such as MODIS and VIIRS were used to identify wildfires and potential BAs. Then, multiple MSR sensors such as Sentinel-2A/2B, Landsat OLI, and Resourcesat AWiFS were synthesized for extracting the BAs with more spatial details in near real-time. We applied the method in California, USA, where wildfires occurred in northern and southern parts in 2017. The results showed that the proposed method is promising for BA mapping with an overall accuracy of 0.84 and 0.85 for wildfires in northern and southern California, respectively. Additionally, the proposed method greatly improved the frequency and reduced the latency, with an average interval of 3.5 days (3 days) and latency of 4 days (sub-daily) for wildfires in southern (northern) California. The extracted BAs illustrated accurate spatial details with MSR sensors. Our method can significantly take advantage of multi-source remote-sensing observations to accurately map the BAs of active wildfires in near real-time. More importantly, the method can be applied to other geographic regions where wildfires risk humans and ecosystems. |
| first_indexed | 2024-03-11T23:08:56Z |
| format | Article |
| id | doaj.art-f06682cb46ae4c54848be61f13ed366c |
| institution | Directory Open Access Journal |
| issn | 1548-1603 1943-7226 |
| language | English |
| last_indexed | 2024-03-11T23:08:56Z |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | GIScience & Remote Sensing |
| spelling | doaj.art-f06682cb46ae4c54848be61f13ed366c2023-09-21T12:43:09ZengTaylor & Francis GroupGIScience & Remote Sensing1548-16031943-72262022-12-015911956197710.1080/15481603.2022.21436902143690Near real-time mapping of burned area by synergizing multiple satellites remote-sensing dataLipeng Jiao0Yanchen Bo1Beijing Normal UniversityBeijing Normal UniversityWildfires have significant impacts on human lives, critical infrastructures, and Earth’s ecosystems. Accurate and timely information on burned area (BA) affected by wildfires is vital to better understand the drivers of wildfire events, as well as its relevance for biogeochemical cycles, climate, and air quality, and to aid wildfire management. Single satellite data have been used to detect the characteristics of wildfires, retrospectively mapping BAs at a variety of spatial resolutions in previous studies. However, due to the trade-off between spatial and temporal resolutions, single-source satellite data are not sufficient to characterize the explicit dynamics of BAs at high resolutions in both space and time. Thus, a two-stage near real-time BA mapping method was developed in this study to take advantage of the high temporal frequency of coarse resolution sensors and the fine spatial resolution of medium resolution sensors in BA mapping by synergizing freely available coarse and medium spatial resolution (MSR) sensors. First, high temporal frequency sensors such as MODIS and VIIRS were used to identify wildfires and potential BAs. Then, multiple MSR sensors such as Sentinel-2A/2B, Landsat OLI, and Resourcesat AWiFS were synthesized for extracting the BAs with more spatial details in near real-time. We applied the method in California, USA, where wildfires occurred in northern and southern parts in 2017. The results showed that the proposed method is promising for BA mapping with an overall accuracy of 0.84 and 0.85 for wildfires in northern and southern California, respectively. Additionally, the proposed method greatly improved the frequency and reduced the latency, with an average interval of 3.5 days (3 days) and latency of 4 days (sub-daily) for wildfires in southern (northern) California. The extracted BAs illustrated accurate spatial details with MSR sensors. Our method can significantly take advantage of multi-source remote-sensing observations to accurately map the BAs of active wildfires in near real-time. More importantly, the method can be applied to other geographic regions where wildfires risk humans and ecosystems.http://dx.doi.org/10.1080/15481603.2022.2143690wildfireburned areanear real-timehigh spatiotemporal resolutionmulti-source satellite images |
| spellingShingle | Lipeng Jiao Yanchen Bo Near real-time mapping of burned area by synergizing multiple satellites remote-sensing data GIScience & Remote Sensing wildfire burned area near real-time high spatiotemporal resolution multi-source satellite images |
| title | Near real-time mapping of burned area by synergizing multiple satellites remote-sensing data |
| title_full | Near real-time mapping of burned area by synergizing multiple satellites remote-sensing data |
| title_fullStr | Near real-time mapping of burned area by synergizing multiple satellites remote-sensing data |
| title_full_unstemmed | Near real-time mapping of burned area by synergizing multiple satellites remote-sensing data |
| title_short | Near real-time mapping of burned area by synergizing multiple satellites remote-sensing data |
| title_sort | near real time mapping of burned area by synergizing multiple satellites remote sensing data |
| topic | wildfire burned area near real-time high spatiotemporal resolution multi-source satellite images |
| url | http://dx.doi.org/10.1080/15481603.2022.2143690 |
| work_keys_str_mv | AT lipengjiao nearrealtimemappingofburnedareabysynergizingmultiplesatellitesremotesensingdata AT yanchenbo nearrealtimemappingofburnedareabysynergizingmultiplesatellitesremotesensingdata |