Applying the Tropical Peatland Combustion Algorithm to Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery
This study establishes a new technique for peatland fire detection in tropical environments using Landsat-8 and Sentinel-2. The Tropical Peatland Combustion Algorithm (ToPeCAl) without longwave thermal infrared (TIR) (henceforth known as ToPeCAl-2) was tested on Landsat-8 Operational Land Imager (OL...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-12-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/23/3958 |
| _version_ | 1797545818101645312 |
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| author | Parwati Sofan David Bruce Eriita Jones M. Rokhis Khomarudin Orbita Roswintiarti |
| author_facet | Parwati Sofan David Bruce Eriita Jones M. Rokhis Khomarudin Orbita Roswintiarti |
| author_sort | Parwati Sofan |
| collection | DOAJ |
| description | This study establishes a new technique for peatland fire detection in tropical environments using Landsat-8 and Sentinel-2. The Tropical Peatland Combustion Algorithm (ToPeCAl) without longwave thermal infrared (TIR) (henceforth known as ToPeCAl-2) was tested on Landsat-8 Operational Land Imager (OLI) data and then applied to Sentinel-2 Multi Spectral Instrument (MSI) data. The research is aimed at establishing peatland fire information at higher spatial resolution and more frequent observation than from Landsat-8 data over Indonesia’s peatlands. ToPeCAl-2 applied to Sentinel-2 was assessed by comparing fires detected from the original ToPeCAl applied to Landsat-8 OLI/Thermal Infrared Sensor (TIRS) verified through comparison with ground truth data. An adjustment of ToPeCAl-2 was applied to minimise false positive errors by implementing pre-process masking for water and permanent bright objects and filtering ToPeCAl-2’s resultant detected fires by implementing contextual testing and cloud masking. Both ToPeCAl-2 with contextual test and ToPeCAl with cloud mask applied to Sentinel-2 provided high detection of unambiguous fire pixels (>95%) at 20 m spatial resolution. Smouldering pixels were less likely to be detected by ToPeCAl-2. The detected smouldering pixels from ToPeCAl-2 applied to Sentinel-2 with contextual testing and with cloud masking were only 35% and 56% correct, respectively; this needs further investigation and validation. These results demonstrate that even in the absence of TIR data, an adjusted ToPeCAl algorithm (ToPeCAl-2) can be applied to detect peatland fires at 20 m resolution with high accuracy especially for flaming. Overall, the implementation of ToPeCAl applied to cost-free and available Landsat-8 and Sentinel-2 data enables regular peatland fire monitoring in tropical environments at higher spatial resolution than other satellite-derived fire products. |
| first_indexed | 2024-03-10T14:21:23Z |
| format | Article |
| id | doaj.art-69af2ffdecbd45d396ff56a3601c5c7c |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T14:21:23Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-69af2ffdecbd45d396ff56a3601c5c7c2023-11-20T23:22:32ZengMDPI AGRemote Sensing2072-42922020-12-011223395810.3390/rs12233958Applying the Tropical Peatland Combustion Algorithm to Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) ImageryParwati Sofan0David Bruce1Eriita Jones2M. Rokhis Khomarudin3Orbita Roswintiarti4Science, Technology, Engineering and Mathematics (STEM), Scarce Resources and Circular Economy (ScaRCE), University of South Australia, Adelaide/Mawson Lakes, SA 5000, AustraliaScience, Technology, Engineering and Mathematics (STEM), Scarce Resources and Circular Economy (ScaRCE), University of South Australia, Adelaide/Mawson Lakes, SA 5000, AustraliaScience, Technology, Engineering and Mathematics (STEM), Scarce Resources and Circular Economy (ScaRCE), University of South Australia, Adelaide/Mawson Lakes, SA 5000, AustraliaRemote Sensing Application Center of Indonesian Institute of Aeronautics and Space (LAPAN), Jakarta 13710, IndonesiaRemote Sensing Technology and Data Center of Indonesian Institute of Aeronautics and Space (LAPAN), Jakarta 13710, IndonesiaThis study establishes a new technique for peatland fire detection in tropical environments using Landsat-8 and Sentinel-2. The Tropical Peatland Combustion Algorithm (ToPeCAl) without longwave thermal infrared (TIR) (henceforth known as ToPeCAl-2) was tested on Landsat-8 Operational Land Imager (OLI) data and then applied to Sentinel-2 Multi Spectral Instrument (MSI) data. The research is aimed at establishing peatland fire information at higher spatial resolution and more frequent observation than from Landsat-8 data over Indonesia’s peatlands. ToPeCAl-2 applied to Sentinel-2 was assessed by comparing fires detected from the original ToPeCAl applied to Landsat-8 OLI/Thermal Infrared Sensor (TIRS) verified through comparison with ground truth data. An adjustment of ToPeCAl-2 was applied to minimise false positive errors by implementing pre-process masking for water and permanent bright objects and filtering ToPeCAl-2’s resultant detected fires by implementing contextual testing and cloud masking. Both ToPeCAl-2 with contextual test and ToPeCAl with cloud mask applied to Sentinel-2 provided high detection of unambiguous fire pixels (>95%) at 20 m spatial resolution. Smouldering pixels were less likely to be detected by ToPeCAl-2. The detected smouldering pixels from ToPeCAl-2 applied to Sentinel-2 with contextual testing and with cloud masking were only 35% and 56% correct, respectively; this needs further investigation and validation. These results demonstrate that even in the absence of TIR data, an adjusted ToPeCAl algorithm (ToPeCAl-2) can be applied to detect peatland fires at 20 m resolution with high accuracy especially for flaming. Overall, the implementation of ToPeCAl applied to cost-free and available Landsat-8 and Sentinel-2 data enables regular peatland fire monitoring in tropical environments at higher spatial resolution than other satellite-derived fire products.https://www.mdpi.com/2072-4292/12/23/3958peatland fires detectionSentinel-2Landsat-8SWIRTIR |
| spellingShingle | Parwati Sofan David Bruce Eriita Jones M. Rokhis Khomarudin Orbita Roswintiarti Applying the Tropical Peatland Combustion Algorithm to Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery Remote Sensing peatland fires detection Sentinel-2 Landsat-8 SWIR TIR |
| title | Applying the Tropical Peatland Combustion Algorithm to Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery |
| title_full | Applying the Tropical Peatland Combustion Algorithm to Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery |
| title_fullStr | Applying the Tropical Peatland Combustion Algorithm to Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery |
| title_full_unstemmed | Applying the Tropical Peatland Combustion Algorithm to Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery |
| title_short | Applying the Tropical Peatland Combustion Algorithm to Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery |
| title_sort | applying the tropical peatland combustion algorithm to landsat 8 operational land imager oli and sentinel 2 multi spectral instrument msi imagery |
| topic | peatland fires detection Sentinel-2 Landsat-8 SWIR TIR |
| url | https://www.mdpi.com/2072-4292/12/23/3958 |
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