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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Main Authors: Parwati Sofan, David Bruce, Eriita Jones, M. Rokhis Khomarudin, Orbita Roswintiarti
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Remote Sensing
Subjects:
TIR
Online Access:https://www.mdpi.com/2072-4292/12/23/3958
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spelling doaj-69af2ffdecbd45d396ff56a3601c5c7c2020-12-04T00:03:19ZengMDPI AGRemote Sensing2072-42922020-12-01123958395810.3390/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 Roswintiarti4Scarce Resources and Circular Economy (ScaRCE), University of South Australia, Science, Technology, Engineering and Mathematics (STEM), Adelaide/Mawson Lakes, SA 5000, AustraliaScarce Resources and Circular Economy (ScaRCE), University of South Australia, Science, Technology, Engineering and Mathematics (STEM), Adelaide/Mawson Lakes, SA 5000, AustraliaScarce Resources and Circular Economy (ScaRCE), University of South Australia, Science, Technology, Engineering and Mathematics (STEM), 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
collection DOAJ
language English
format Article
sources DOAJ
author Parwati Sofan
David Bruce
Eriita Jones
M. Rokhis Khomarudin
Orbita Roswintiarti
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
author_facet Parwati Sofan
David Bruce
Eriita Jones
M. Rokhis Khomarudin
Orbita Roswintiarti
author_sort Parwati Sofan
title 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_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_sort applying the tropical peatland combustion algorithm to landsat-8 operational land imager (oli) and sentinel-2 multi spectral instrument (msi) imagery
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2020-12-01
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.
topic peatland fires detection
Sentinel-2
Landsat-8
SWIR
TIR
url https://www.mdpi.com/2072-4292/12/23/3958
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