Abstract
A Tropical Peatland Combustion Algorithm (ToPeCAl) was first established from Landsat-8 images acquired in 2015, which were used to detect peatland combustion in flaming and smouldering stages. Detection of smouldering combustion from space remains a challenge due to its low temperature and generally small spatial extent. The ToPeCAl consists of the Shortwave Infrared Combustion Index based on reflectance (SICIρ), and Top of Atmosphere (TOA) reflectance in Shortwave Infrared band-7 (SWIR-2), TOA brightness temperature of Thermal Infrared band-10 (TIR-1), and TOA reflectance of band-1, the Landsat-8 aerosol band. The implementation of ToPeCAl was then validated using terrestrial and aerial images (helicopter and drone) collected during fieldwork in Central Kalimantan, Indonesia in the 2018 fire season, on the same day as Landsat-8 overpasses. The overall accuracy of ToPeCAl was found to be 82% with omission errors in a small area (less than 30 m × 30 m) from mixtures of smouldering and vegetation pixels, and commission errors (with minimum area of 30 m x 30 m) on high reflective building rooftops in urban areas. These errors were further reduced by masking and removing urban areas prior to analysis using landuse Geographic Information System (GIS) data; improving the overall mapping accuracy to 93%. For comparison, the day and night-time VIIRS (375 m) active fire product (VNP14IMG) was utilised, obtaining a lower probability of fire detection of 71% compared to ground truth, and 57–72% agreement in a buffer distance of 375 m to 1500 m when compared to the Landsat-8 ToPeCAl results. The night-time data of VNP14IMG was found to have a better correspondence with ToPeCAl results from Landsat 8 than day-time data. This finding could lead to a potential merger of ToPeCAl with VNP14IMG to fill the temporal gaps of peatland fire information when using Landsat. However, the VNP14IMG product exhibited overestimation compared with the results of ToPeCAl applied to Landsat-8.
Highlights
Wildfire is a global issue which threatens every year during dry seasons
The discrimination of flaming and smouldering combustion of peatland fires over tropical areas can be mapped through the use of day-time images from Landsat-8
Tropical Peatland Combustion Algorithm (ToPeCAl) consists of the SICIρ for separating combustion from the non-combustion areas, Top of Atmosphere (TOA) planetary reflectance of shortwave infrared (SWIR)-2 (2.2 μm), and TOA brightness temperature of Thermal Infrared band-10 (TIR-1) (10.9 μm) for classifying the peatland combustion into flaming and smouldering stages
Summary
Wildfire is a global issue which threatens every year during dry seasons. For almost two decades, forest/land fires have attracted both interest and challenge for research to provide a useful monitoring system from satellite remote sensing data [1,2,3]. Most of the global operational fire products from low spatial resolution satellite data (~1 km pixel size) use the 3–4 μm (middle infrared (MIR)) and the 10–11 μm (thermal infrared (TIR)) components of the electromagnetic spectrum to detect smouldering and flaming fires, which operate at temperatures from 400 to 1200 K [27,28]. In the moderate spatial resolution area (30 and 100 m pixels) and repeated observation of 16 days, sensors such us Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) and Landsat-8 possibly could be used to detect flaming and smouldering peatland. This study explores how flaming and smouldering of tropical peat fires, with a variety of atmospheric states (clear and smoke conditions) can be detected from the SWIR and TIR of Landsat-8 day-time data. The temporal gaps of peatland fire monitoring from a medium spatial resolution (20–30 m) sensor may be filled leading to much needed regular monitoring of peatland fires
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