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.

中文翻译：

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热带泥炭地燃烧算法在Landsat-8作战陆地成像仪（OLI）和Sentinel-2多光谱仪（MSI）成像中的应用

这项研究建立了使用Landsat-8和Sentinel-2在热带环境中检测泥炭地火的新技术。对不带长波热红外（TIR）的热带泥炭地燃烧算法（ToPeCAl）（以下称为ToPeCAl-2）进行了Landsat-8操作性陆地成像仪（OLI）数据测试，然后将其应用于Sentinel-2多光谱仪（MSI）数据。这项研究的目的是建立泥炭地火信息，其空间分辨率和观测频率要高于印度尼西亚泥炭地的Landsat-8数据。通过比较从原始ToPeCAl应用于Landsat-8 OLI /热红外传感器（TIRS）所检测到的火势，并与地面真实数据进行比较，对火灾进行了评估，从而评估了应用于Sentinel-2的ToPeCAl-2。对ToPeCAl-2进行了调整，以通过对水和永久亮物体实施预处理遮罩，并通过进行上下文测试和云遮罩对ToPeCAl-2产生的探测到的火灾进行过滤来最大程度地减少假阳性错误。应用于上下文测试的ToPeCAl-2和应用于Sentinel-2的具有云遮罩的ToPeCAl都可以在20 m空间分辨率下对清晰的火灾像素（> 95％）进行高检测。ToPeCAl-2不太可能检测到闷烧的像素。通过上下文测试和云遮罩应用到Sentinel-2的ToPeCAl-2中检测到的闷烧像素分别正确率只有35％和56％。这需要进一步的调查和验证。这些结果表明，即使没有TIR数据，可以将经过调整的ToPeCAl算法（ToPeCAl-2）用于以20 m的分辨率检测泥炭地大火，并具有很高的准确度，特别是用于燃烧。总体而言，将ToPeCAl应用于免费和可用的Landsat-8和Sentinel-2数据，可以在热带环境中以比其他卫星衍生消防产品更高的空间分辨率对泥炭地进行常规火情监测。