Detecting early signs of impending eruptions and monitoring the evolution of volcanic phenomena are fundamental objectives of applied volcanology, both essential for timely assessment of associated hazards. Thermal remote sensing proves to be a cost-effective, yet reliable, information source for these purposes, especially for the hundreds of volcanoes still lacking conventional ground-based monitoring networks. In this work, we present an innovative and effective single band TIR-based (11.45 μm) algorithm (TIRVolcH), capable of detecting thermal anomalies in a broad range of volcanic settings, from low-temperature hydrothermal systems to high-temperature effusive events. Based on the processing of Visible Infrared Imaging Radiometer Suite (VIIRS) scenes, the algorithm offers an unprecedented trade-off between spatial (375 m) and temporal resolution (multiple acquisitions per day), having the potential to detect thermal anomalies for pixel-integrated temperatures as low as 0.5 K above the background, while maintaining a false positive rate of ∼1.8 %. The analysis of decadal time series of VIIRS data (2012−2023), acquired at three different volcanoes, reveals how the algorithm can: (i) detect hydrothermal crises at fumarolic fields (Vulcano, Italy), (ii) unveil thermal unrest preceding dome extrusions and explosive eruptions (Agung, Indonesia), and (iii) spatially trace lava flows extent and quantify their advancement rate, as well as track their long-term cooling behaviour (La Palma, Spain).We envisage that the algorithm will prove instrumental for detecting early signs of volcanic activity and following the evolution of eruptive phenomena, providing a useful tool for hazard management and risk reduction applications. Furthermore, the compilation of statistically robust multidecadal thermal datasets will provide novel insights and new perspectives into volcano monitoring, laying the ground for forthcoming higher-resolution TIR missions.

中文翻译：

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TIRVolcH：火山热点的热红外识别。一种基于单波段 TIR 的算法，用于检测火山区域中从低到高的热异常。


检测即将喷发的早期迹象和监测火山现象的演变是应用火山学的基本目标，这两者都对于及时评估相关危害至关重要。热遥感被证明是一种经济高效但可靠的信息来源，特别是对于仍然缺乏常规地面监测网络的数百座火山。在这项工作中，我们提出了一种创新且有效的基于 TIR 的单波段 （11.45 μm） 算法 （TIRVolcH），能够检测从低温热液系统到高温喷发事件的广泛火山环境中的热异常。基于可见光红外成像辐射计套件 （VIIRS） 场景的处理，该算法在空间分辨率（375 m）和时间分辨率（每天多次采集）之间提供了前所未有的权衡，有可能检测到低至背景上方 0.5 K 的像素积分温度的热异常，同时保持 ∼1.8% 的假阳性率。对在三个不同火山获取的 VIIRS 数据（2012-2023 年）的年代际时间序列的分析揭示了该算法如何：（i） 检测喷气田的热液危机（意大利武尔卡诺），（ii） 揭示圆顶挤压和爆炸性喷发之前的热动荡（印度尼西亚阿贡），以及 （iii） 空间追踪熔岩流范围并量化其推进速率，以及跟踪其长期冷却行为（拉帕尔马， Spain）。我们设想该算法将有助于检测火山活动的早期迹象和跟踪喷发现象的演变，为灾害管理和降低风险应用提供有用的工具。 此外，统计上稳健的多年代际热数据集的汇编将为火山监测提供新的见解和新的视角，为即将到来的更高分辨率的 TIR 任务奠定基础。