TIRVolcH: Thermal Infrared Recognition of Volcanic Hotspots. A single band TIR-based algorithm to detect low-to-high thermal anomalies in volcanic regions.

IF 11.1 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES
S. Aveni , M. Laiolo , A. Campus , F. Massimetti , D. Coppola
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引用次数: 0

Abstract

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.
TIRVolcH:火山热点热红外识别。一种基于单波段热红外的算法,用于探测火山区域从低到高的热异常。
探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,对于及时评估相关危害都至关重要。事实证明,热遥感是实现这些目标的一种经济而可靠的信息来源,特别是对于仍然缺乏传统地面监测网络的数百座火山而言。在这项工作中,我们提出了一种创新而有效的基于可见光红外波段(11.45 μm)的单波段算法(TIRVolcH ),能够探测从低温热液系统到高温喷出事件等各种火山环境中的热异常。该算法以可见红外成像辐射计套件(VIIRS)场景处理为基础,在空间分辨率(375 米)和时间分辨率(每天多次采集)之间进行了前所未有的权衡,有可能探测到像素积分温度比背景低 0.5 千帕的热异常,同时保持 1.8%的误报率。对在三座不同火山获取的 VIIRS 数据十年时间序列(2012-2023 年)进行的分析揭示了该算法如何能够:(我们预计,该算法将被证明有助于探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,统计上可靠的十年期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热成像仪任务奠定基础。
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来源期刊
Remote Sensing of Environment
Remote Sensing of Environment 环境科学-成像科学与照相技术
CiteScore
25.10
自引率
8.90%
发文量
455
审稿时长
53 days
期刊介绍: Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.
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