Routine Processing and Automatic Detection of Volcanic Ground Deformation Using Sentinel-1 InSAR Data: Insights from African Volcanoes
Routine Processing and Automatic Detection of Volcanic Ground Deformation Using Sentinel-1 InSAR Data: Insights from African Volcanoes
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DOI：
10.3390/rs14225703
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发表时间：
2022-11
期刊：
影响因子：
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通讯作者：
F. Albino;J. Biggs;M. Lazecký;Y. Maghsoudi
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作者：
F. Albino;J. Biggs;M. Lazecký;Y. Maghsoudi
自哨兵-1号使命发射以来，已开发了自动化处理系统，用于近实时监测地面变形信号。在这里，我们进行了5年的区域分析，超过64个火山中心位于沿着东非裂谷系（EARS）。我们表明，大气信号的干旱和低海拔EARS火山的校正是不太重要的比其他火山环境。我们发现，64座火山中有16座的累积位移幅度超过时间序列（3σ）的时间噪声的三倍，其中包括先前报道的变形信号，以及帕卡和西拉利火山的两个新信号。从一个5年的时间序列来看，变形率的不确定性为0.1厘米/年，而与参考像素的选择相关的不确定性通常为0.3-0.6厘米/年。我们适合的时间序列，使用简单的函数形式和分类的火山时间序列为“线性”，六个“sigmoidal”和三个“混合”，使我们能够区分稳定的变形和短期脉冲变形。这项研究提供了一个框架，在大陆尺度上使用干涉合成孔径雷达例行火山监测。在这里，我们重点关注EARS的Sentinel-1数据，但该框架可以扩展到包括其他卫星系统或全球覆盖范围。
Since the launch of Sentinel-1 mission, automated processing systems have been developed for near real-time monitoring of ground deformation signals. Here, we perform a regional analysis of 5 years over 64 volcanic centres located along the East African Rift System (EARS). We show that the correction of atmospheric signals for the arid and low-elevation EARS volcanoes is less important than for other volcanic environments. We find that the amplitude of the cumulative displacements exceeds three times the temporal noise of the time series (3σ) for 16 of the 64 volcanoes, which includes previously reported deformation signals, and two new ones at Paka and Silali volcanoes. From a 5-year times series, uncertainties in rates of deformation are ∼0.1 cm/yr, whereas uncertainties associated with the choice of reference pixel are typically 0.3–0.6 cm/yr. We fit the time series using simple functional forms and classify seven of the volcano time series as ‘linear’, six as ‘sigmoidal’ and three as ‘hybrid’, enabling us to discriminate between steady deformation and short-term pulses of deformation. This study provides a framework for routine volcano monitoring using InSAR on a continental scale. Here, we focus on Sentinel-1 data from the EARS, but the framework could be expanded to include other satellite systems or global coverage.