This paper presents a methodological approach to the time-series analysis of movement monitoring data of a large slow-moving landslide. It combines different methods of data manipulation to decrease the subjectivity of a researcher and provides a fully quantitative approach for analyzing large amounts of data. The methodology was applied to 3D dilatometric data acquired from the giant San Andrés Landslide on El Hierro in the Canary Islands in the period from October 2013 to April 2019. The landslide is a creeping volcanic flank collapse showing a decrease of speed of movement during the monitoring period. Despite the fact that clear and unambiguous geological interpretations cannot be made, the analysis is capable of showing correlations of the changes of the movement with increased seismicity and, to some point, with precipitation. We consider this methodology being the first step in automatizing and increasing the objectivity of analysis of slow-moving landslide monitoring data.

中文翻译：

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3D膨胀计时间序列分析可更好地了解巨型慢速滑坡的动力学

本文提出了一种对大型慢速滑坡运动监测数据进行时间序列分析的方法学方法。它结合了不同的数据处理方法以降低研究人员的主观性，并提供了一种用于分析大量数据的完全定量的方法。该方法应用于从2013年10月至2019年4月期间从加那利群岛El Hierro上的SanAndrés滑坡巨人采集的3D测斜数据。该滑坡是一个蠕动的火山侧面崩塌，表明监测期间移动速度降低期。尽管无法做出清晰，明确的地质解释，但该分析仍能够显示出运动变化与地震活动性以及在某种程度上与降水的相关性。