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Wavelet analysis of land subsidence time-series: Madrid Tertiary aquifer case study

机译:土地沉降时间系列小波分析 - 马德里大学含水层案例研究

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Interpretation of land subsidence time-series to understand the evolution of the phenomenon and the existing relationships between triggers and measured displacements is a great challenge. Continuous wavelet transform (CWT) is a powerful signal processing method mainly suitable for the analysis of individual nonstationary time-series. CWT expands time-series into the time-frequency space allowing identification of localized nonstationary periodicities. Complementarily, Cross Wavelet Transform (XWT) and Wavelet Coherence (WTC) methods allow the comparison of two time-series that may be expected to be related in order to identify regions in the time-frequency domain that exhibit large common cross-power and wavelet coherence, respectively, and therefore are evocative of causality. In this work we use CWT, XWT and WTC to analyze piezometric and InSAR (interferometric synthetic aperture radar) time-series from the Tertiary aquifer of Madrid (Spain) to illustrate their capabilities for interpreting land subsidence and piezometric time-series information.
机译:解释土地沉降时间系列以了解现象的演变和触发器之间存在的现有关系是一个巨大的挑战。连续小波变换(CWT)是一种强大的信号处理方法,主要适用于分析个体非间断时间序列。 CWT将时间序列扩展到时频空间,允许识别本地化的非标准周期。互补地,跨小波变换(XWT)和小波相干性(WTC)方法允许比较两个时间序列,其可以预期与展示具有大型常见交叉电源和小波的时频域中的区域相关联分别相干,因此令人兴奋的因果关系。在这项工作中,我们使用CWT,XWT和WTC来分析来自马德里(西班牙)的第三级含水层的压电和insar(干涉合成孔径雷达)时间序列,以说明它们对解释土地沉降和压电时间序列信息的能力。

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