Abstract
Abstract. Persistent Scatterer Interferometry (PSInSAR) exploits a time series of Synthetic Aperture Radar (SAR) images to estimate the mean velocity with which the surface of the earth is deforming. However, most PSInSAR algorithms estimate the mean velocities using a linear regression model. Since some deformation phenomena can exhibit a more complex behavior over time, using a linear regression model leads to potentially wrong estimations for the mean velocity. For example, the velocity of a landslide moving down a steep slope can change depending on the water content of the material of the landslide, or an inactive landslide can reactivate due to an earthquake. Both scenarios would not result in a time series with a constant linear slope but in a piecewise linear time series.This paper presents a Matlab-based tool to analyze an individual Persistent Scatterer (PS) time series. The Persistent Scatterer Deformation Pattern Analysis Tool (PSDefoPAT) aims to build a mathematical model that sufficiently describes the time series trend and seasonal and noise components. The trend component is estimated using polynomial regression and piecewise linear models, while a sine function approximates the seasonal component. The goal is to identify the best fitting model for the displacement time series of a PS. PSDefoPAT is introduced by examine the time series of three different PS located in the region surrounding Patras, Greece. Based on the derived models, we discuss the nature of their deformation patterns.
Highlights
Persistent Scatterer Interferometry (PSInSAR) is a method widely used to monitor the deformation of the surface of the earth
We presented a Matlab-based tool to analyze the displacement time series of the individual PS
We demonstrated with three exemplary PS displacement time series, that additional relevant information is gained by decomposing the time series into its trend, seasonal and noise component
Summary
Persistent Scatterer Interferometry (PSInSAR) is a method widely used to monitor the deformation of the surface of the earth. Studies such as Tomás et al (2019) have used these estimates to, for example, distinguish active persistent scatterers (PS) from non-active ones and define areas of active deformation. Afterward, they use the displacement time series of those areas to associate them with different deformation patterns. The map shows the mean velocities of the city of Patras in southern Greece and its surrounding region, estimated for the observation period from January 2019 to January 2021 Based on this map, many red or blue PS clusters would be regarded as actively deforming areas. Faults can switch from being active to being dormant and vice versa, meaning the mean velocity of that area is underestimated or overestimated
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