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Concept to analyze the displacement time series of individual persistent scatterers

Evers, M.; Thiele, A.; Hammer, H.; Cadario, E.; Schulz, K.; Hinz, S.


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. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000138866
Veröffentlicht am 13.10.2021
DOI: 10.5194/isprs-archives-XLIII-B3-2021-147-2021
Zitationen: 4
Zitationen: 4
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Photogrammetrie und Fernerkundung (IPF)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2021
Sprache Englisch
Identifikator ISSN: 1682-1750
KITopen-ID: 1000138866
Erschienen in XXIV ISPRS Congress (2021 edition). Ed.: N. Paparoditis
Veranstaltung 24th ISPRS Congress (2021), Online, 05.07.2021 – 09.07.2021
Verlag International Society for Photogrammetry and Remote Sensing (ISPRS)
Seiten 147-154
Serie The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; 43
Nachgewiesen in Dimensions
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