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PSDefoPAT—Persistent Scatterer Deformation Pattern Analysis Tool

Evers, Madeline 1; Thiele, Antje 1; Hammer, Horst; Hinz, Stefan 1
1 Institut für Photogrammetrie und Fernerkundung (IPF), Karlsruher Institut für Technologie (KIT)

Abstract:

Persistent Scatterer Deformation Pattern Analysis Tool, for short PSDefoPAT, was designed to assign each measuring point of an advanced DInSAR data set a best-fitting time series model based on its displacement time series. In this paper, we will outline the operating principles of the tool. The periodic and trend components of a time series model are separately determined based on hypothesis tests. The periodic component is fitted as a sine function, and for the trend component, linear, quadratic, and piecewise linear regression models are considered. Additionally, the tool assesses the goodness-of-fit for each model in the form of the adjusted coefficient of determination $R^2_{adj}$ value. The tool works fully automatically and thus facilitates the analysis of large data sets, which are becoming more available to the public due to services such as the European Ground Motion Service. Additionally, we demonstrate the capabilities of PSDefoPAT using four case studies characterized by different deformation mechanisms, various extents of active deformation area, and varying density of measuring points. In all cases, we successfully reveal information on the temporal behavior of the deformation not apparent in the typically presented mean deformation velocity maps.


Verlagsausgabe §
DOI: 10.5445/IR/1000163740
Veröffentlicht am 02.11.2023
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Photogrammetrie und Fernerkundung (IPF)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 01.10.2023
Sprache Englisch
Identifikator ISSN: 2072-4292
KITopen-ID: 1000163740
HGF-Programm 12.11.31 (POF IV, LK 01) New observational systems and cross platform integration
Erschienen in Remote Sensing
Verlag MDPI
Band 15
Heft 19
Seiten Art.-Nr.: 4646
Vorab online veröffentlicht am 22.09.2023
Schlagwörter advanced DInSAR, European Ground Motion Service, Sentinel-1, infrastructure monitoring, geo-hazards, time series analysis, EGMS
Nachgewiesen in Web of Science
Scopus
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