Regional Ground Movement Detection by Analysis and Modeling PSI Observations

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OriginalspracheEnglisch
Aufsatznummer2246
FachzeitschriftRemote sensing
Jahrgang13
Ausgabenummer12
PublikationsstatusVeröffentlicht - 8 Juni 2021

Abstract

Any changes to the Earth’s surface should be monitored in order to maintain and update the spatial reference system. To establish a global model of ground movements for a large area, it is important to have consistent and reliable measurements. However, in dealing with mass data, outliers may occur and robust analysis of data is indispensable. In particular, this paper will analyse Synthetic Aperture Radar (SAR) data for detecting the regional ground movements (RGM) in the area of Hanover, Germany. The relevant data sets have been provided by the Federal Institute for Geo-sciences and Natural Resources (BGR) for the period of 2014 to 2018. In this paper, we propose a data adoptive outlier detection algorithm to preprocess the observations. The algorithm is tested with different reference data sets and as a binary classifier performs with 0.99 accuracy and obtains a 0.95 F1-score in detecting the outliers. The RGMs that are observed as height velocities are mathematically modeled as a surface based on a hierarchical B-splines (HB-splines) method. For the approximated surface, a 95% confidence interval is estimated based on a bootstrapping approach. In the end, the user is enabled to predict RGM at any point and is provided with a measure of quality for the prediction.

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Regional Ground Movement Detection by Analysis and Modeling PSI Observations. / Mohammadivojdan, Bahareh; Brockmeyer, Marco; Jahn, Cord-Hinrich et al.
in: Remote sensing, Jahrgang 13, Nr. 12, 2246, 08.06.2021.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Mohammadivojdan, Bahareh ; Brockmeyer, Marco ; Jahn, Cord-Hinrich et al. / Regional Ground Movement Detection by Analysis and Modeling PSI Observations. in: Remote sensing. 2021 ; Jahrgang 13, Nr. 12.
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AU - Brockmeyer, Marco

AU - Jahn, Cord-Hinrich

AU - Neumann, Ingo

AU - Alkhatib, Hamza

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