TY - CONF

T1 - Quality assessment of Persistent Scatterer Interferometry time series using vector-autoregressive-based spatio-temporal (VAR-ST-PS) modelling

AU - Omidalizarandi, Mohammad

AU - Shahryarinia, Kourosh

AU - Mohammadivojdan, Bahareh

AU - Neumann, Ingo

PY - 2024/4/16

Y1 - 2024/4/16

N2 - Large-scale, cost-effective, and reliable deformation monitoring of natural objects or man-made infrastructures is still challenging. Numerous past studies have employed the Persistent Scatterer Interferometry (PSI) technique, utilising open-source synthetic aperture radar (SAR) data from C-band of satellite Sentinel-1, for this purpose. However, a limited number of investigations have been performed to evaluate the quality of the Persistent Scatterer (PS) data points.In this research, a comprehensive and sophisticated multi-step procedure is developed and implemented to perform quality assessment of the PS data points using vector-autoregressive-based spatio-temporal (VAR-ST-PS) modelling. Firstly, the PS points are classified into buildings and ground types using LoD2 building models. Multivariate PSI time series analysis is then carried out to understand the temporal behaviours of groups of PS points in local geometric patches. This involves modelling and analysing PSI time series to estimate deterministic and stochastic parameters such as offset, velocity, standard deviation, and corresponding distributional parameters. A spatio-temporal modelling is employed within the local geometric patches of PS points using a mathematical surface approximation model. A 95% confidence interval is estimated for the approximated surfaces using a bootstrapping approach. Subsequently, an appropriate quality model for the PS points is derived from the above-mentioned temporal and spatial modelling. The quality assessment and subsequent deformation analysis are carried out for areas of interest in the state of Lower Saxony, Germany. The PS data points for this study are extracted from the freely available online platform of the BodenBewegungsdienst Deutschland (Ground Motion Service Germany) provided by the Federal Institute for Geosciences and Natural Resources (BGR), Germany. For validation purposes, a time series of leveling and Global Navigation Satellite System (GNSS) measurements in the Hengstlage area, Germany, are considered, which provided by Landesamt für Geoinformation und Landesvermessung Niedersachsen (LGLN). In addition, cross-validation is performed for different local geometric patches. In the end, the results of the deformation analysis are compared with those obtained from the BGR. The outcomes of this study can be used to track earth surface displacements over time. This information could be valuable in understanding natural hazard processes such as landslides, earthquakes, and floods, and in improving the safety and resilience of communities and infrastructure.

AB - Large-scale, cost-effective, and reliable deformation monitoring of natural objects or man-made infrastructures is still challenging. Numerous past studies have employed the Persistent Scatterer Interferometry (PSI) technique, utilising open-source synthetic aperture radar (SAR) data from C-band of satellite Sentinel-1, for this purpose. However, a limited number of investigations have been performed to evaluate the quality of the Persistent Scatterer (PS) data points.In this research, a comprehensive and sophisticated multi-step procedure is developed and implemented to perform quality assessment of the PS data points using vector-autoregressive-based spatio-temporal (VAR-ST-PS) modelling. Firstly, the PS points are classified into buildings and ground types using LoD2 building models. Multivariate PSI time series analysis is then carried out to understand the temporal behaviours of groups of PS points in local geometric patches. This involves modelling and analysing PSI time series to estimate deterministic and stochastic parameters such as offset, velocity, standard deviation, and corresponding distributional parameters. A spatio-temporal modelling is employed within the local geometric patches of PS points using a mathematical surface approximation model. A 95% confidence interval is estimated for the approximated surfaces using a bootstrapping approach. Subsequently, an appropriate quality model for the PS points is derived from the above-mentioned temporal and spatial modelling. The quality assessment and subsequent deformation analysis are carried out for areas of interest in the state of Lower Saxony, Germany. The PS data points for this study are extracted from the freely available online platform of the BodenBewegungsdienst Deutschland (Ground Motion Service Germany) provided by the Federal Institute for Geosciences and Natural Resources (BGR), Germany. For validation purposes, a time series of leveling and Global Navigation Satellite System (GNSS) measurements in the Hengstlage area, Germany, are considered, which provided by Landesamt für Geoinformation und Landesvermessung Niedersachsen (LGLN). In addition, cross-validation is performed for different local geometric patches. In the end, the results of the deformation analysis are compared with those obtained from the BGR. The outcomes of this study can be used to track earth surface displacements over time. This information could be valuable in understanding natural hazard processes such as landslides, earthquakes, and floods, and in improving the safety and resilience of communities and infrastructure.

U2 - 10.5194/egusphere-egu24-17912

DO - 10.5194/egusphere-egu24-17912

M3 - Slides to presentation

SP - EGU24-17912

T2 - EGU General Assembly 2024

Y2 - 14 April 2024 through 19 April 2024

ER -