Details
| Original language | English |
|---|---|
| Pages (from-to) | 119-131 |
| Number of pages | 13 |
| Journal | Journal of Applied Geodesy |
| Volume | 17 |
| Issue number | 2 |
| Early online date | 28 Feb 2023 |
| Publication status | Published - 25 Apr 2023 |
Abstract
based on time series analysis of specific points. It also enables performing spatio-temporal area-based deformation monitoring. Currently, these data do not have a sophisticated quality assurance process to judge the significance of deformations. To obtain different quality classes of the Persistent Scatterer (PS) data points, the first step is to classify them into buildings and ground types using LoD2 building models. Next, time series analysis of the PS points is performed to model systematic and random errors. It allows estimation of the offset and the deformation rate for each point. Finally, spatio-temporal modelling of neighbourhood relations of the PS points is carried out using local geometric patches which are approximated with a mathematical model, such as, e.g., hierarchical B-Splines. Subsequently, the quality of SAR data from temporal and spatial neighbourhood relations is checked. Having an appropriate spatio-temporal quality model of the PS data, a deformation analysis is performed for areas of interest in the city of Hamburg. In the end, the results of the deformation analysis are compared with the BodenBewegungsdienst Deutschland (Ground Motion Service Germany) provided by the Federal Institute for Geosciences and Natural Resources (BGR), Germany.
Keywords
- Persistent Scatterer Interferometry (PSI), spatio-temporal, quality model, classification, robust parameter estimation, deformation analysis
Sustainable Development Goals
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
In: Journal of Applied Geodesy, Vol. 17, No. 2, 25.04.2023, p. 119-131.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - On the Quality Checking of Persistent Scatterer Interferometry by spatial-temporal modelling
AU - Omidalizarandi, Mohammad
AU - Mohammadivojdan, Bahareh
AU - Alkhatib, Hamza
AU - Paffenholz, Jens-André
AU - Neumann, Ingo
PY - 2023/4/25
Y1 - 2023/4/25
N2 - Today, rapid growth in infrastructure development and urbanization process increases the attention for accurate deformation monitoring on a relatively large-scale. Furthermore, such deformation monitoring is of great importance in the assessment and management of natural hazard processes like landslides, earthquakes, and floods. In this study, the Persistent Scatterer Interferometry (PSI) technique is applied using open-source synthetic aperture radar (SAR) data from the satellite Sentinel-1. It allows point-wise deformation monitoringbased on time series analysis of specific points. It also enables performing spatio-temporal area-based deformation monitoring. Currently, these data do not have a sophisticated quality assurance process to judge the significance of deformations. To obtain different quality classes of the Persistent Scatterer (PS) data points, the first step is to classify them into buildings and ground types using LoD2 building models. Next, time series analysis of the PS points is performed to model systematic and random errors. It allows estimation of the offset and the deformation rate for each point. Finally, spatio-temporal modelling of neighbourhood relations of the PS points is carried out using local geometric patches which are approximated with a mathematical model, such as, e.g., hierarchical B-Splines. Subsequently, the quality of SAR data from temporal and spatial neighbourhood relations is checked. Having an appropriate spatio-temporal quality model of the PS data, a deformation analysis is performed for areas of interest in the city of Hamburg. In the end, the results of the deformation analysis are compared with the BodenBewegungsdienst Deutschland (Ground Motion Service Germany) provided by the Federal Institute for Geosciences and Natural Resources (BGR), Germany.
AB - Today, rapid growth in infrastructure development and urbanization process increases the attention for accurate deformation monitoring on a relatively large-scale. Furthermore, such deformation monitoring is of great importance in the assessment and management of natural hazard processes like landslides, earthquakes, and floods. In this study, the Persistent Scatterer Interferometry (PSI) technique is applied using open-source synthetic aperture radar (SAR) data from the satellite Sentinel-1. It allows point-wise deformation monitoringbased on time series analysis of specific points. It also enables performing spatio-temporal area-based deformation monitoring. Currently, these data do not have a sophisticated quality assurance process to judge the significance of deformations. To obtain different quality classes of the Persistent Scatterer (PS) data points, the first step is to classify them into buildings and ground types using LoD2 building models. Next, time series analysis of the PS points is performed to model systematic and random errors. It allows estimation of the offset and the deformation rate for each point. Finally, spatio-temporal modelling of neighbourhood relations of the PS points is carried out using local geometric patches which are approximated with a mathematical model, such as, e.g., hierarchical B-Splines. Subsequently, the quality of SAR data from temporal and spatial neighbourhood relations is checked. Having an appropriate spatio-temporal quality model of the PS data, a deformation analysis is performed for areas of interest in the city of Hamburg. In the end, the results of the deformation analysis are compared with the BodenBewegungsdienst Deutschland (Ground Motion Service Germany) provided by the Federal Institute for Geosciences and Natural Resources (BGR), Germany.
KW - Persistent Scatterer Interferometry (PSI)
KW - spatio-temporal
KW - quality model
KW - classification
KW - robust parameter estimation
KW - deformation analysis
UR - http://www.scopus.com/inward/record.url?scp=85149311375&partnerID=8YFLogxK
U2 - 10.1515/jag-2022-0043
DO - 10.1515/jag-2022-0043
M3 - Article
VL - 17
SP - 119
EP - 131
JO - Journal of Applied Geodesy
JF - Journal of Applied Geodesy
SN - 1862-9016
IS - 2
ER -