Ground Motion Monitoring System of InSAR.Hungary: Results and Validation Findings
This study presents the development and validation of the nationwide ground motion monitoring system of InSAR.Hungary, which is designed to produce deformation monitoring products harmonized with the European Ground Motion Service. The proposed workflow integrates PSI results with GNSS-derived deformation models within a consistent framework. As a methodological contribution, it introduces an optimization-based spatial reference point selection method, which combines kernel density estimation with global optimization, and its extended formulation permitting subsequent utilization of a virtual reference. In addition, a simplified calibration strategy is also implemented, reducing the calibration of InSAR with GNSS data to a superimposing step, under the assumption that large-scale deformation components are introduced only by GNSS to the calibrated results. The system is validated through cross-comparisons, first against the European Ground Motion Service. The results reveal low-amplitude, spatially heterogeneous large-scale residual patterns between the products, which are potentially attributable to differences in the handling of long-wavelength phase and deformation components between the models. After accounting for these effects, the residual differences exhibit no significant bias and remain consistent with random spatial variability, indicating statistical agreement between the models. This finding is also supported by the outcome of the cross-comparison of InSAR.Hungary and observed GNSS-based deformation measurements. These findings confirm the reliability of the proposed workflow and establish InSAR.Hungary as a consistent framework for wide-area ground motion monitoring with practical applicability in geodetic and operational contexts.
Authors
- Bálint Magyar (ORCID: https://orcid.org/0000-0002-2464-6805)
Institutions
- Budapest University of Technology and Economics (HU)
- Department of Geodesy, Remote Sensing and Land Offices (HU)
Publication Details
- Journal
- Remote Sensing
- Published
- 2026-07-27
- DOI
- https://doi.org/10.3390/rs18152466
- Primary Topic
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Budapesti Műszaki és Gazdaságtudományi Egyetem
- National Research, Development and Innovation Office