Zhang et al. (2025) 3D surface displacement modeling in Lorca, Spain, using dual-orbit MT-InSAR and multiple prior constraints

Identification

• Journal: International Journal of Applied Earth Observation and Geoinformation
• Year: 2025
• Date: 2025-11-20
• Authors: Yansuo Zhang, Yandong Gao, Sen Du, Shubi Zhang, Shijin Li, Wei Duan, Juan F. Prieto, José Fernández
• DOI: 10.1016/j.jag.2025.104967

Research Groups

• School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
• Instituto de Geociencias (CSIC, UCM), Madrid, Spain
• ETS de Ingenieros en Topografía, Geodesia y Cartografía, Universidad Politécnica de Madrid, Madrid, Spain
• Key Laboratory of Land Environment and Disaster Monitoring, MNR, China University of Mining and Technology, Xuzhou, China

Short Summary

This study proposes a novel method to model three-dimensional (3D) surface displacement by integrating dual-orbit Multi-Temporal InSAR (MT-InSAR) measurements with multiple prior deformation models. Applied in the Lorca basin, Spain, the approach successfully reconstructed high-precision 3D cumulative displacement fields, revealing significant horizontal movements and improving accuracy over conventional methods without requiring ground-based observations.

Objective

• To develop a novel approach for modeling 3D surface displacement by integrating dual-orbit Multi-Temporal InSAR measurements with multiple prior deformation models.
• To address the low sensitivity of InSAR in monitoring north–south displacement induced by groundwater extraction, providing new evidence to elucidate deformation mechanisms and inform sustainable groundwater management and geohazard mitigation.

Study Configuration

• Spatial Scale: Lorca basin, Alto Guadalentín Basin, southeastern Iberian Peninsula, Spain. The land subsidence area extends over 170 square kilometers, with an aquifer system spanning approximately 277 square kilometers.
• Temporal Scale: October 7, 2015, to March 24, 2017 (a period of 1 year, 5 months, and 17 days).

Methodology and Data

• Models used:
  • Multi-Temporal InSAR (MT-InSAR) processing using StaMPS/MTI, incorporating Lp-norm optimization compressive sensing (PU-LCS) for phase unwrapping.
  • Mogi point source model for volumetric contraction.
  • Okada dislocation model for elastic deformation from fault dislocations.
  • Force field theory (surface horizontal force equilibrium equation) with Green's functions for horizontal displacement reconstruction.
  • Bayesian estimation for model parameter inversion.
  • Weighted Least Squares (WLS) for final vertical displacement estimation.
• Data sources:
  • Sentinel-1A SAR imagery (C-band) from ascending (43 scenes) and descending (37 scenes) orbits.
  • Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) with a spatial resolution of 30 meters for topographic phase removal.
  • Generic Atmospheric Correction Online Service for InSAR (GACOS) products for atmospheric delay correction.
  • GNSS 3D displacement measurements from 22 stations (for validation purposes).

Main Results

• The study revealed a maximum cumulative subsidence of 121.5 mm and notable horizontal displacements with a peak magnitude of 18.6 mm, representing approximately 15% of the vertical displacement.
• The proposed approach achieved significant accuracy improvements compared to the GNSS-aided SMVCE method: 33.69 % for vertical, 51.33 % for east–west, and 43.91 % for north–south deformation components.
• The method eliminates the need for ground-based observations, reducing monitoring costs.
• The observed deformation pattern is an elliptical subsidence zone with its major axis oriented northeast-southwest, consistent with a typical subsidence funnel morphology.
• Horizontal displacement analysis showed a bidirectional compressive deformation pattern, with both flanks converging towards the central subsidence zone in both east–west and north–south directions.
• No significant signs of slip or extensional deformation were observed along the Alhama de Murcia Fault (AMF) and Palomares Fault during the monitoring period, suggesting faults primarily act as structural boundaries.

Contributions

• Introduction of a novel method for 3D surface displacement modeling by integrating dual-orbit MT-InSAR measurements with multiple prior deformation models (Mogi, Okada, and force field theory).
• First documented evidence of high-precision, high-resolution north–south displacement in the Lorca region using only InSAR data, overcoming the inherent low sensitivity of conventional multi-orbit InSAR to this component.
• Development of a radar-based, physically constrained approach for 3D surface deformation estimation that eliminates the dependence on external data sources like GNSS, thereby significantly lowering monitoring costs.
• Provides enhanced quantitative interpretation of surface deformation and critical evidence for elucidating geological processes and tectonic mechanisms in the Lorca region.

Funding

• National Natural Science Foundation of China [grant numbers 42271460, and 42404047]
• Natural Science Foundation of Jiangsu Province [grant number BK20241671]
• Spanish Agencia Estatal de Investigacion [grant number G2HOTSPOTS (PID2021-122142OB-I00)]
• Research project MADRIZ (PR14724-31939) funded by the Community of Madrid through the Multiannual Agreement for the regulation of the cooperation framework within the Regional System of Scientific Research and Technological Innovation, signed between the Community of Madrid and the UCM, within the framework of the 6th PRICIT (Regional Plan for Scientific Research and Technological Innovation for the 2022–2025 period).

Citation

@article{Zhang20253D,
  author = {Zhang, Yansuo and Gao, Yandong and Du, Sen and Zhang, Shubi and Li, Shijin and Duan, Wei and Prieto, Juan F. and Fernández, José},
  title = {3D surface displacement modeling in Lorca, Spain, using dual-orbit MT-InSAR and multiple prior constraints},
  journal = {International Journal of Applied Earth Observation and Geoinformation},
  year = {2025},
  doi = {10.1016/j.jag.2025.104967},
  url = {https://doi.org/10.1016/j.jag.2025.104967}
}