Assessing Subsidence in Remote Reclaimed Islands by Integrating PPP, Leveling, and InSAR
To address the urgent need for safety maintenance of remote reclaimed islands, we propose a novel monitoring framework integrating PPP, leveling, and InSAR technologies to comprehensively capture slow surface deformations across point, line, and area dimensions. This study also details the data interpretation methods and critical processing workflow, using Shandong Haiyang Junzi-Lianli island as a case study. The monitoring results revealed maximum annual displacements of 2 mm for PPP reference points, 5 mm elevation variations for leveling benchmarks, and an average InSAR deformation rate of −0.34 mm/yr with peak deformation reaching 18.60 mm/yr. Meanwhile, cross-validation was performed on the results obtained from these three different techniques. The discrepancy between the benchmark PPP observation and the InSAR measurement was 3.81 mm. For the common monitoring points, the differences between leveling and InSAR ranged from 0.57 mm to 5.41 mm. The deformation trends observed in PPP reference points, leveling benchmarks, and corresponding InSAR time-series data demonstrated good consistency, indicating overall stability of the reclamation island. The proposed methodology accurately identifies minute surface deformations at different spatial scales (point, linear, and areal) of the artificial island, overcoming the limitations of single-technique approaches, thus proving to be an effective means for subsidence assessment of offshore artificial island structures. This study advances the technical framework for reclaimed island stability monitoring, offering data and solutions to identify subsidence risks and enhance disaster prevention.
Authors
- Menghao Li (ORCID: https://orcid.org/0000-0001-7458-238X)
- Baoquan Cheng (ORCID: https://orcid.org/0000-0002-4179-6709)
- Deming Ma (ORCID: https://orcid.org/0000-0002-3246-8113)
- Yonggang Jia
- Yabin Wang (ORCID: https://orcid.org/0000-0002-7966-6117)
Institutions
- Harbin Engineering University (CN)
- Ministry of Natural Resources (CN)
- First Institute of Oceanography (CN)
- Ocean University of China (CN)
Publication Details
- Journal
- Remote Sensing
- Published
- 2025-11-02
- DOI
- https://doi.org/10.3390/rs17213628
- Primary Topic
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Shandong Province
- Ocean Public Welfare Scientific Research Project