Zhao et al. (2026) A multi-pass InSAR analysis of the estuarine alluvial Chongming Island ground displacements with implications on flood risk

Identification

• Journal: International Journal of Applied Earth Observation and Geoinformation
• Year: 2026
• Date: 2026-01-06
• Authors: Qing Zhao, Lei Zhou, Yifei Zhang, Antonio Pepe, Chengfang Yao, Jingjing Wang, Yuanzhi Yao
• DOI: 10.1016/j.jag.2025.105057

Research Groups

• Key Laboratory of Geographical Information Science, Ministry of Education, East China Normal University, Shanghai 200062, China
• School of Geographic Sciences, East China Normal University, Shanghai 200241, China
• Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China
• National Research Council of Italy (CNR), Institute for the Electromagnetic Sensing of the Environment, 328 Diocleziano, 80124 Napoli, Italy

Short Summary

This study investigates long-term ground deformation on Chongming Island from 2012 to 2023 using multi-pass InSAR, revealing significant subsidence in the eastern region exceeding 20 mm/year. It then simulates future coastal flood risk under combined effects of this subsidence, sea level rise, and storm surges, predicting over 50% island inundation by 2042 in worst-case scenarios.

Objective

• To retrieve the Chongming Island ground displacement time series from 2012 to 2023 and analyze the impact of accelerated Sea Level Rise (SLR) and ground subsidence on coastal flood risk, simulating future inundation scenarios.

Study Configuration

• Spatial Scale: Chongming Island, Shanghai, China (Yangtze River Estuary).
• Temporal Scale: Ground deformation monitored from January 2012 to October 2023; flood risk simulated for 2018, 2030, and 2042.

Methodology and Data

• Models used:
  • Small BAseline Subset (SBAS) algorithm for 1-D Line Of Sight (LOS) ground deformation.
  • Singular Value Decomposition (SVD) for combining multi-satellite InSAR time series.
  • Least Squares (LS) method for Digital Elevation Model (DEM) error estimation.
  • LISFLOOD-FP 2-D hydrodynamic model for flood simulation.
  • Random Forest machine learning algorithm for land cover classification.
• Data sources:
  • Satellite: RADARSAT-2 (44 Wide Mode images, descending, VV polarization, 2012-2016), Sentinel-1A (426 TOPS mode images, ascending, VH polarization, 2016-2023), Sentinel-2A (for land cover mapping), Landsat-8 (for location map).
  • Observation/Reanalysis: ASTER Digital Elevation Model (DEM) (30 m resolution), Global Tide and Surge Reanalysis (GTSR) datasets (100-year return period extreme sea levels), SinoLC-1 (1-meter resolution national-scale land cover map).
  • Ancillary: 2023 China Sea Level Bulletin for SLR predictions.

Main Results

• The eastern region of Chongming Island experienced significant ground subsidence from 2012 to 2023, with a maximum amplitude exceeding 20 mm/year.
• The subsidence rate in the eastern island is at least 2.5 times greater than the concurrent sea level rise (SLR) rate (3.2 mm/year for the East China Sea).
• 90% of high-coherent InSAR points had a Root Mean Square Error (RMSE) smaller than 5 mm, and 80% had an R² higher than 0.6, indicating a predominantly linear deformation trend.
• Under simulated worst-case scenarios (seawall failures, combined with subsidence and SLR), the total flood inundation area is estimated to exceed 50% of the island by 2042.
• Specifically, the failure of seawall segment 8 could lead to an inundation area of 291.25 km² by 2042.
• Coastal flood inundation areas significantly expand over time due to relative SLR: 392.83 km² in 2018, 506.20 km² in 2030, and 631.32 km² in 2042 (total for all seawall failures).
• Almost all salt marsh vegetation in Chongming Dongtan Nature Reserve (17.61 km², 14.68% of the reserve) would be flooded by 2030 under seawall failure scenarios.
• Inundated areas for traffic routes, tree cover, cropland, and buildings are projected to increase significantly by 2042.

Contributions

• Provides the first long-term (2012-2023) and high-resolution ground deformation time series for Chongming Island using a multi-pass InSAR analysis combining RADARSAT-2 and Sentinel-1A data.
• Quantifies the combined impact of local ground subsidence, sea level rise, and storm surges on coastal flood risk for Chongming Island, projecting future scenarios up to 2042.
• Integrates InSAR-derived ground deformation with a 2-D hydrodynamic model (LISFLOOD-FP) and an updated DEM to simulate detailed inundation maps under various seawall failure scenarios.
• Highlights the critical vulnerability of the eastern and northern seawalls and the significant threat to the Chongming Dongtan Nature Reserve's salt marsh vegetation due to relative sea level rise.

Funding

• NSFC [# 41801337]
• Research Grant of the Science and Technology Commission of Shanghai Municipality [project 18ZR1410800]
• ECNU High-end Foreign Expert Project (G2022137009L)
• Fundamental Research Funds for the Central Universities of China
• Dragon 5 ESA project ID 58351
• Dragon 6 project ID 95316

Citation

@article{Zhao2026multipass,
  author = {Zhao, Qing and Zhou, Lei and Zhang, Yifei and Pepe, Antonio and Yao, Chengfang and Wang, Jingjing and Yao, Yuanzhi},
  title = {A multi-pass InSAR analysis of the estuarine alluvial Chongming Island ground displacements with implications on flood risk},
  journal = {International Journal of Applied Earth Observation and Geoinformation},
  year = {2026},
  doi = {10.1016/j.jag.2025.105057},
  url = {https://doi.org/10.1016/j.jag.2025.105057}
}