Peng et al. (2026) Large-scale high-resolution coastal subsidence mapping in eastern China with Sentinel-1 and Sentinel-2: Heterogeneous patterns and primary drivers

Identification

• Journal: International Journal of Applied Earth Observation and Geoinformation
• Year: 2026
• Date: 2026-01-06
• Authors: Li Peng, Jianbo Bai, Lin Shen, Wei Tang, C. W. Liang, Bin Zhao, Zhenhong LI, Houjie Wang
• DOI: 10.1016/j.jag.2025.105047

Research Groups

• Institute of Estuarine and Coastal Zone, College of Marine Geosciences, Key Laboratory of Submarine Geosciences and Prospecting Technology, Ministry of Education, Ocean University of China, Qingdao, China
• Laboratory for Marine Geology, Qingdao Marine Science and Technology Center, Qingdao, China
• Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, USA
• College of Geoscience and Surveying Engineering, University of Mining and Technology, Beijing, China
• Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing, China
• Key Laboratory of Earthquake Geodesy, Institute of Seismology, China Earthquake Administration, Wuhan, China
• College of Geological Engineering and Geomatics, Chang’an University, Xi’an, China

Short Summary

This study mapped large-scale, high-resolution coastal subsidence in eastern China (Shandong and Jiangsu provinces) from 2017 to 2024 using TS-InSAR and Sentinel-1 data. It revealed extensive heterogeneous subsidence funnels, primarily driven by anthropogenic factors like brine extraction, groundwater pumping, and land reclamation.

Objective

• To comprehensively detect and quantify large-scale coastal subsidence patterns and their primary drivers in eastern China (Shandong and Jiangsu provinces).
• To develop a multi-frame mosaicking method for spatially consistent InSAR observations over land-sea transition areas.
• To characterize subsidence patterns and analyze their spatiotemporal distribution and correlation with underlying drivers, including groundwater levels.

Study Configuration

• Spatial Scale: Coastal regions of Shandong and Jiangsu provinces, eastern China, with deformation maps at 90 m resolution. Analysis focused on a coastal buffer area extending 100 km landward from the shore.
• Temporal Scale: Sentinel-1 data from March 2017 to December 2023. Groundwater level data from 2018 to 2021. GNSS data from 2010 to 2023.

Methodology and Data

• Models used: Time Series Interferometric Synthetic Aperture Radar (TS-InSAR), Small Baseline Subset (SBAS) time series analysis, Principal Component Analysis (PCA), novel multi-frame mosaicking method, InSAR Scientific Computing Environment (ISCE), Miami INsar Time-series software in PYthon (MintPy), statistical-cost network-flow algorithm for phase unwrapping (SNAPHU), generic atmospheric correction online service (GACOS).
• Data sources: Sentinel-1 (Single-Look-Complex, Interferometric Wide Swath mode, ascending orbit, 2017–2023), Sentinel-2 (multispectral imagery, 10 m spatial resolution), GNSS data (9 continuous stations from Crustal Movement Observation Network of China, 2010–2023), groundwater level measurements (China Geological Environment Monitoring Groundwater Level Yearbook, 2018–2021), NASADEM (30 m, for topographic phase removal), Landsat-derived annual land use land cover (LULC) product of China (30 m), 1:5,000,000 geologic chronogram of surface outcrops (United States Geological Survey).

Main Results

• Generated 90 m resolution TS-InSAR vertical deformation rate maps for the coastal regions of Shandong and Jiangsu provinces from 2017 to 2023.
• Developed a novel multi-frame mosaicking method to achieve spatially consistent InSAR observations over land-sea transition areas.
• Uncovered extensive coastal subsidence in northeastern Shandong and eastern Jiangsu, highlighting several rapid-subsidence funnels with rates exceeding 50 mm/yr for the first time.
• The maximum subsidence rate recorded was 344 mm/yr in the Yellow River Delta (YRD).
• Regions experiencing annual average subsidence rates greater than 20 mm/yr spanned 23,653 km², accounting for 15.6 % of the total study area.
• Anthropogenic factors were identified as the dominant drivers of coastal subsidence, with four distinct mechanisms:
  1. Brine extraction for salt production and aquaculture (e.g., Dongying City, Guangrao County).
  2. Excessive freshwater withdrawal for agricultural irrigation and industrial use (e.g., Guangrao County).
  3. Groundwater depletion for intensive greenhouse aquaculture (e.g., Yancheng City, with maximum annual rates reaching 630 mm/yr in some periods).
  4. Land reclamation for industrial infrastructure development (e.g., Longkou Port and Yulong Island in Yantai City).
• Most subsidence funnels exhibited deformation patterns predominantly controlled by a single dominant factor, as indicated by Principal Component 1 (PC1) variance explanation ratios exceeding 85.9 %.
• A strong correlation was observed between groundwater level fluctuations and coastal subsidence.
• Weak uplift phenomena were detected in newly formed land areas of river estuaries, silty salt marshes, and tidal flats, attributed to rapid sediment deposition.
• The root mean square (RMS) error between InSAR and GNSS vertical deformation rates was 1.3 mm/yr. The correlation coefficient between ascending and descending Sentinel-1 results was 0.97, with a mean difference of 1.0 mm/yr and a standard deviation of 6.9 mm/yr.

Contributions

• Provides the first comprehensive, large-scale, and high-resolution (90 m) mapping of coastal subsidence in eastern China (Shandong and Jiangsu provinces) using TS-InSAR.
• Introduces a novel multi-frame mosaicking method specifically designed for coastal areas, improving spatial consistency of InSAR observations.
• Identifies and quantifies rapid-subsidence funnels exceeding 50 mm/yr in eastern China for the first time.
• Offers a detailed analysis of heterogeneous subsidence patterns and their primary anthropogenic drivers, integrating satellite imagery, time series data, and in-situ measurements.
• Enhances the understanding of coastal subsidence risks and provides critical guidance for monitoring, disaster management, and protecting vulnerable coastal communities.
• Establishes a robust methodological framework for future research in large-scale coastal deformation monitoring.

Funding

• National Natural Science Foundation of China (No. 41806108; 42041005-4)
• Shandong Provincial Natural Science Foundation (No. ZR2024MD061)

Citation

@article{Peng2026Largescale,
  author = {Peng, Li and Bai, Jianbo and Shen, Lin and Tang, Wei and Liang, C. W. and Zhao, Bin and LI, Zhenhong and Wang, Houjie},
  title = {Large-scale high-resolution coastal subsidence mapping in eastern China with Sentinel-1 and Sentinel-2: Heterogeneous patterns and primary drivers},
  journal = {International Journal of Applied Earth Observation and Geoinformation},
  year = {2026},
  doi = {10.1016/j.jag.2025.105047},
  url = {https://doi.org/10.1016/j.jag.2025.105047}
}