Patil et al. (2026) Assessing peat surface motion using Interferometric Synthetic Aperture Radar (InSAR) in the Great Fen area of Cambridgeshire, UK

Identification

• Journal: Remote Sensing Applications Society and Environment
• Year: 2026
• Date: 2026-01-01
• Authors: Abhishek Patil, Abdou Khouakhi, N. T. Girkin, Ian Holman
• DOI: 10.1016/j.rsase.2026.101919

Research Groups

• Faculty of Engineering and Applied Sciences, Cranfield University, Bedford, UK
• School of Biosciences, University of Nottingham, Sutton Bonington, UK

Short Summary

This study utilized Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) data from 2015 to 2025 to monitor peat surface motion in the Great Fen, UK, quantifying subsidence rates and deriving deformation-based carbon flux proxies across different restoration stages. It revealed distinct subsidence patterns, with long-term conservation areas showing the lowest rates (0.48 cm/year) and later-restored farms exhibiting the highest (1.40 cm/year), demonstrating InSAR's effectiveness for assessing peatland restoration outcomes and carbon vulnerability.

Objective

• To evaluate the potential of SBAS-InSAR to detect and quantify surface motion in lowland peatlands and assess its reliability against independent ground-based survey data.
• To analyze peat surface deformation across multiple spatial scales (pixel, farm, and sub-region) and characterize seasonal deformation in relation to soil moisture and rainfall.
• To derive first-order, deformation-based proxies for peat carbon flux to support comparative assessment of restoration outcomes and inform sustainable land management.
• Principal hypothesis: Subsidence would be lowest in National Nature Reserves under long-term wet conservation management, followed by earlier-restored farms, and highest in later-restored farms.

Study Configuration

• Spatial Scale: The Great Fen area of Cambridgeshire, UK, encompassing approximately 34 square kilometers, with analysis conducted at pixel, farm, and sub-regional scales.
• Temporal Scale: Sentinel-1 InSAR data spanning 2015–2025 for surface motion analysis; seasonal analysis from 2016–2024; validation against ground-based peat-depth surveys from the 1980s and 2021–2022.

Methodology and Data

• Models used:
  • Interferometric Synthetic Aperture Radar (InSAR) with the Small Baseline Subset (SBAS) technique for time-series analysis.
  • Jet Propulsion Laboratory's InSAR Scientific Computing Environment (ISCE) for interferogram processing.
  • MintPy InSAR time-series software (Python) for SBAS time series analysis.
  • PyAPS3 package for tropospheric delay correction using ERA5 reanalysis data.
  • Ordinary Kriging for interpolating peat-depth rasters.
  • Equation (3): Cem/ab = A × Dv × BD × Corg for deformation-associated carbon flux estimation.
• Data sources:
  • Satellite: Sentinel-1A/B (S1) Single Look Complex (SLC) SAR data (2015–2025), acquired in Interferometric Wide (IW) swath mode on ascending (track 132) and descending (track 81) passes.
  • Topography: 30-meter Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM).
  • Reanalysis: ERA5 atmospheric reanalysis data.
  • Observation/Ground-based:
    • Three-month Standardised Precipitation Index (SPI-3) for the Great Ouse catchment (UKCEH Water Resources Portal).
    • Soil moisture data (volumetric water content at 5 cm and 50 cm depths) from the COSMOS-UK Fincham site.
    • Ground-based peat-depth surveys from the 1980s Lowland Peat Survey (Burton and Hodgson, 1987).
    • Recent field measurements (Jasper et al., 2022; Girkin et al., 2022) for validation.
    • Google Earth imagery (2008, 2014, 2020, 2025) for reference point stability.

Main Results

• The Great Fen region exhibited an average subsidence rate of 1.24 cm/year between 2016 and 2025.
• Spatially, the northern region showed the highest average subsidence (1.51 cm/year), followed by the central region (1.31 cm/year), and the southern region with the lowest rates (0.84 cm/year).
• Distinct subsidence patterns were observed based on restoration timing:
  • Later-restored farms (Region A) showed the highest average subsidence rate at 1.40 cm/year.
  • Earlier-restored farms (Region B) exhibited an average subsidence of 1.17 cm/year.
  • National Nature Reserves (Holme Fen and Woodwalton Fen), under long-term wet conservation management, recorded the lowest subsidence rates of 0.48 cm/year.
• Deformation-associated carbon flux proxies (using baseline parameters) were estimated as:
  • Later-restored farms (Region A): 17.37 tonnes CO2/hectare/year.
  • Earlier-restored farms (Region B): 14.50 tonnes CO2/hectare/year.
  • National Nature Reserves: 5.98 tonnes CO2/hectare/year.
• Seasonal fluctuations in peat surface motion were strongly correlated with soil moisture, particularly at 50 cm depth, and precipitation anomalies, indicating significant hydrological control.
• Comparison with ground-based peat loss surveys (1980s–2022) showed consistent spatial patterns of peat loss, validating the InSAR-derived deformation trends.

Contributions

• Demonstrated the effectiveness of InSAR as a high-resolution, cost-effective, and spatially continuous tool for monitoring lowland peatland physical dynamics (subsidence and seasonal motion) across farm to landscape scales.
• Provided quantitative evidence of distinct peat surface motion patterns directly linked to different restoration timelines and land management practices, highlighting the impact of timely interventions.
• Developed first-order, deformation-based proxies for peat carbon flux, offering a relative indicator of carbon vulnerability and mitigation potential across various restoration stages.
• Validated InSAR-derived seasonal surface dynamics against independent hydrological indicators (Standardised Precipitation Index and soil moisture), confirming the strong hydrological control on peat surface movement.
• Reinforced the reliability of satellite-based approaches by demonstrating alignment between InSAR-derived long-term subsidence patterns and historical ground-based peat depth surveys.
• Highlighted InSAR's practical utility for supporting national inventory reporting, validating peatland code restoration sites, quantifying public benefits of agri-environmental payments, and prioritizing conservation outcomes in peatland management.

Funding

• Access to SAR imagery provided by the Alaska Satellite Facility (ASF) Distributed Active Archive Center (DAAC).
• SAR time series processing supported by ASF Data Search Vortex and Open Science Lab platforms.
• Fieldwork support and site access provided by the Wildlife Trust for Bedfordshire, Cambridgeshire & Northamptonshire (WTBCN).

Citation

@article{Patil2026Assessing,
  author = {Patil, Abhishek and Khouakhi, Abdou and Girkin, N. T. and Holman, Ian},
  title = {Assessing peat surface motion using Interferometric Synthetic Aperture Radar (InSAR) in the Great Fen area of Cambridgeshire, UK},
  journal = {Remote Sensing Applications Society and Environment},
  year = {2026},
  doi = {10.1016/j.rsase.2026.101919},
  url = {https://doi.org/10.1016/j.rsase.2026.101919}
}