Assessing mire breathing patterns across Mecklenburg Vorpommern, Germany using a Sentinel-1 SBAS approach

Peatland condition is a key indicator of ecosystem integrity and carbon storage potential, making reliable monitoring of degradation processes essential at regional to national scales. Mire breathing—the cyclic surface motion driven by hydrological dynamics—serves as an important proxy for peatland degradation. Drained or degraded peatlands typically exhibit weak oscillatory behaviour combined with persistent subsidence trends, whereas near-natural peatlands show pronounced seasonal surface dynamics. Quantifying peatland subsidence therefore provides a structural indicator for assessing peatland condition and its implications for carbon storage dynamics and greenhouse gas emissions.

In this study, interferometric time-series analysis based on Sentinel-1 Synthetic Aperture Radar (SAR) data was applied to monitor large-scale peatland subsidence using a Small Baseline Subset (SBAS) approach implemented in MintPy. Additionally, hourly Radolan precipitation data were integrated to relate subsidence dynamics to hydrological forcing, and first in-situ measurements from extensometers were used to capture actual ground motion. The analysis covers peatlands across the federal state of Mecklenburg-Vorpommern (north-eastern Germany) for the period 2017–2024 and demonstrates a scalable monitoring framework applicable to national peatland inventories.

The results reveal pronounced spatiotemporal subsidence patterns across the study region. At three representative sites, mean subsidence rates range from −4.3 to −9.6 cm yr⁻¹ in line of sight (LOS). In addition, distinct site-specific mire breathing signals were identified, with seasonal amplitudes between 5 and 15 cm (LOS). The time series show enhanced subsidence during summer months and partial surface recovery during wetter periods, highlighting the strong control of hydrological conditions on peatland surface dynamics.

Overall, the findings demonstrate the capability of SBAS-based InSAR time-series analysis to capture both long-term subsidence trends and short-term oscillatory responses in peatlands. Comparison with in-situ extensometer measurements confirms the validity of the remote-sensing-derived deformation signals. This supports large-scale peatland mapping and monitoring efforts and provides a remote-sensing-based component relevant for greenhouse gas accounting and monitoring, reporting and verification (MRV) frameworks. Future work will focus on improving methodological robustness and validating the InSAR-derived deformation signals using in-situ subsidence measurements.

This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Project-ID 531801029 (TRR 410).