Object oriented data analysis of surface motion time series in peatland landscapes

Mitchell, Emily G; Dryden, Ian L; Fallaize, Christopher J; Andersen, Roxane; Bradley, Andrew V; Large, David J; Sowter, Andrew

Abstract

Peatlands account for 10% of UK land area, 80% of which are degraded to some degree, emitting carbon at a similar magnitude to oil refineries or landfill sites. A lack of tools for rapid and reliable assessment of peatland condition has limited monitoring of vast areas of peatland and prevented targeting areas urgently needing action to halt further degradation. Measured using interferometric synthetic aperture radar (InSAR), peatland surface motion is highly indicative of peatland condition, largely driven by the eco-hydrological change in the peatland causing swelling and shrinking of the peat substrate. The computational intensity of recent methods using InSAR time series to capture the annual functional structure of peatland surface motion becomes increasingly challenging as the sample size increases. Instead, we utilize the behaviour of the entire peatland surface motion time series using object oriented data analysis to assess peatland condition. Bayesian cluster analysis based on the functional structure of the surface motion time series finds areas indicative of soft/wet peatlands, drier/shrubby peatlands and thin/modified peatlands. The posterior distribution of the assigned peatland types enables the scale of peatland degradation to be assessed, which will guide future cost-effective decisions for peatland restoration

Citation

Mitchell, E. G., Dryden, I. L., Fallaize, C. J., Andersen, R., Bradley, A. V., Large, D. J., & Sowter, A. (2025). Object oriented data analysis of surface motion time series in peatland landscapes. Journal of the Royal Statistical Society: Series C, 74(2), 406-428. https://doi.org/10.1093/jrsssc/qlae060

• Journal Article Type: Article
• Acceptance Date: Sep 28, 2024
• Online Publication Date: Nov 20, 2024
• Publication Date: 2025-03
• Deposit Date: Oct 2, 2024
• Publicly Available Date: Nov 21, 2025
• Journal: Journal of the Royal Statistical Society Series C: Applied Statistics
• Print ISSN: 0035-9254
• Electronic ISSN: 1467-9876
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 74
• Issue: 2
• Pages: 406-428
• DOI: https://doi.org/10.1093/jrsssc/qlae060
• Keywords: InSAR, peatland condition mapping, satellite, spatial, square root velocity function, time series, warping
• Public URL: https://nottingham-repository.worktribe.com/output/40283675
• Publisher URL: https://academic.oup.com/jrsssc/article/74/2/406/7905504