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South Patagonian peat bogs are little studied sources of methane (CH4). Since CH4 fluxes can vary greatly on a small scale of meters, high-quality maps are needed to accurately quantify CH4 fluxes from bogs. We used high-resolution color infrared (CIR) images captured by an Unmanned Aerial System (UAS) to investigate potential uncertainties in total ecosystem CH4 fluxes introduced by the classification of the surface area. An object-based approach was used to classify vegetation both on species and microform level. We achieved an overall Kappa Index of Agreement (KIA) of 0.90 for the species- and 0.83 for the microform-level classification, respectively. CH4 fluxes were determined by closed chamber measurements on four predominant microforms of the studied bog. Both classification approaches were employed to up-scale CH4 closed chamber measurements in a total area of around 1.8 hectares. Including proportions of the surface area where no chamber measurements were conducted, we estimated a potential uncertainty in ecosystem CH4 fluxes introduced by the classification of the surface area. This potential uncertainty ranged from 14.2 mg·m−2·day−1 to 26.8 mg·m−2·day−1. Our results show that a simple classification with only few classes potentially leads to pronounced bias in total ecosystem CH4 fluxes when plot-scale fluxes are up-scaled

remote sensing

High-Resolution Classification of South Patagonian Peat Bog Microforms Reveals Potential Gaps in Up-Scaled CH4 Fluxes by use of Unmanned Aerial System (UAS) and CIR Imagery