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

Lehmann, Jan R. K.; Münchberger, Wiebke; Knoth, Christian; Blodau, Christian; Nieberding, Felix; Prinz, Torsten; Pancotto, Verónica A.; Kleinebecker, Till

doi:10.3390/rs8030173

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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

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Institute of Landscape Ecology, University of Muenster, Heisenbergstr. 2, 48149 Muenster, Germany

Institute for Geoinformatics, University of Muenster, Heisenbergstr. 2, 48149 Muenster, Germany

Centro Austral de Investigaciones Científicas (CADIC-CONICET), B. Houssay 200, 9410 Ushuaia, Tierra del Fuego, Argentina

Authors to whom correspondence should be addressed.

^†

These authors contributed equally to this work.

Academic Editors: Richard L. Miller, Cheng-Chien Liu, Norman Kerle and Prasad S. Thenkabail

Remote Sens. 2016, 8(3), 173; https://doi.org/10.3390/rs8030173

Received: 13 November 2015 / Revised: 2 February 2016 / Accepted: 14 February 2016 / Published: 25 February 2016

(This article belongs to the Special Issue Remote Sensing of Biogeochemical Cycles)

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Abstract

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. View Full-Text

Keywords: closed chamber; object-based image analysis; OBIA classification; methane; peatland; RPAS; UAV

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MDPI and ACS Style

Lehmann, J.R.K.; Münchberger, W.; Knoth, C.; Blodau, C.; Nieberding, F.; Prinz, T.; Pancotto, V.A.; Kleinebecker, T. 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. Remote Sens. 2016, 8, 173. https://doi.org/10.3390/rs8030173

AMA Style

Lehmann JRK, Münchberger W, Knoth C, Blodau C, Nieberding F, Prinz T, Pancotto VA, Kleinebecker T. 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. Remote Sensing. 2016; 8(3):173. https://doi.org/10.3390/rs8030173

Chicago/Turabian Style

Lehmann, Jan R.K., Wiebke Münchberger, Christian Knoth, Christian Blodau, Felix Nieberding, Torsten Prinz, Verónica A. Pancotto, and Till Kleinebecker. 2016. "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" Remote Sensing 8, no. 3: 173. https://doi.org/10.3390/rs8030173

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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

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