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Open AccessArticle

Upscaling Northern Peatland CO2 Fluxes Using Satellite Remote Sensing Data

1
Department of Physical Geography and Ecosystem Science, Lund University, 223 62 Lund, Sweden
2
Centre for Environmental and Climate Science, Lund University, 223 62 Lund, Sweden
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Finnish Meteorological Institute, Erik Palménin Aukio 1, 00560 Helsinki, Finland
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Department of Earth Sciences, University of Gothenburg, 405 30 Gothenburg, Sweden
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Institute for Atmospheric and Earth System Research (INAR)/Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland
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Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, 901 83 Umeå, Sweden
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School of Forest Sciences, University of Eastern Finland, 80101 Joensuu, Finland
*
Author to whom correspondence should be addressed.
Academic Editors: Bassil El Masri and Jingfeng Xiao
Remote Sens. 2021, 13(4), 818; https://doi.org/10.3390/rs13040818
Received: 15 January 2021 / Revised: 9 February 2021 / Accepted: 20 February 2021 / Published: 23 February 2021
(This article belongs to the Special Issue Remote Sensing of Carbon Fluxes and Stocks)
Peatlands play an important role in the global carbon cycle as they contain a large soil carbon stock. However, current climate change could potentially shift peatlands from being carbon sinks to carbon sources. Remote sensing methods provide an opportunity to monitor carbon dioxide (CO2) exchange in peatland ecosystems at large scales under these changing conditions. In this study, we developed empirical models of the CO2 balance (net ecosystem exchange, NEE), gross primary production (GPP), and ecosystem respiration (ER) that could be used for upscaling CO2 fluxes with remotely sensed data. Two to three years of eddy covariance (EC) data from five peatlands in Sweden and Finland were compared to modelled NEE, GPP and ER based on vegetation indices from 10 m resolution Sentinel-2 MSI and land surface temperature from 1 km resolution MODIS data. To ensure a precise match between the EC data and the Sentinel-2 observations, a footprint model was applied to derive footprint-weighted daily means of the vegetation indices. Average model parameters for all sites were acquired with a leave-one-out-cross-validation procedure. Both the GPP and the ER models gave high agreement with the EC-derived fluxes (R2 = 0.70 and 0.56, NRMSE = 14% and 15%, respectively). The performance of the NEE model was weaker (average R2 = 0.36 and NRMSE = 13%). Our findings demonstrate that using optical and thermal satellite sensor data is a feasible method for upscaling the GPP and ER of northern boreal peatlands, although further studies are needed to investigate the sources of the unexplained spatial and temporal variation of the CO2 fluxes. View Full-Text
Keywords: ecosystem respiration (ER); footprint analysis; gross primary production (GPP); net ecosystem exchange (NEE); peatland; Sentinel-2; upscaling ecosystem respiration (ER); footprint analysis; gross primary production (GPP); net ecosystem exchange (NEE); peatland; Sentinel-2; upscaling
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MDPI and ACS Style

Junttila, S.; Kelly, J.; Kljun, N.; Aurela, M.; Klemedtsson, L.; Lohila, A.; Nilsson, M.B.; Rinne, J.; Tuittila, E.-S.; Vestin, P.; Weslien, P.; Eklundh, L. Upscaling Northern Peatland CO2 Fluxes Using Satellite Remote Sensing Data. Remote Sens. 2021, 13, 818. https://doi.org/10.3390/rs13040818

AMA Style

Junttila S, Kelly J, Kljun N, Aurela M, Klemedtsson L, Lohila A, Nilsson MB, Rinne J, Tuittila E-S, Vestin P, Weslien P, Eklundh L. Upscaling Northern Peatland CO2 Fluxes Using Satellite Remote Sensing Data. Remote Sensing. 2021; 13(4):818. https://doi.org/10.3390/rs13040818

Chicago/Turabian Style

Junttila, Sofia; Kelly, Julia; Kljun, Natascha; Aurela, Mika; Klemedtsson, Leif; Lohila, Annalea; Nilsson, Mats B.; Rinne, Janne; Tuittila, Eeva-Stiina; Vestin, Patrik; Weslien, Per; Eklundh, Lars. 2021. "Upscaling Northern Peatland CO2 Fluxes Using Satellite Remote Sensing Data" Remote Sens. 13, no. 4: 818. https://doi.org/10.3390/rs13040818

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