Articles | Volume 11, issue 7
https://doi.org/10.5194/bg-11-1961-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-11-1961-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
09 Apr 2014
Research article |
| 09 Apr 2014
A satellite data driven biophysical modeling approach for estimating northern peatland and tundra CO2 and CH4 fluxes
J. D. Watts
Flathead Lake Biological Station, The University of Montana, 32125 Bio Station Lane, Polson, MT, USA
Numerical Terradynamic Simulation Group, CHCB 428, 32 Campus Drive, The University of Montana, Missoula, MT, USA
J. S. Kimball
Flathead Lake Biological Station, The University of Montana, 32125 Bio Station Lane, Polson, MT, USA
Numerical Terradynamic Simulation Group, CHCB 428, 32 Campus Drive, The University of Montana, Missoula, MT, USA
F. J. W. Parmentier
Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 223 62, Lund, Sweden
Helmholtz Centre Potsdam – GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
Department of Geosciences and Geography; Department of Physics, P.O. Box 64, 00014 University of Helsinki, Finland
Department of Animal and Plant Science, University of Sheffield, Sheffield, UK
Department of Biology, San Diego State University, San Diego, CA, USA
W. Oechel
Department of Biology, San Diego State University, San Diego, CA, USA
T. Tagesson
Department of Geography and Geology, Copenhagen University, Øster Voldgade 10, 1350 Copenhagen, Denmark
M. Jackowicz-Korczyński
Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 223 62, Lund, Sweden
M. Aurela
Finnish Meteorological Institute, Climate Change Research, P.O. Box 503, 00101, Helsinki, Finland
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Cited
24 citations as recorded by crossref.
- Recent climatic changes and wetland expansion turned Tibet into a net CH4 source D. Wei & X. Wang https://doi.org/10.1007/s10584-017-2069-y
- Improving Permafrost Modeling by Assimilating Remotely Sensed Soil Moisture S. Zwieback et al. https://doi.org/10.1029/2018WR023247
- Remote sensing applications for monitoring restoration outcomes in boreal forestry-drained peatlands - Reviewed applications and future potential L. Ikkala et al. https://doi.org/10.1016/j.rse.2025.115093
- Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model Y. Wang et al. https://doi.org/10.1029/2019MS001771
- Comparing modeled and measured carbon dioxide data at five canadian peatlands revealed highly variable non-growing season fluxes E. Hettinga et al. https://doi.org/10.3389/fenvs.2026.1838949
- Multi-model ensemble successfully predicted atmospheric methane consumption in soils across the complex landscape M. Glagolev et al. https://doi.org/10.18822/edgcc625761
- Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems X. Xu et al. https://doi.org/10.5194/bg-13-3735-2016
- The missing pieces for better future predictions in subarctic ecosystems: A Torneträsk case study D. Pascual et al. https://doi.org/10.1007/s13280-020-01381-1
- Carbon uptake in Eurasian boreal forests dominates the high‐latitude net ecosystem carbon budget J. Watts et al. https://doi.org/10.1111/gcb.16553
- MATHEMATICAL MODELS OF METHANE CONSUMPTION BY SOILS: A REVIEW M. Glagolev et al. https://doi.org/10.18822/edgcc622937
- High-resolution mapping of peatland CO2 fluxes using drone multispectral images R. Walcker et al. https://doi.org/10.1016/j.ecoinf.2025.103060
- Soil Respiration Phenology Improves Modeled Phase of Terrestrial net Ecosystem Exchange in Northern Hemisphere K. Endsley et al. https://doi.org/10.1029/2021MS002804
- Statistical Machine Learning Methods and Remote Sensing for Sustainable Development Goals: A Review J. Holloway & K. Mengersen https://doi.org/10.3390/rs10091365
- Surface water inundation in the boreal-Arctic: potential impacts on regional methane emissions J. Watts et al. https://doi.org/10.1088/1748-9326/9/7/075001
- Progress in space-borne studies of permafrost for climate science: Towards a multi-ECV approach A. Trofaier et al. https://doi.org/10.1016/j.rse.2017.05.021
- Upscaling CO2 fluxes from agricultural drained lowland peatlands in England using remote sensing and machine learning A. Khan et al. https://doi.org/10.1016/j.rsase.2025.101728
- Estimation of foliar chlorophyll and nitrogen content in an ombrotrophic bog from hyperspectral data: Scaling from leaf to image M. Kalacska et al. https://doi.org/10.1016/j.rse.2015.08.012
- Causality constrained machine learning framework enhances the reliability and spatiotemporal generalization in ecosystem respiration estimation C. Zhao et al. https://doi.org/10.1016/j.agrformet.2025.110718
- Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties A. Virkkala et al. https://doi.org/10.1111/gcb.15659
- Remote Sensing of Environmental Changes in Cold Regions: Methods, Achievements and Challenges J. Du et al. https://doi.org/10.3390/rs11161952
- Temporal Variation of Ecosystem Scale Methane Emission From a Boreal Fen in Relation to Temperature, Water Table Position, and Carbon Dioxide Fluxes J. Rinne et al. https://doi.org/10.1029/2017GB005747
- An Overview of Remote Sensing Data Applications in Peatland Research Based on Works from the Period 2010–2021 S. Czapiewski & D. Szumińska https://doi.org/10.3390/land11010024
- Responses of peat carbon at different depths to simulated warming and oxidizing L. Liu et al. https://doi.org/10.1016/j.scitotenv.2015.11.149
- Using Stable Carbon Isotopes of Seasonal Ecosystem Respiration to Determine Permafrost Carbon Loss M. Mauritz et al. https://doi.org/10.1029/2018JG004619
24 citations as recorded by crossref.
- Recent climatic changes and wetland expansion turned Tibet into a net CH4 source D. Wei & X. Wang https://doi.org/10.1007/s10584-017-2069-y
- Improving Permafrost Modeling by Assimilating Remotely Sensed Soil Moisture S. Zwieback et al. https://doi.org/10.1029/2018WR023247
- Remote sensing applications for monitoring restoration outcomes in boreal forestry-drained peatlands - Reviewed applications and future potential L. Ikkala et al. https://doi.org/10.1016/j.rse.2025.115093
- Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model Y. Wang et al. https://doi.org/10.1029/2019MS001771
- Comparing modeled and measured carbon dioxide data at five canadian peatlands revealed highly variable non-growing season fluxes E. Hettinga et al. https://doi.org/10.3389/fenvs.2026.1838949
- Multi-model ensemble successfully predicted atmospheric methane consumption in soils across the complex landscape M. Glagolev et al. https://doi.org/10.18822/edgcc625761
- Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems X. Xu et al. https://doi.org/10.5194/bg-13-3735-2016
- The missing pieces for better future predictions in subarctic ecosystems: A Torneträsk case study D. Pascual et al. https://doi.org/10.1007/s13280-020-01381-1
- Carbon uptake in Eurasian boreal forests dominates the high‐latitude net ecosystem carbon budget J. Watts et al. https://doi.org/10.1111/gcb.16553
- MATHEMATICAL MODELS OF METHANE CONSUMPTION BY SOILS: A REVIEW M. Glagolev et al. https://doi.org/10.18822/edgcc622937
- High-resolution mapping of peatland CO2 fluxes using drone multispectral images R. Walcker et al. https://doi.org/10.1016/j.ecoinf.2025.103060
- Soil Respiration Phenology Improves Modeled Phase of Terrestrial net Ecosystem Exchange in Northern Hemisphere K. Endsley et al. https://doi.org/10.1029/2021MS002804
- Statistical Machine Learning Methods and Remote Sensing for Sustainable Development Goals: A Review J. Holloway & K. Mengersen https://doi.org/10.3390/rs10091365
- Surface water inundation in the boreal-Arctic: potential impacts on regional methane emissions J. Watts et al. https://doi.org/10.1088/1748-9326/9/7/075001
- Progress in space-borne studies of permafrost for climate science: Towards a multi-ECV approach A. Trofaier et al. https://doi.org/10.1016/j.rse.2017.05.021
- Upscaling CO2 fluxes from agricultural drained lowland peatlands in England using remote sensing and machine learning A. Khan et al. https://doi.org/10.1016/j.rsase.2025.101728
- Estimation of foliar chlorophyll and nitrogen content in an ombrotrophic bog from hyperspectral data: Scaling from leaf to image M. Kalacska et al. https://doi.org/10.1016/j.rse.2015.08.012
- Causality constrained machine learning framework enhances the reliability and spatiotemporal generalization in ecosystem respiration estimation C. Zhao et al. https://doi.org/10.1016/j.agrformet.2025.110718
- Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties A. Virkkala et al. https://doi.org/10.1111/gcb.15659
- Remote Sensing of Environmental Changes in Cold Regions: Methods, Achievements and Challenges J. Du et al. https://doi.org/10.3390/rs11161952
- Temporal Variation of Ecosystem Scale Methane Emission From a Boreal Fen in Relation to Temperature, Water Table Position, and Carbon Dioxide Fluxes J. Rinne et al. https://doi.org/10.1029/2017GB005747
- An Overview of Remote Sensing Data Applications in Peatland Research Based on Works from the Period 2010–2021 S. Czapiewski & D. Szumińska https://doi.org/10.3390/land11010024
- Responses of peat carbon at different depths to simulated warming and oxidizing L. Liu et al. https://doi.org/10.1016/j.scitotenv.2015.11.149
- Using Stable Carbon Isotopes of Seasonal Ecosystem Respiration to Determine Permafrost Carbon Loss M. Mauritz et al. https://doi.org/10.1029/2018JG004619
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