Articles | Volume 20, issue 12
https://doi.org/10.5194/bg-20-2265-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-20-2265-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Mapping of ESA's Climate Change Initiative land cover data to plant functional types for use in the CLASSIC land model
Climate Processes Section, Climate Research Division, Environment and
Climate Change Canada, Toronto, ON, Canada
Vivek K. Arora
Canadian Centre for Climate Modelling and Analysis, Climate Research
Division, Environment and Climate Change Canada, Victoria, BC, Canada
Paul Bartlett
Climate Processes Section, Climate Research Division, Environment and
Climate Change Canada, Toronto, ON, Canada
Climate Processes Section, Climate Research Division, Environment and
Climate Change Canada, Toronto, ON, Canada
Salvatore R. Curasi
Department of Geography and Environmental Studies, Carleton
University, Ottawa, ON, Canada
Climate Processes Section, Climate Research Division, Environment and
Climate Change Canada, Victoria, BC, Canada
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Cited
14 citations as recorded by crossref.
- Impact of topography and meteorological forcing on snow simulation in the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) L. Wang et al. https://doi.org/10.5194/gmd-18-6597-2025
- Implementing methane dynamics into the LPJmL6 model S. Schaphoff et al. https://doi.org/10.5194/gmd-19-7615-2026
- Temporal stability of a new 40-year daily AVHRR land surface temperature dataset for the pan-Arctic region S. Dupuis et al. https://doi.org/10.5194/tc-18-6027-2024
- Vegetation biogeography is a main source of uncertainty in modelling the land carbon cycle R. Zhao et al. https://doi.org/10.1038/s41467-025-67636-1
- Assessing the effect of land cover on ISBA snow water equivalent and land surface temperature simulations over Europe O. Rojas-Munoz et al. https://doi.org/10.5194/tc-20-4099-2026
- Global vegetation productivity has become less sensitive to drought in the first two decades of the 21st century M. Luo et al. https://doi.org/10.1016/j.jag.2024.104297
- A metrological framework for uncertainty evaluation in machine learning classification models S. Bilson et al. https://doi.org/10.1088/1681-7575/ae1bae
- Canada's Forests Are Shifting From a Recovery‐Driven Carbon Sink to a Disturbance‐Driven Carbon Source S. Curasi et al. https://doi.org/10.1111/gcb.70958
- Critical classification parameters linking species to Plant Functional Type in African ecosystems E. Akhabue et al. https://doi.org/10.1038/s41597-026-06728-z
- Anthropogenic activities and the influence of desertification processes on the water cycle and water use in the Aral Sea basin A. Kayiranga et al. https://doi.org/10.1016/j.ejrh.2023.101598
- Implementing a dynamic representation of fire and harvest including subgrid-scale heterogeneity in the tile-based land surface model CLASSIC v1.45 S. Curasi et al. https://doi.org/10.5194/gmd-17-2683-2024
- Global Sensitivity Analysis of the Future Land Carbon Sink R. Deepak et al. https://doi.org/10.1080/07055900.2025.2540430
- The impacts of modelling prescribed vs. dynamic land cover in a high-CO2 future scenario – greening of the Arctic and Amazonian dieback S. Kou-Giesbrecht et al. https://doi.org/10.5194/bg-21-3339-2024
- Contribution of oasis evapotranspiration to precipitation in arid Central Asia: Quantifying moisture recycling of mountain-oasis-desert systems H. Jie et al. https://doi.org/10.1016/j.jhydrol.2025.134624
14 citations as recorded by crossref.
- Impact of topography and meteorological forcing on snow simulation in the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) L. Wang et al. https://doi.org/10.5194/gmd-18-6597-2025
- Implementing methane dynamics into the LPJmL6 model S. Schaphoff et al. https://doi.org/10.5194/gmd-19-7615-2026
- Temporal stability of a new 40-year daily AVHRR land surface temperature dataset for the pan-Arctic region S. Dupuis et al. https://doi.org/10.5194/tc-18-6027-2024
- Vegetation biogeography is a main source of uncertainty in modelling the land carbon cycle R. Zhao et al. https://doi.org/10.1038/s41467-025-67636-1
- Assessing the effect of land cover on ISBA snow water equivalent and land surface temperature simulations over Europe O. Rojas-Munoz et al. https://doi.org/10.5194/tc-20-4099-2026
- Global vegetation productivity has become less sensitive to drought in the first two decades of the 21st century M. Luo et al. https://doi.org/10.1016/j.jag.2024.104297
- A metrological framework for uncertainty evaluation in machine learning classification models S. Bilson et al. https://doi.org/10.1088/1681-7575/ae1bae
- Canada's Forests Are Shifting From a Recovery‐Driven Carbon Sink to a Disturbance‐Driven Carbon Source S. Curasi et al. https://doi.org/10.1111/gcb.70958
- Critical classification parameters linking species to Plant Functional Type in African ecosystems E. Akhabue et al. https://doi.org/10.1038/s41597-026-06728-z
- Anthropogenic activities and the influence of desertification processes on the water cycle and water use in the Aral Sea basin A. Kayiranga et al. https://doi.org/10.1016/j.ejrh.2023.101598
- Implementing a dynamic representation of fire and harvest including subgrid-scale heterogeneity in the tile-based land surface model CLASSIC v1.45 S. Curasi et al. https://doi.org/10.5194/gmd-17-2683-2024
- Global Sensitivity Analysis of the Future Land Carbon Sink R. Deepak et al. https://doi.org/10.1080/07055900.2025.2540430
- The impacts of modelling prescribed vs. dynamic land cover in a high-CO2 future scenario – greening of the Arctic and Amazonian dieback S. Kou-Giesbrecht et al. https://doi.org/10.5194/bg-21-3339-2024
- Contribution of oasis evapotranspiration to precipitation in arid Central Asia: Quantifying moisture recycling of mountain-oasis-desert systems H. Jie et al. https://doi.org/10.1016/j.jhydrol.2025.134624
Saved (final revised paper)
Latest update: 02 Sep 2026
Short summary
Plant functional types (PFTs) are groups of plant species used to represent vegetation distribution in land surface models. There are large uncertainties associated with existing methods for mapping land cover datasets to PFTs. This study demonstrates how fine-resolution tree cover fraction and land cover datasets can be used to inform the PFT mapping process and reduce the uncertainties. The proposed largely objective method makes it easier to implement new land cover products in models.
Plant functional types (PFTs) are groups of plant species used to represent vegetation...
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