Articles | Volume 13, issue 10
https://doi.org/10.5194/essd-13-4881-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-4881-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Mapping global forest age from forest inventories, biomass and climate data
Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
Laboratory of Geo-Information Science and Remote Sensing, Wageningen University & Research, Wageningen, the Netherlands
Sujan Koirala
Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
Maurizio Santoro
Gamma Remote Sensing, Bern, Switzerland
Ulrich Weber
Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
Jacob Nelson
Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
Jonas Gütter
Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
Data Management and Analysis, Institute of Data Science, German Aerospace Center (DLR), Jena, Germany
Bruno Herault
Institut National Polytechnique Félix Houphouët-Boigny (INP-HB), Côte d'Ivoire
Research Unit Forests and Societies, CIRAD, University of Montpellier, Montpellier, France
Justin Kassi
Laboratoire de Botanique, UFR Biosciences, Université Félix Houphouët-Boigny, Abidjan, Côte d'Ivoire
Anny N'Guessan
Laboratoire de Botanique, UFR Biosciences, Université Félix Houphouët-Boigny, Abidjan, Côte d'Ivoire
Christopher Neigh
Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
Benjamin Poulter
Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
Tao Zhang
Department of Biology, University of Florida, Gainesville, Florida, USA
Department of Forest Resources, University of Minnesota, Minneapolis, Minnesota, USA
Nuno Carvalhais
CORRESPONDING AUTHOR
Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
Departamento de Ciências e Engenharia do Ambiente (DCEA), Faculdade de Ciências e Tecnologia (FCT), Universidade Nova de Lisboa, Lisbon, Portugal
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- Forestation at the right time with the right species can generate persistent carbon benefits in China H. Xu et al. 10.1073/pnas.2304988120
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- Canopy-Height and Stand-Age Estimation in Northeast China at Sub-Compartment Level Using Multi-Resource Remote Sensing Data X. Guan et al. 10.3390/rs15153738
- Assessing the potential of remote sensing-based models to predict old-growth forests on large spatiotemporal scales E. Lalechère et al. 10.1016/j.jenvman.2023.119865
- Maps with 1 km resolution reveal increases in above- and belowground forest biomass carbon pools in China over the past 20 years Y. Chen et al. 10.5194/essd-15-897-2023
- Forest Age Mapping Using Landsat Time-Series Stacks Data Based on Forest Disturbance and Empirical Relationships between Age and Height L. Tian et al. 10.3390/rs15112862
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- High-resolution forest age mapping based on forest height maps derived from GEDI and ICESat-2 space-borne lidar data X. Lin et al. 10.1016/j.agrformet.2023.109592
- Spatial database of planted forests in East Asia A. Abbasi et al. 10.1038/s41597-023-02383-w
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- Nitrogen addition delays the emergence of an aridity-induced threshold for plant biomass H. Li et al. 10.1093/nsr/nwad242
- Reforestation policies around 2000 in southern China led to forest densification and expansion in the 2010s X. Tong et al. 10.1038/s43247-023-00923-1
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- Biogeographic pattern of living vegetation carbon turnover time in mature forests across continents K. Yu et al. 10.1111/geb.13736
- Land cover and management effects on ecosystem resistance to drought stress C. Xiao et al. 10.5194/esd-14-1211-2023
- Mapping Annual Global Forest Gain From 1983 to 2021 With Landsat Imagery Z. Du et al. 10.1109/JSTARS.2023.3267796
- The significance of large old trees and tree cavities for forest carbon estimates M. Hauck et al. 10.1016/j.foreco.2023.121319
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Latest update: 28 Mar 2024
Short summary
Forest age can determine the capacity of a forest to uptake carbon from the atmosphere. Yet, a lack of global diagnostics that reflect the forest stage and associated disturbance regimes hampers the quantification of age-related differences in forest carbon dynamics. In this paper, we introduced a new global distribution of forest age inferred from forest inventory, remote sensing and climate data in support of a better understanding of the global dynamics in the forest water and carbon cycles.
Forest age can determine the capacity of a forest to uptake carbon from the atmosphere. Yet, a...
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