Articles | Volume 16, issue 1
https://doi.org/10.5194/bg-16-57-2019
© Author(s) 2019. 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-16-57-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Emergent relationships with respect to burned area in global satellite observations and fire-enabled vegetation models
Matthias Forkel
CORRESPONDING AUTHOR
Climate and Environmental Remote Sensing Group, Department of Geodesy and Geoinformation, Technische Universität Wien, Vienna, Austria
Niels Andela
Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Sandy P. Harrison
Department of Geography and Environmental Science, University of Reading, Reading, UK
Gitta Lasslop
Senckenberg Biodiversity and Climate Research Centre, Frankfurt am Main, Germany
Margreet van Marle
Deltares, Delft, the Netherlands
Emilio Chuvieco
Environmental Remote Sensing Research Group, Department of Geology, Geography and the Environment, Universidad de Alcalá, Alcalá de Henares, Spain
Wouter Dorigo
Climate and Environmental Remote Sensing Group, Department of Geodesy and Geoinformation, Technische Universität Wien, Vienna, Austria
Matthew Forrest
Senckenberg Biodiversity and Climate Research Centre, Frankfurt am Main, Germany
Stijn Hantson
Geospatial Data Solutions Center, University of California, Irvine, CA, USA
Angelika Heil
Department for Atmospheric Chemistry, Max Planck Institute for Chemistry, Mainz, Germany
International Center for Climate and Environmental Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Joe Melton
Climate Research Division, Environment Canada, Victoria, BC, Canada
Stephen Sitch
College of Life and Environmental Sciences, University of Exeter, Exeter, UK
Chao Yue
Laboratoire des Sciences du Climat et de l'Environnement, Gif-sur-Yvette, France
Almut Arneth
Atmospheric Environmental Research, Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
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- Progress and challenges in remotely sensed terrestrial carbon fluxes T. Wang et al. 10.1080/10095020.2024.2336599
- The interactive global fire module pyrE (v1.0) K. Mezuman et al. 10.5194/gmd-13-3091-2020
- Assessing anthropogenic influence on fire history during the Holocene in the Iberian Peninsula L. Sweeney et al. 10.1016/j.quascirev.2022.107562
- Towards understanding the environmental and climatic changes and its contribution to the spread of wildfires in Ghana using remote sensing tools and machine learning (Google Earth Engine) K. Dahan et al. 10.1080/17538947.2023.2197263
- Eco‐evolutionary optimality as a means to improve vegetation and land‐surface models S. Harrison et al. 10.1111/nph.17558
- Pyros: a raster–vector spatial simulation model for predicting wildland surface fire spread and growth D. Voltolina et al. 10.1071/WF22142
- Examining wildfire dynamics using ECOSTRESS data with machine learning approaches: the case of South‐Eastern Australia's black summer Y. Zhu et al. 10.1002/rse2.422
- Spatial distribution of tree species in mountain national parks depends on geomorphology and climate M. Dyderski & Ł. Pawlik 10.1016/j.foreco.2020.118366
- Advancements in remote sensing for active fire detection: A review of datasets and methods S. Yang et al. 10.1016/j.scitotenv.2024.173273
- Constraining modelled global vegetation dynamics and carbon turnover using multiple satellite observations M. Forkel et al. 10.1038/s41598-019-55187-7
- Observational evidence of wildfire-promoting soil moisture anomalies S. O et al. 10.1038/s41598-020-67530-4
- The Reading Palaeofire Database: an expanded global resource to document changes in fire regimes from sedimentary charcoal records S. Harrison et al. 10.5194/essd-14-1109-2022
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Latest update: 25 Dec 2024
Short summary
Weather, humans, and vegetation control the occurrence of fires. In this study we find that global fire–vegetation models underestimate the strong increase of burned area with higher previous-season plant productivity in comparison to satellite-derived relationships.
Weather, humans, and vegetation control the occurrence of fires. In this study we find that...
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