Articles | Volume 14, issue 3
https://doi.org/10.5194/essd-14-1063-2022
© Author(s) 2022. 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-14-1063-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
10 Mar 2022
Data description paper |
| 10 Mar 2022
VODCA2GPP – a new, global, long-term (1988–2020) gross primary production dataset from microwave remote sensing
Department of Geodesy and Geoinformation, TU Wien, Wiedner Hauptstraße 8, 1040 Vienna, Austria
Irene Teubner
Department of Geodesy and Geoinformation, TU Wien, Wiedner Hauptstraße 8, 1040 Vienna, Austria
Zentralanstalt für Meteorologie und Geodynamik (ZAMG), Hohe Warte 38, 1190 Vienna, Austria
Leander Moesinger
Department of Geodesy and Geoinformation, TU Wien, Wiedner Hauptstraße 8, 1040 Vienna, Austria
Ruxandra-Maria Zotta
Department of Geodesy and Geoinformation, TU Wien, Wiedner Hauptstraße 8, 1040 Vienna, Austria
Matthias Forkel
Environmental Remote Sensing Group, Institute of Photogrammetry and Remote Sensing, Technische Universität Dresden, Helmholtzstraße 10, 01069 Dresden, Germany
Robin van der Schalie
VanderSat, Wilhelminastraat 43A, 2011 VK Haarlem, the Netherlands
Stephen Sitch
College of Life and Environmental Sciences, University of Exeter, Exeter, EX4 4QE, UK
Wouter Dorigo
Department of Geodesy and Geoinformation, TU Wien, Wiedner Hauptstraße 8, 1040 Vienna, Austria
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Cited
15 citations as recorded by crossref.
- Estimating Global GPP From the Plant Functional Type Perspective Using a Machine Learning Approach R. Guo et al. 10.1029/2022JG007100
- Association and driving factors of meteorological drought and agricultural drought in Ningxia, Northwest China P. Yang et al. 10.1016/j.atmosres.2023.106753
- Estimating leaf moisture content at global scale from passive microwave satellite observations of vegetation optical depth M. Forkel et al. 10.5194/hess-27-39-2023
- Assessment of Carbon Productivity Trends and Their Resilience to Drought Disturbances in the Middle East Based on Multi-Decadal Space-Based Datasets K. Alsafadi et al. 10.3390/rs14246237
- Vegetation growth due to CO2 fertilization is threatened by increasing vapor pressure deficit S. Li et al. 10.1016/j.jhydrol.2023.129292
- Assessing the sensitivity of multi-frequency passive microwave vegetation optical depth to vegetation properties L. Schmidt et al. 10.5194/bg-20-1027-2023
- Effects of Extreme Temperature and Precipitation Events on Daily CO2 Fluxes in the Tropics D. Gushchina et al. 10.3390/cli11060117
- Stability of the ecosystem gross primary productivity increasing in Chinese forestry ecological engineering area H. Liu et al. 10.1016/j.agee.2023.108636
- Tracking Global Patterns of Drought‐Induced Productivity Loss Along Severity Gradient Y. Wang et al. 10.1029/2021JG006753
- Improving the Gross Primary Production Estimate by Merging and Downscaling Based on Deep Learning J. Lu et al. 10.3390/f14061201
- Remote sensing of daily evapotranspiration and gross primary productivity of four forest ecosystems in East Asia using satellite multi-channel passive microwave measurements Y. Wang et al. 10.1016/j.agrformet.2023.109595
- Satellite‐Observed Vegetation Responses to Intraseasonal Precipitation Variability B. Harris et al. 10.1029/2022GL099635
- Declining resistance of vegetation productivity to droughts across global biomes Z. Liu et al. 10.1016/j.agrformet.2023.109602
- Progress of studies on satellite-based terrestrial vegetation production models in China W. Yuan et al. 10.1177/03091333221114864
- Effects of Vegetation Phenology on Ecosystem Water Use Efficiency in a Semiarid Region of Northern China Y. Zhang et al. 10.3389/fpls.2022.945582
13 citations as recorded by crossref.
- Estimating Global GPP From the Plant Functional Type Perspective Using a Machine Learning Approach R. Guo et al. 10.1029/2022JG007100
- Association and driving factors of meteorological drought and agricultural drought in Ningxia, Northwest China P. Yang et al. 10.1016/j.atmosres.2023.106753
- Estimating leaf moisture content at global scale from passive microwave satellite observations of vegetation optical depth M. Forkel et al. 10.5194/hess-27-39-2023
- Assessment of Carbon Productivity Trends and Their Resilience to Drought Disturbances in the Middle East Based on Multi-Decadal Space-Based Datasets K. Alsafadi et al. 10.3390/rs14246237
- Vegetation growth due to CO2 fertilization is threatened by increasing vapor pressure deficit S. Li et al. 10.1016/j.jhydrol.2023.129292
- Assessing the sensitivity of multi-frequency passive microwave vegetation optical depth to vegetation properties L. Schmidt et al. 10.5194/bg-20-1027-2023
- Effects of Extreme Temperature and Precipitation Events on Daily CO2 Fluxes in the Tropics D. Gushchina et al. 10.3390/cli11060117
- Stability of the ecosystem gross primary productivity increasing in Chinese forestry ecological engineering area H. Liu et al. 10.1016/j.agee.2023.108636
- Tracking Global Patterns of Drought‐Induced Productivity Loss Along Severity Gradient Y. Wang et al. 10.1029/2021JG006753
- Improving the Gross Primary Production Estimate by Merging and Downscaling Based on Deep Learning J. Lu et al. 10.3390/f14061201
- Remote sensing of daily evapotranspiration and gross primary productivity of four forest ecosystems in East Asia using satellite multi-channel passive microwave measurements Y. Wang et al. 10.1016/j.agrformet.2023.109595
- Satellite‐Observed Vegetation Responses to Intraseasonal Precipitation Variability B. Harris et al. 10.1029/2022GL099635
- Declining resistance of vegetation productivity to droughts across global biomes Z. Liu et al. 10.1016/j.agrformet.2023.109602
2 citations as recorded by crossref.
Discussed (final revised paper)
Latest update: 30 Sep 2023
Short summary
Gross primary production (GPP) describes the conversion of CO2 to carbohydrates and can be seen as a filter for our atmosphere of the primary greenhouse gas CO2. We developed VODCA2GPP, a GPP dataset that is based on vegetation optical depth from microwave remote sensing and temperature. Thus, it is mostly independent from existing GPP datasets and also available in regions with frequent cloud coverage. Analysis showed that VODCA2GPP is able to complement existing state-of-the-art GPP datasets.
Gross primary production (GPP) describes the conversion of CO2 to carbohydrates and can be seen...
