Articles | Volume 17, issue 7
https://doi.org/10.5194/essd-17-3293-2025
© Author(s) 2025. 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-17-3293-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
10 Jul 2025
Data description paper |
| 10 Jul 2025
| 10 Jul 2025
Remote sensing of young leaf photosynthetic capacity in tropical and subtropical evergreen broadleaved forests
Xueqin Yang
Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 101408, China
Qingling Sun
Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China
Liusheng Han
CORRESPONDING AUTHOR
School of Civil Engineering and Geomatics, Shandong University of Technology, Zibo 255000, China
Jie Tian
Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China
Wenping Yuan
College of Urban and Environmental Sciences, School of Urban Planning and Design, Peking University, Beijing 100871, China
Liyang Liu
Laboratoire des Sciences du Climat et de l'Environnement, IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
Wei Zheng
Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China
Mei Wang
Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China
Yunpeng Wang
Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 101408, China
Xiuzhi Chen
CORRESPONDING AUTHOR
Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China
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Short summary
Understanding how leaves absorb carbon from the atmosphere is essential for predicting changes in global forests. Young leaves play a key role in this process, but their efficiency has been difficult to measure at large scales. Using satellite data, we developed a new method to track the seasonal patterns of young leaves’ photosynthetic capacity from 2001 to 2018. Our dataset helps scientists better understand forest growth and how ecosystems respond to climate change.
Understanding how leaves absorb carbon from the atmosphere is essential for predicting changes...
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