Articles | Volume 18, issue 1
https://doi.org/10.5194/essd-18-55-2026
© Author(s) 2026. 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-18-55-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
05 Jan 2026
Data description paper |
| 05 Jan 2026
| 05 Jan 2026
Development of the long-term harmonized multi-satellite SIF (LHSIF) dataset at 0.05° resolution (1995–2024)
Chu Zou
State Key Laboratory of Efficient Utilization of Arable Land in Northern China, National Hulunber Grassland Ecosystem Observation and Research Station, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
Shanshan Du
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
Xinjie Liu
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
University of Chinese Academy of Sciences, Beijing 100049, China
International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
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Short summary
Understanding plant sunlight absorption is crucial for tracking global ecosystem health. We developed a 1995–2024 dataset that enhances satellite-based plant activity measurements by resolving data inconsistencies and improving resolution. Using advanced modeling, we harmonized signals from multiple satellites, cutting errors by 49 %. This offers clearer global photosynthesis trends, aiding climate research and vegetation monitoring.
Understanding plant sunlight absorption is crucial for tracking global ecosystem health. We...
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