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New satellite dataset sheds light on plant growth on Earth

Gross primary production (GPP), the process by which plants convert carbon dioxide and sunlight into glucose and oxygen, constitutes the largest carbon flux on Earth. Accurate quantification of GEPs is crucial for understanding carbon budgets and their implications for climate change and land management policies. However, traditional methods of estimating global GPP are challenged by the complexity of integrating biophysical and biochemical processes at different scales. This challenge led to the development of the Comprehensive Mechanistic Light Response (GPP) (CMLR) dataset, and the details are in the article (DOI: 10.34133/remotesensing.0127) published in the Remote Sensing Journal on February 13, 2024.

This dataset exploits for the first time solar-induced chlorophyll fluorescence (SIF), a direct signal emitted by plants during photosynthesis, providing a more precise and direct measure of plant productivity at scale. worldwide. The researchers used a sophisticated light response model, adjusted to the forest canopy scale, to transform TROPOMI’s SIF observations into a global GPP dataset. This method represents a substantial advancement over previous models by integrating direct plant physiological signals, thereby reducing uncertainties and improving the reliability of the dataset under various environmental conditions and vegetation types. Through rigorous validation against tower-based GPP measurements, the CMLR GPP dataset demonstrated strong correlation and consistency, proving its effectiveness in accurately capturing the spatial and temporal patterns of global photosynthesis.

Liangyun Liu, principal investigator involved in the study, highlighted the importance of this advancement: “The CMLR GPP dataset not only improves our understanding of global photosynthesis, but also serves as a crucial tool for monitoring the cycle of carbon of the Earth. This dataset is a testimony. with the power to combine satellite technology with ecological research to address pressing environmental challenges.

The creation of the CMLR GPP dataset marks a pivotal moment in environmental research, providing unprecedented insights into the terrestrial carbon cycle, informing models of climate change, and facilitating policy decisions on land management and climate change mitigation.

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The references

DO I

10.34133/remote sensing.0127

Original source URL

https://doi.org/10.34133/remotesensing.0127

Funding information

This research was supported by the National Natural Science Foundation of China (grant numbers 41825002 and 42071310). This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) as part of the German Excellence Strategy – EXC 2070 – 390732324.

About Remote Sensing Journal

The Remote Sensing Journal, an online-only open access journal published in association with AIR-CAS, promotes remote sensing theory, science and technology, as well as interdisciplinary research in the Earth and information sciences.



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