Estimating GPP in China using different site-level datasets, vegetation classification and vegetation indices

Estimating GPP in China using different site-level datasets, vegetation classification and vegetation indices

Abstract Background Machine learning is widely used to estimate gross primary productivity (GPP) on large scales. Usually, models are trained at site level using eddy flux observations and remote sensing based vegetation indices. However, how to more effectively utilize the gradually increasing site...

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Bibliographic Details
Main Authors: Jiahui Xu, Tiexi Chen, Xin Chen, Shengjie Zhou, Zhe Gu, Wenhui Li, Yingying Cui, Shengzhen Wang, Shuci Liu
Format: Article
Language:English
Published: SpringerOpen 2025-08-01
Series:Ecological Processes
Subjects:
Gross primary productivity
Machine learning model
Random forest
Leaf area index
NIRv
Online Access:https://doi.org/10.1186/s13717-025-00617-w
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https://doi.org/10.1186/s13717-025-00617-w

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