Assessment of Six Machine Learning Methods for Predicting Gross Primary Productivity in Grassland

Assessment of Six Machine Learning Methods for Predicting Gross Primary Productivity in Grassland

Grassland gross primary productivity (GPP) is an important part of global terrestrial carbon flux, and its accurate simulation and future prediction play an important role in understanding the ecosystem carbon cycle. Machine learning has potential in large-scale GPP prediction, but its application a...

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Bibliographic Details
Main Authors: Hao Wang, Wei Shao, Yunfeng Hu, Wei Cao, Yunzhi Zhang
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Remote Sensing
Subjects:
machine learning
gross primary productivity
prediction
key factors
Mongolian Plateau
Online Access:https://www.mdpi.com/2072-4292/15/14/3475

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https://www.mdpi.com/2072-4292/15/14/3475

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