Comparative Analysis of Two Machine Learning Algorithms in Predicting Site-Level Net Ecosystem Exchange in Major Biomes

Comparative Analysis of Two Machine Learning Algorithms in Predicting Site-Level Net Ecosystem Exchange in Major Biomes

The net ecosystem CO<sub>2</sub> exchange (NEE) is a critical parameter for quantifying terrestrial ecosystems and their contributions to the ongoing climate change. The accumulation of ecological data is calling for more advanced quantitative approaches for assisting NEE prediction. In...

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Bibliographic Details
Main Authors: Jianzhao Liu, Yunjiang Zuo, Nannan Wang, Fenghui Yuan, Xinhao Zhu, Lihua Zhang, Jingwei Zhang, Ying Sun, Ziyu Guo, Yuedong Guo, Xia Song, Changchun Song, Xiaofeng Xu
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Remote Sensing
Subjects:
machine learning
NEE
random forest
terrestrial ecosystem
XGBoost
Online Access:https://www.mdpi.com/2072-4292/13/12/2242

Internet

https://www.mdpi.com/2072-4292/13/12/2242

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