Global fire modelling and control attributions based on the ensemble machine learning and satellite observations

Global fire modelling and control attributions based on the ensemble machine learning and satellite observations

Contemporary fire dynamics is one of the most complex and least understood land surface phenomena. Global fire controls related to climate, vegetation, and anthropogenic activity are usually intertwined, and difficult to disentangle in a quantitative way. Here, we leveraged an ensemble of five machi...

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Bibliographic Details
Main Authors: Yulong Zhang, Jiafu Mao, Daniel M. Ricciuto, Mingzhou Jin, Yan Yu, Xiaoying Shi, Stan Wullschleger, Rongyun Tang, Jicheng Liu
Format: Article
Language:English
Published: Elsevier 2023-06-01
Series:Science of Remote Sensing
Subjects:
Contemporary fire dynamics
Global fire modeling
Fire attributions
Ensemble machine learning
Remote sensing
Climate-vegetation-human controls
Online Access:http://www.sciencedirect.com/science/article/pii/S2666017223000135

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http://www.sciencedirect.com/science/article/pii/S2666017223000135

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