Exploring the Individualized Effect of Climatic Drivers on MODIS Net Primary Productivity through an Explainable Machine Learning Framework

Exploring the Individualized Effect of Climatic Drivers on MODIS Net Primary Productivity through an Explainable Machine Learning Framework

Along with the development of remote sensing technology, the spatial–temporal variability of vegetation productivity has been well observed. However, the drivers controlling the variation in vegetation under various climate gradients remain poorly understood. Identifying and quantifying the independ...

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Bibliographic Details
Main Authors: Luyi Li, Zhenzhong Zeng, Guo Zhang, Kai Duan, Bingjun Liu, Xitian Cai
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Remote Sensing
Subjects:
net primary productivity
MODIS
vegetation response
climatic drivers
machine learning
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Online Access:https://www.mdpi.com/2072-4292/14/17/4401

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https://www.mdpi.com/2072-4292/14/17/4401

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