Multi-Label Data Fusion to Support Agricultural Vulnerability Assessments

Multi-Label Data Fusion to Support Agricultural Vulnerability Assessments

Identifying crop species and varieties adaptable to climate change impacts is one of the main aspects of climate vulnerability assessments. This estimation involves processing, integrating, and analyzing many information sources to provide accurate and timely responses. However, designing this evalu...

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Bibliographic Details
Main Authors: Ivan Dario Lopez, Apolinar Figueroa, Juan Carlos Corrales
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Climate vulnerability assessment
climate change
crop production
data processing
data fusion
machine learning
Online Access:https://ieeexplore.ieee.org/document/9455370/

Internet

https://ieeexplore.ieee.org/document/9455370/

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