Multivariate Analysis for Solar Resource Assessment Using Unsupervised Learning on Images from the GOES-13 Satellite

Multivariate Analysis for Solar Resource Assessment Using Unsupervised Learning on Images from the GOES-13 Satellite

Solar resource assessment is of paramount importance in the planning of solar energy applications. Solar resources are abundant and characterization is essential for the optimal design of a system. Solar energy is estimated, indirectly, by the processing of satellite images. Several analyses with sa...

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Bibliographic Details
Main Authors: Jared D. Salinas-González, Alejandra García-Hernández, David Riveros-Rosas, Gamaliel Moreno-Chávez, Luis F. Zarzalejo, Joaquín Alonso-Montesinos, Carlos E. Galván-Tejada, Alejandro Mauricio-González, Adriana E. González-Cabrera
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Remote Sensing
Subjects:
solar resource assessment
clustering analysis
satellite images
climatic features
unsupervised learning
solar energy
Online Access:https://www.mdpi.com/2072-4292/14/9/2203

Internet

https://www.mdpi.com/2072-4292/14/9/2203

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