Cite
A machine learning approach to estimation of downward solar radiation from satellite-derived data products: An application over a semi-arid ecosystem in the U.S
MLA
Nancy F. Glenn, et al. “A Machine Learning Approach to Estimation of Downward Solar Radiation from Satellite-Derived Data Products: An Application over a Semi-Arid Ecosystem in the U.S.” PLoS ONE, vol. 12, no. 8, Aug. 2017. EBSCOhost, widgets.ebscohost.com/prod/customlink/proxify/proxify.php?count=1&encode=0&proxy=&find_1=&replace_1=&target=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&scope=site&db=edsair&AN=edsair.doi.dedup.....11933ccaf0519ab42f44158187184d85&authtype=sso&custid=ns315887.
APA
Nancy F. Glenn, Bangshuai Han, Qingtao Zhou, Reggie D. Walters, & Alejandro N. Flores. (2017). A machine learning approach to estimation of downward solar radiation from satellite-derived data products: An application over a semi-arid ecosystem in the U.S. PLoS ONE, 12(8).
Chicago
Nancy F. Glenn, Bangshuai Han, Qingtao Zhou, Reggie D. Walters, and Alejandro N. Flores. 2017. “A Machine Learning Approach to Estimation of Downward Solar Radiation from Satellite-Derived Data Products: An Application over a Semi-Arid Ecosystem in the U.S.” PLoS ONE 12 (8). http://widgets.ebscohost.com/prod/customlink/proxify/proxify.php?count=1&encode=0&proxy=&find_1=&replace_1=&target=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&scope=site&db=edsair&AN=edsair.doi.dedup.....11933ccaf0519ab42f44158187184d85&authtype=sso&custid=ns315887.