Capturing leaf color variances over space is important for diagnosing plant nutrient and health status,estimating water availability as well as improving ornamental and tourism values of *** this study,leaf color vari...
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Capturing leaf color variances over space is important for diagnosing plant nutrient and health status,estimating water availability as well as improving ornamental and tourism values of *** this study,leaf color variances of the Eurasian smoke tree,Cotinus coggygria were estimated based on geographic and climate variables in a shrub community using generalized elastic net(gelnet)and support vector machine(SVM)*** reveal that leaf color varied over space,and the variances were the result of geography due to its effect on solar radiation,temperature,illumination and moisture of the shrub environment,whereas the influence of climate were not *** SVM and gelnet algorithm models were similar estimating leaf color indices based on geographic variables,and demonstrates that both techniques have the potential to estimate leaf color variances of *** in a shrubbery with a complex geographical environment in the absence of human activity.
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