Abstract
When designing the river environments, it is very important to analyze the aesthetic influence on each element composing riverine landscape. In this paper, the riverine landscape evaluation system was proposed through two stages of analysis. In the first stage, 30 persons as an observer group rated the riverine scenery for projected color slides which were taken at representative 30 points. The preference judging of observers were analyzed by the semantic-differential method for all of the presented slides. Using the multivariate technique, we characterized four categories as dominant factors for scenic preferences in principal component analysis. In the second stage, the landscape elements items and the score of scenic preferences obtained by the factor analysis were input to the neural network as initial data. Then relationship between those items and stores were characterized by sensitivity analysis of the neural network. The riverine landscape evaluating system was developed using the artificial neural network.
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