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- W4308342133 abstract "People inherently assess landscapes by creating spontaneous aesthetic liking judgments based on the surrounding stimuli. To understand these judgements objectively, use may be made of the fluency theory of aesthetic pleasure (the psychological processes through which people experience beauty). This study aims to predict people’s visual aesthetic preferences based on fluency theory and to correlate these preferences with landscape types and features. An ordinary least squares (OLS) regression model was developed to predict visual aesthetic liking, using image statistics as explanatory variables. We determined types of landscape using Landscape Character Assessment (LCA) and applied viewshed analyses distinguishing between near, medium, and far zones. We identified landscape features by content analysis making use of machine learning-based image recognition supplied by Google Cloud Vision API. The results show that vegetation and geological forms were the most significant features for people’s visual aesthetic liking, followed by waterscapes and built structures/human settlements. The viewshed analyses indicated that ‘medium-altitude, low-gradient artificial areas’ were visible in photographs with high aesthetic visual liking in all zones (i.e., at all distances). When the photographs showing this type of landscape are examined, the artificial areas in the photographs turn out to consist mostly of historical buildings or remains. This finding suggests that historical sites are not just important for their cultural value, but for their visual aesthetic value as well." @default.
- W4308342133 created "2022-11-11" @default.
- W4308342133 creator A5020605308 @default.
- W4308342133 creator A5050190722 @default.
- W4308342133 date "2022-11-04" @default.
- W4308342133 modified "2023-09-24" @default.
- W4308342133 title "Correlating fluency theory-based visual aesthetic liking of landscape with landscape types and features" @default.
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- W4308342133 cites W1972879197 @default.
- W4308342133 cites W1979754191 @default.
- W4308342133 cites W1980480920 @default.
- W4308342133 cites W1983928958 @default.
- W4308342133 cites W1988187608 @default.
- W4308342133 cites W2000672557 @default.
- W4308342133 cites W2003873840 @default.
- W4308342133 cites W2008608949 @default.
- W4308342133 cites W2008929286 @default.
- W4308342133 cites W2010039638 @default.
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- W4308342133 cites W2029142448 @default.
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- W4308342133 cites W2061986258 @default.
- W4308342133 cites W2073262198 @default.
- W4308342133 cites W2079015760 @default.
- W4308342133 cites W2085378755 @default.
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- W4308342133 doi "https://doi.org/10.1080/10095020.2022.2125836" @default.
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