Preference, Complexity, and Color Information Entropy Values for Visual Depictions of Plant and Vegetative Growth

Abstract

Few have examined the relationship between landscape color changes, landscape complexity, and laypersons’ visual preference ratings. We examined whether depictions of visual changes to plant and vegetative colors affect preference ratings, estimations of complexity, and computed color information entropy values. Photographs depicted four visual states of plant growth—winter dormancy, foliation, flowering, and senescence—in color at four locations on each of three landscape architecture project sites in New York and Pennsylvania. Participants viewed and evaluated the scenes depicted in the photographs for preference (n = 52) and estimated the presence of complexity (n = 47). A multiparadigm numerical computing environment performed algorithmic functions to calculate Shannon information entropy values of perceptual and categorical colors for each photograph. The visual changes depicted significantly affected perceptual color information entropy values, but significant effects were not found in three contrasts between values for the four stages of plant and vegetative growth. Preference ratings for foliated scenes were significantly higher than those for dormant and senescent scenes. Respondents’ complexity estimations for foliated scenes were lower than those of flowering and senescent, yet complexity and preference did not correlate. Preference correlated strongly and positively with perceptual color information entropy, which may help predict landscape preference. However, the presence of green foliage may affect preference more than perceptual color information entropy within scenes.