Fig 1.
Analysis steps to assess the effect of clouds in landscape photographs on people’s preferences.
For each photograph (A), a manipulated version without clouds was created (B). People’s preferences were collected in an online survey and the picture pairs were tested for differences in preferences between A and B to answer research question R1. For all pictures, various predictor variables were calculated using three different approaches [53]. The variables were related to the preference scores via regression analysis to explain variations in preference scores and answer research question R2.
Table 1.
Variables derived for all pictures using three different analysis approaches [53].
Table 2.
Result of the multiple linear regression, using the difference in preference score (B-A) between the manipulated picture without clouds (B) and the original landscape photograph with clouds (A) as dependent variable.
Positive differences indicate that the photo without clouds is preferred over the photo with clouds, negative values indicate the opposite result. Accordingly, a negative regression coefficient B indicates that this variable has a positive effect on the preference score of photos with clouds. Only predictors with variance inflation factor (VIF) <10 during collinearity diagnostics are included.
Fig 2.
Percentage of photos with significant differences in preference scores due to the removal of clouds (paired sample t-test, p<0.05) and photo examples.
Photographs by Eurac Research.
Fig 3.
Relationship between the proportion of sky and clouds in the picture and effects on the preference score due to the removal of clouds.
Values represent mean values of the variables sky and clouds across picture pairs with decreased (A>B), not changed (A = B), and increased (A<B) preference score. A: Original picture with clouds, B: manipulated picture without clouds. Different colored letters (a, b) near the symbols indicate statistically significant differences (LSD post hoc test, p < 0.05).
Fig 4.
Divergent effects of clouds on landscape preferences in two landscapes (Examples 1 and 2).
For each example, above are shown the original picture with clouds (A; photographs by Eurac research) and the manipulated picture without clouds (B), the heatmap indicating the probability that areas are seen within the first 3–5 seconds (middle), and the hotspots derived from the heatmap with the probability that a person will look somewhere within the hotspot areas within the first 3–5 seconds (below). Hotspots are delimited with a red line a probability > = 80% and with a yellow line for a probability < 80%.