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Biophilic Design: The Theory, Science, and Practice of Bringing Buildings to Life

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20世紀の名著名論：David Marr:Vision:a Computational Investigation into the Human Representation and Processing of Visual Information

Psychological responses to natural patterns in architecture

Does spending time in beautiful settings boost people’s happiness? The answer to this question has long remained elusive due to a paucity of large-scale data on environmental aesthetics and individual happiness. Here, we draw on two novel datasets: first, individual happiness data from the smartphone app, Mappiness, and second, crowdsourced ratings of the “scenicness” of photographs taken across England from the online game Scenic-Or-Not. We find that individuals are happier in more scenic locations, even when we account for a range of factors such as the activity the individual was engaged in at the time, weather conditions and the income of local inhabitants. Crucially, this relationship holds not only in natural environments, but in built-up areas too, even after controlling for the presence of green space. Our results provide evidence that the aesthetics of the environments that policymakers choose to build or demolish may have consequences for our everyday wellbeing.

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Happiness is Greater in More Scenic Locations

Psychological and neural responses to architectural interiors.

Previous research has investigated ways to quantify visual information of a scene in terms of a visual processing hierarchy, i. e. making sense of visual environment by segmentation and integration of elementary sensory input. Guided by this research, studies have developed categories for low-level visual features (e.g., edges, colors), high-level visual features (scene-level entities that convey semantic information such as objects), and how models of those features predict aesthetic preference and naturalness. For example, in Kardan et al. (2015), 52 participants provided aesthetic preference and naturalness ratings, which are used in the current study, for 307 images of mixed natural and urban content. Kardan et al. (2015) then developed a model using low-level features to predict aesthetic preference and naturalness and could do so with high accuracy. What has yet to be explored is the ability of higher-level visual features (e.g., horizon line position relative to viewer, geometry of building distribution relative to visual access) to predict aesthetic preference and naturalness of scenes, and whether higher-level features mediate some of the association between the low-level features and aesthetic preference or naturalness. In this study we investigated these relationships and found that low- and high- level features explain 68.4% of the variance in aesthetic preference ratings and 88.7% of the variance in naturalness ratings. Additionally, several high-level features mediated the relationship between the low-level visual features and aesthetic preference. In a multiple mediation analysis, the high-level feature mediators accounted for over 50% of the variance in predicting aesthetic preference. These results show that high-level visual features play a prominent role predicting aesthetic preference, but do not completely eliminate the predictive power of the low-level visual features. These strong predictors provide powerful insights for future research relating to landscape and urban design with the aim of maximizing subjective well-being, which could lead to improved health outcomes on a larger scale.

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Image Feature Types and Their Predictions of Aesthetic Preference and Naturalness

This study investigated variation in viewing time in response to different types of images with violent and/or disgusting content. We hypothesized that people should exhibit aversion to and avoidance of disgusting images and/or interest in and attraction to images of violence, especially those that represent a potential threat to them. Study participants were 101 White male and female college students. They viewed 60 images on a computer monitor and could control, within certain limits, their viewing time for each image. Viewing time was lowest for disgusting non-violent images, highest for violent non-disgusting images, and intermediate for images that were both violent and disgusting. Images of animal to human violence had higher viewing time than images of human to animal violence, and images of male-male violence in which an outgroup individual was the perpetrator of violence against an ingroup individual had the highest viewing time of all images in which we manipulated the ingroup/outgroup identity of perpetrator and victim. Images of outgroup-ingroup violence also had higher viewing time than images of accidental self-inflicted violence. Female participants had lower viewing time than male participants across most image types, but variation in viewing time in relation to the content of the image was largely similar in men and women. The results of our study are consistent with our hypothesis that differences in viewing time devoted to images with disgusting and violent content reflect functionally adaptive responses to different cues of danger: presence of pathogens vs threat of physical violence. Further research on responses to disgusting and nondisgusting images of violence may enhance our understanding of the role of emotions in the regulation of violent behavior and responses to displays of violence.

Frank F. Ibarra

Papers

Image Feature Types and Their Predictions of Aesthetic Preference and Naturalness

Assessing People’s Interest in Images with Violent or Disgusting Content: a Functional-Evolutionary Analysis