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Yuhao Kang
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Feeling Nature
Measuring perceptions of biophilia across global biomes using visual AI
Journal article
(2025)
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Deborah C. Lefosse, Fábio Duarte, Rohit Priyadarshi Sanatani, Yuhao Kang, Arjan van Timmeren, Carlo Ratti
An increasing number of studies suggest that biophilia encompasses benefits resulting from human–nature interactions. However, quantifying these effects remains challenging. Since natural features vary worldwide, this study explores whether people perceive biophilia universally or if it is influenced by local or geographical conditions. To this end, we quantify, qualify, and map biophilic perceptions (BP) across terrestrial biomes. We first surveyed 400 people in eight cities to identify urban features evoking more positive feelings via Google Street View imagery. Thereafter, survey outcomes were used to calculate specific metrics (coverage, diversity, distribution, intensity, specificity) aimed at measuring BP using a machine-learning model to detect 25 visual biophilic classes (BC). We found that people yield greater benefits from eye contact with nature-based elements within the cityscape unanimously, regardless of biome or gender. We provide AI-driven measurement tools applicable to any city globally to foster understanding and the enhancement of biophilic experiences.
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An increasing number of studies suggest that biophilia encompasses benefits resulting from human–nature interactions. However, quantifying these effects remains challenging. Since natural features vary worldwide, this study explores whether people perceive biophilia universally or if it is influenced by local or geographical conditions. To this end, we quantify, qualify, and map biophilic perceptions (BP) across terrestrial biomes. We first surveyed 400 people in eight cities to identify urban features evoking more positive feelings via Google Street View imagery. Thereafter, survey outcomes were used to calculate specific metrics (coverage, diversity, distribution, intensity, specificity) aimed at measuring BP using a machine-learning model to detect 25 visual biophilic classes (BC). We found that people yield greater benefits from eye contact with nature-based elements within the cityscape unanimously, regardless of biome or gender. We provide AI-driven measurement tools applicable to any city globally to foster understanding and the enhancement of biophilic experiences.