In an era where urban landscapes are continuously evolving, understanding how people perceive these environments has never been more essential. Urban planners, architects, and policy makers rely on insights regarding citizens’ preferences to create spaces that are not just functional but also enjoyable and equitable. Traditionally, attempts to decode public perceptions of streetscapes have aggregated responses across diverse populations without adequately accounting for demographic nuances. This oversight risks oversimplifying human experience, masking critical differences shaped by culture, age, gender, personality, and socioeconomic status. A groundbreaking study published in 2025 by Quintana, Gu, Liang, and colleagues introduces a paradigm shift by meticulously exploring the complex web of factors influencing urban visual perceptions on a global scale.
The research titled “Global urban visual perception varies across demographics and personalities” harnesses the power of large-scale, diverse data collection to peer deeper into how individuals from varied backgrounds interpret their urban surroundings. Employing street view imagery from cities around the world, the team conducted an ambitious survey involving 1,000 participants carefully balanced across key demographic attributes such as gender, age, income level, education, race, ethnicity, and intriguing dimensions of personality traits. What sets this inquiry apart is its deliberate effort to transcend homogenized data pools, instead emphasizing the heterogeneity of urban perception that emerges when identity markers are honored and dissected.
At the heart of this work lies the Street Perception Evaluation Considering Socioeconomics (SPEC) dataset, a rich repository created by the authors that captures the spectrum of perception indicators conventionally used in urban studies. These include long-established dimensions like safety, liveliness, wealth, beauty, boredom, and depression. Beyond these traditional markers, the study introduces four novel sentiments that resonate deeply with contemporary urban life—participants’ willingness or preference to live nearby, walk, cycle, and appreciation of greenery. These additions reflect an evolving understanding of what makes streetscapes desirable and functional in today’s world, highlighting behaviors and environmental qualities that signal livability.
What emerges from analysis of the SPEC dataset is a compelling portrait of the nuanced ways in which demographics and personality intersect to shape urban visual assessments. For instance, perceptions of safety are influenced not only by objective street features but also by the observer’s age, cultural background, and psychological predispositions. Older participants may prioritize different cues compared to younger individuals; income and education create lenses that either amplify or attenuate feelings of security and affluence. Meanwhile, personality traits such as openness, neuroticism, or extraversion subtly color the emotional valence assigned to urban images. This multidimensional approach uncovers patterns invisible in aggregate data, offering urban designers a richer canvas of human sentiment.
One of the study’s most striking revelations concerns the discrepancies between human perceptions and predictions made by machine learning models trained on widely used global datasets. While artificial intelligence has been heralded as a transformative tool for urban analytics, the authors found that such models are prone to overestimating positive attributes and downplaying negative sentiments when applied universally. For example, AI might predict a streetscape as highly “safe” or “beautiful” without incorporating contextual socio-cultural factors that influence human experience on the ground. This gap highlights the critical need for integrating local demographic data and personality insights into computational frameworks to avoid reinforcing biases or misguiding urban interventions.
The methodological rigor underpinning the study warrants particular attention. By recruiting a demographically balanced sample representing five countries and 45 nationalities, the research circumvents the common pitfall of parochial datasets limited to Western or urban-centric populations. Each participant rated a diverse set of street view images on the ten perception indicators, ensuring a robust cross-cultural comparison. The integration of personality assessments alongside socioeconomic metrics adds an innovative psychological dimension rarely explored in urban perception research. This comprehensive approach lays foundational groundwork for future studies aiming to unravel the complexity of human-environment interactions at scale.
Moreover, the inclusion of novel indicators such as “live nearby,” “walk,” “cycle,” and “green” reflects an alignment with contemporary urban priorities, including active transportation and environmental sustainability. These sentiments speak to behavioral intentions and preferences rather than mere appearances, signaling a shift toward understanding the lived realities and aspirations of city dwellers. For instance, a streetscape might be rated as beautiful but not conducive to cycling or walking, signaling design trade-offs and opportunities for improvement. By quantifying these preferences, the study provides actionable insights for urban policies striving to enhance mobility, environmental quality, and public health.
The authors also demonstrate that local sentiments significantly shape perceptions, underscoring the importance of embedding geographical context in urban studies. Perception is not formed in a vacuum; the same street can evoke divergent feelings depending on historical, cultural, and social undercurrents specific to its locale. This variability cautions against the uncritical application of global models and calls for localized, participatory approaches in urban assessment and planning. Community engagement, informed by finely tuned demographic insights, can thus become a cornerstone for designing streetscapes that resonate with the lived experiences and values of diverse populations.
This research carries profound implications for the future of urban design and management. It challenges planners and AI developers alike to rethink how perception data is gathered, interpreted, and deployed. The demonstrated demographic and psychological divergences demand a move beyond one-size-fits-all metrics toward stratified frameworks capable of capturing individual and group-specific experiences. This nuanced understanding permits the tailoring of urban interventions, enabling environments that feel not only functional but genuinely inclusive and welcoming. In doing so, cities can aspire to equity in experience, fostering cohesion amidst diversity.
Beyond theoretical insights, the study’s findings have practical applications. Urban planners could leverage the SPEC dataset to prioritize improvements aligned with demographic-specific needs. For example, ensuring green space accessibility for lower-income groups or enhancing walkability in neighborhoods populated by older adults. Policymakers may also utilize these insights in participatory planning workshops, creating feedback loops that honor community voices hitherto obscured by aggregated data. The study also offers a blueprint for integrating psychological constructs into urban decision-making, paving the way for discoveries about how mental wellbeing intersects with spatial design.
Importantly, the research highlights the limitations of present-day machine-learning models in capturing the rich texture of human environment perception. As much urban assessment increasingly relies on automated tools to process big data, the risk of sidelining or misinterpreting diverse lived experiences grows. The authors’ findings advocate strongly for incorporating demographic and personality data to enhance model fidelity. This could involve developing new algorithms that adjust predictions based on locally calibrated parameters or hybrid approaches blending human-centered surveys with AI analysis. Such innovations promise to democratize urban design, respecting subjective experience as much as objective measurement.
The emotional and psychological dimensions uncovered by this work further illuminate the intricacies of urban perception. Feelings associated with streetscapes—whether of boredom, depression, or vitality—reflect deep, often subconscious human responses to form and function. By mapping how these sentiments vary across demographics, the study opens avenues for designing cities that not only satisfy material needs but also nurture emotional wellbeing. The integration of new indicators centered on movement and greenery reinforces a holistic vision of urban livability, acknowledging that the quality of life is bound tightly to both physical infrastructure and subjective experience.
Culturally, the research underscores the diversity of perceptual frameworks operating worldwide. Perceptions marked by cultural heritage, social norms, and historical experience underpin how individuals interpret threats, beauty, or vitality in urban scenes. Recognizing these differences challenges universalist assumptions in urban theory and practice and demands that planners adopt culturally sensitive methodologies. This nuance enhances the potential for cities to embody pluralism, accommodating multiple realities and fostering cross-cultural understanding through shared public spaces designed with empathy.
As the world urbanizes at an unprecedented pace, the importance of inclusive, data-driven yet human-sensitive approaches to city planning intensifies. This study marks a milestone, reminding the academic and practitioner communities that perception is not monolithic, but a kaleidoscope refracted through the prisms of identity and personality. Leveraging such insights can drive smarter, fairer urban innovations, creating environments that truly respond to the people they serve. Through a sophisticated fusion of psychological profiling, demographic analysis, and spatial imagery, the research charts a path toward cities that are not only seen but felt deeply and personally.
In conclusion, Quintana and colleagues convincingly argue for the recalibration of urban perception research to include demographic and psychological diversity. Their study, through the pioneering SPEC dataset, reveals how varied urban perceptions can be—even when evaluating the same streetscapes. By illuminating the limitations of existing AI models and emphasizing contextual understanding, this work urges a fundamental rethink of how cities listen to and learn from their inhabitants. Ultimately, their findings pave the way for a more human-centered urban future, where perception is honored as a mosaic of voices, each shaping the urban experience in indelible ways.
Subject of Research:
Urban visual perception influenced by demographic and personality variables, and its implications for urban planning.
Article Title:
Global urban visual perception varies across demographics and personalities.
Article References:
Quintana, M., Gu, Y., Liang, X. et al. Global urban visual perception varies across demographics and personalities. Nat Cities (2025). https://doi.org/10.1038/s44284-025-00330-x
Image Credits:
AI Generated
