It is not always greener on the other side: Greenery perception across demographics and personalities in multiple cities

TL;DR

The paper investigates how subjective greenery perception aligns with objective street-view greenery measurements across five global cities using the SPECS dataset. It combines Green View Index, spatial entropy, and depth-based proximity with extensive participant demographics to assess correlations, biases, and predictors of perception. Key findings show a moderate link between perception and objective greenery, with perception often higher than measured greenery and strongly influenced by where people live and how greenery is spatially arranged. The results argue for integrating subjective, location-specific assessments with objective metrics in urban greenery planning, recognizing the nuanced role of cultural and experiential context. Overall, the work provides practical guidance for more human-centric greenery assessments in diverse urban environments.

Abstract

Quantifying and assessing urban greenery is consequential for planning and development, reflecting the everlasting importance of green spaces for multiple climate and well-being dimensions of cities. Evaluation can be broadly grouped into objective (e.g., measuring the amount of greenery) and subjective (e.g., polling the perception of people) approaches, which may differ -- what people see and feel about how green a place is might not match the measurements of the actual amount of vegetation. In this work, we advance the state of the art by measuring such differences and explaining them through human, geographic, and spatial dimensions. The experiments rely on contextual information extracted from street view imagery and a comprehensive urban visual perception survey collected from 1,000 people across five countries with their extensive demographic and personality information. We analyze the discrepancies between objective measures (e.g., Green View Index (GVI)) and subjective scores (e.g., pairwise ratings), examining whether they can be explained by a variety of human and visual factors such as age group and spatial variation of greenery in the scene. The findings reveal that such discrepancies are comparable around the world and that demographics and personality do not play a significant role in perception. Further, while perceived and measured greenery correlate consistently across geographies (both where people and where imagery are from), where people live plays a significant role in explaining perceptual differences, with these two, as the top among seven, features that influences perceived greenery the most. This location influence suggests that cultural, environmental, and experiential factors substantially shape how individuals observe greenery in cities.

Figures (15)

• Figure 1: Workflow and methodology of this study: dataset identification, data preprocessing, and scores comparisons. We used the Street Perception Evaluation Considering Socioeconomic (SPECS) dataset due to its diverse samples and inclusion of a greenery perceptual indicator Quintana.2025. We calculated green perception scores based on ratings for all 400 images, obtained the Green View Index (GVI) using the panoptic semantic segmentation models recommended in Hou.2024, and computed greenery spatial arrangement metrics based on the segmented greenery. We then compared these subjective, i.e., greenery perception, and objective, i.e., GVI, measurements in terms of their correlation and bias. Finally, as a last comparison, we looked into the vegetation spatial arrangement within images among the least and most green-rated images.
• Figure 2: Four images from the SPECS dataset Quintana.2025 arranged based on their (a) green perception Q scores (y-axis) and their Green View Index (GVI) values (x-axis), and their (b) spatial entropy.
• Figure 3: Pearson correlation between the green perception Q scores and Green View Index (GVI) using all images and responses (a) and grouped by the images' and participants location (b).
• Figure 4: Bland-Altman plot comparing differences between green perception Q Scores and normalized Green View Index (GVI) values across different location pairs (country-city pairs). The plot shows the difference between measurements (y-axis) against their mean (x-axis) for all images and participants' location pairs, with green horizontal lines representing the mean difference, dashed orange lines indicating $\pm$1.96 standard deviations, and a dotted gray line at zero. Each location pair has more than 54 images with more than four pairwise comparisons ($n\geq54$). Location pairs with significant differences between green perception Q score and normalized GVI are shown (*$p<0.05$).
• Figure 5: Greenery distributions and statistical comparison of street view imagery (SVI) within the 25$^{th}$ ($\leq$Q1 in lighter green) or within the 75$^{th}$ ($\geq$Q3 in darker green) percentile of their green perception Q scores. Green perception Q scores are calculated based on the images' and participants' location pairs (country-city pairs), with the median represented by a filled circle. Each location pair has more than 14 images with more than four pairwise comparisons ($n\geq14$). Significance thresholds *$p<0.05$.