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

  • Matias Quintana
  • , Fangqi Liu
  • , Jussi Torkko
  • , Youlong Gu
  • , Xiucheng Liang
  • , Yujun Hou
  • , Koichi Ito
  • , Yihan Zhu
  • , Mahmoud Abdelrahman
  • , Tuuli Toivonen
  • , Yi Lu
  • , Filip Biljecki*
  • *Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

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 1000 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. We also found that the spatial arrangement of greenery in the sight, rather than its proximity to the person, influences perception. Our study provides a new understanding of the deep relationships between objective and subjective street-level greenery assessments, contributing to a more human-centric design of green urban environments. © 2026 Elsevier B.V.
Original languageEnglish
Article number105618
Number of pages21
JournalLandscape and Urban Planning
Volume271
Online published6 Mar 2026
DOIs
Publication statusPublished - Jul 2026

Funding

We are grateful for the constructive and encouraging feedback from the editors and reviewers, which has significantly improved our paper. We thank the participants of the study. This research was conducted at the Future Cities Lab Global at Singapore-ETH Centre. Future Cities Lab Global is supported and funded by the National Research Foundation, Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme and ETH Zürich (ETHZ), with additional contributions from the National University of Singapore (NUS), Nanyang Technological University (NTU), Singapore and the Singapore University of Technology and Design (SUTD). This research is part of the project Large-scale 3D Geospatial Data for Urban Analytics, which is supported by the National University of Singapore under the Start Up Grant R-295-000-171-133. This research was supported by the Singapore International Graduate Award (SINGA) scholarship provided by the Agency for Science, Technology, and Research (A*STAR), and the NUS Graduate Research Scholarship (X.L). This work was supported by the Finnish Ministry of Education and Culture’s Pilot for Doctoral Programmes (Pilot project Mathematics of Sensing, Imaging, and Modelling). This work was supported by the Research Council of Finland (Flagship of Advanced Mathematics for Sensing Imaging and Modelling, FAME, grant number 359182). This work was supported by the Research Council of Finland (Flagship of Advanced Mathematics for Sensing, Imaging, and Modelling, FAME, grant number 359182). This work was funded by the GREENTRAVEL project by the European Union (ERC, project 101044906). Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Research Keywords

  • GeoAI
  • Green view index
  • Pedestrian greenery
  • Street view imagery
  • Urban sensing
  • Urban visual perception

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