Evaluating Urban Greenery Through the Front-Facing Street View Imagery: Insights from a Nanjing Case Study
Street view imagery has become a vital tool for assessing urban street greenery, with the Green View Index (GVI) serving as the predominant metric. However, while GVI effectively quantifies overall greenery, it fails to capture the nuanced, human-scale experience of urban greenery. This study introduces the Front-Facing Green View Index (FFGVI), a metric designed to reflect the perspective of pedestrians traversing urban streets. The FFGVI computation involves three key steps: (1) calculating azimuths for road points, (2) retrieving front-facing street view images, and (3) applying semantic segmentation to identify green pixels in street view imagery. Building on this, this study proposes the Street Canyon Green View Index (SCGVI), a novel approach for identifying boulevards that evoke perceptions of comfort, spaciousness, and aesthetic quality akin to room-like streetscapes. Applying these indices to a case study in Nanjing, China, this study shows that (1) FFGVI exhibited a strong correlation with GVI (R = 0.88), whereas the association between SCGVI and GVI was marginally weaker (R = 0.78). GVI tends to overestimate perceived greenery due to the influence of lateral views dominated by side-facing vegetation; (2) FFGVI provides a more human-centered perspective, mitigating biases introduced by sampling point locations and obstructions such as large vehicles; and (3) SCGVI effectively identifies prominent boulevards that contribute to a positive urban experience. These findings suggest that FFGVI and SCGVI are valuable metrics for informing urban planning, enhancing urban tourism, and supporting greening strategies at the street level.
Authors
- Jin Zhu (ORCID: https://orcid.org/0000-0003-1143-1730)
- Zhe Cao (ORCID: https://orcid.org/0000-0002-8378-348X)
- Yingjing Huang (ORCID: https://orcid.org/0000-0002-8772-1403)
- Yuan Ding (ORCID: https://orcid.org/0000-0001-9802-4606)
- Yue Zhang (ORCID: https://orcid.org/0000-0002-4427-6127)
- Jinglong Du
Institutions
- Hohai University (CN)
- Peking University (CN)
- Suzhou University of Science and Technology (CN)
Publication Details
- Journal
- ISPRS International Journal of Geo-Information
- Published
- 2025-07-24
- DOI
- https://doi.org/10.3390/ijgi14080287
- Citations
- 2
- Primary Topic
- Urban Green Space and Health
- Type
- article
- Field-Weighted Citation Impact
- 2.40
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China