The Visual Greenery Field: Representing the Urban Green Visual Continuum with Street View Image Analysis

This study proposes a method to analyze urban greenery perceived from street-level viewpoints by combining geographic information systems (GIS) with image segmentation. GIS was utilized for a geospatial statistical analysis to examine anisotropy in the distribution of urban greenery and to spatialize image segmentation data. The result was the Visual Greenery Field (VGF) model, which offers a vector-based representation of greenery visibility and directionality in urban environments. The analysis employed street view images from selected geographic locations to calculate a Green View Index (GVI) and derive visual vectors. Validation confirmed the reliability of the methods, as evidenced by solid correlations between automatic and manual segmentations. The findings indicated that greenery visibility varies across the cardinal directions, highlighting that the GVI’s average value may obscure significant differences in greenery’s distribution. The VGF model complements the GVI by revealing directional coherence in urban greenery experiences. This study emphasizes that while the GVI provides an overall assessment, integrating the VGF model enriches the understanding of perceptions of urban greenery by capturing its complexities and nuances.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2024-10-31
DOI
https://doi.org/10.3390/su16219512
Citations
3
Primary Topic
Urban Green Space and Health
Type
article
Field-Weighted Citation Impact
0.94
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Visual Greenery Field: Representing the Urban Green Visual Continuum with Street View Image Analysis

Gabriele Stancato
3 citations
Sustainability
Urban Green Space and Health
0.94
article

The Visual Greenery Field: Representing the Urban Green Visual Continuum with Street View Image Analysis

Gabriele Stancato
article en
3 citations

Abstract

This study proposes a method to analyze urban greenery perceived from street-level viewpoints by combining geographic information systems (GIS) with image segmentation. GIS was utilized for a geospatial statistical analysis to examine anisotropy in the distribution of urban greenery and to spatialize image segmentation data. The result was the Visual Greenery Field (VGF) model, which offers a vector-based representation of greenery visibility and directionality in urban environments. The analysis employed street view images from selected geographic locations to calculate a Green View Index (GVI) and derive visual vectors. Validation confirmed the reliability of the methods, as evidenced by solid correlations between automatic and manual segmentations. The findings indicated that greenery visibility varies across the cardinal directions, highlighting that the GVI’s average value may obscure significant differences in greenery’s distribution. The VGF model complements the GVI by revealing directional coherence in urban greenery experiences. This study emphasizes that while the GVI provides an overall assessment, integrating the VGF model enriches the understanding of perceptions of urban greenery by capturing its complexities and nuances.

SustainabilityVol. 16(21)
Politecnico di Milano (IT)
Sustainable cities and communities
Openalex Percentile: Top 24%
Urban Green Space and Health
0.94
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

The Visual Greenery Field: Representing the Urban Green Visual Continuum with Street View Image Analysis — Gabriele Stancato · Sustainability (2024) | TGRS Research Map | TGRS