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November 14, 2025SustainabilityOpen Access

Investigating Spatial Variation Characteristics and Influencing Factors of Urban Green View Index Based on Street View Imagery—A Case Study of Luoyang, China

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Authors

JHJunhui HuYDYang DuYMYueshan Ma

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Overview

Analysis reveals spatial variation in green view index influenced by vegetation cover and built environment factors.

Key Points

  • This research investigates the spatial variations of the urban Green View Index (GVI) in Luoyang, China.
  • Utilized Baidu Street View imagery and semantic segmentation for GVI extraction.
  • Employed Spearman correlation analysis and Multiscale Geographically Weighted Regression for data analysis.
  • Conducted field surveys to validate GVI findings.
  • Average GVI of the study area is 15.24%, indicating low greening levels with significant spatial variation.
  • Fractal dimension and vegetation cover positively influence GVI, while built environment factors negatively affect it.
  • Spatial influences of factors vary significantly, with some exhibiting global and others regional effects.

Cite This Study

Hu et al. (2025) studied this question.

synapsesocial.com/papers/692519a7c0ce034ddc353ea3https://doi.org/10.3390/su172210208
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Also Consider

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  1. 1Quantifying spatial heterogeneity and associated factors of Nanjing’s street green view index using urban vegetation structure and street view imagery2026
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  3. 3Spatial-temporal patterns and influencing factors of the Building Green View Index: A new approach for quantifying 3D urban greenery visibility2024 · 9 citations
  4. 4Investigating Green View Perception in Non-Street Areas by Combining Baidu Street View and Sentinel-2 Images2025
  5. 5Equity Evaluation of Street-Level Greenery Based on Green View Index from Street View Images: A Case Study of Hangzhou, China2025 · 8 citations