Third Spaces to Represent Urban Greenery: A Study of Informal Green Spaces in a High-Density City Using Deep Learning and Geo-Weighted Analysis

In high-density cities like Hong Kong, green spaces are often characterized by fragmentation and uneven spatial distribution, which negatively impacts their accessibility and equity. To address this issue, studies have proposed the use of informal green spaces (IGSs) as a supplementary component to formal urban green spaces (UGSs). However, the spatial delineation and quantitative analysis of IGSs remain challenging due to the lack of standardized identification and evaluation methods. Building upon the work of urban theorists Henry Lefebvre and Edward Soja, this study explores informal green spaces as third spaces. This study employed remote sensing and GIS technologies to systematically assess the spatial distribution and benefits of IGSs, categorizing them into four types: Urban Interstitial IGSs, Transitional IGSs, Fringe IGSs, and Riparian IGSs. Subsequently, an evaluation framework was constructed across ecological, social, and economic dimensions to quantify the overall value of IGSs. The results reveal that IGS significantly contributes to ecological regulation, social interaction, and economic potential, particularly in urban areas with limited green resources. This demonstrates that IGSs can serve as a vital complement to formal urban green spaces, playing a key role in alleviating green space inequity, enhancing urban livability, and promoting sustainability. Furthermore, this study provides a scientific foundation for precise identification, benefit assessment, and optimized management of IGSs, supporting effective integration and rational utilization in future urban planning.

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Publication Details

Journal
ISPRS International Journal of Geo-Information
Published
2025-09-23
DOI
https://doi.org/10.3390/ijgi14100368
Primary Topic
Urban Green Space and Health
Type
article
Field-Weighted Citation Impact
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article

Third Spaces to Represent Urban Greenery: A Study of Informal Green Spaces in a High-Density City Using Deep Learning and Geo-Weighted Analysis

Mingze Chen, 裕美子 宝田, Xiaoya Hou
ISPRS International Journal of Geo-Information
Urban Green Space and Health
article

Third Spaces to Represent Urban Greenery: A Study of Informal Green Spaces in a High-Density City Using Deep Learning and Geo-Weighted Analysis

Mingze Chen, 裕美子 宝田, Xiaoya Hou
article en

Abstract

In high-density cities like Hong Kong, green spaces are often characterized by fragmentation and uneven spatial distribution, which negatively impacts their accessibility and equity. To address this issue, studies have proposed the use of informal green spaces (IGSs) as a supplementary component to formal urban green spaces (UGSs). However, the spatial delineation and quantitative analysis of IGSs remain challenging due to the lack of standardized identification and evaluation methods. Building upon the work of urban theorists Henry Lefebvre and Edward Soja, this study explores informal green spaces as third spaces. This study employed remote sensing and GIS technologies to systematically assess the spatial distribution and benefits of IGSs, categorizing them into four types: Urban Interstitial IGSs, Transitional IGSs, Fringe IGSs, and Riparian IGSs. Subsequently, an evaluation framework was constructed across ecological, social, and economic dimensions to quantify the overall value of IGSs. The results reveal that IGS significantly contributes to ecological regulation, social interaction, and economic potential, particularly in urban areas with limited green resources. This demonstrates that IGSs can serve as a vital complement to formal urban green spaces, playing a key role in alleviating green space inequity, enhancing urban livability, and promoting sustainability. Furthermore, this study provides a scientific foundation for precise identification, benefit assessment, and optimized management of IGSs, supporting effective integration and rational utilization in future urban planning.

ISPRS International Journal of Geo-InformationVol. 14(10)
University of British Columbia (CA), South China University of Technology (CN)
Openalex Percentile: Top 66%
Urban Green Space and Health
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Third Spaces to Represent Urban Greenery: A Study of Informal Green Spaces in a High-Density City Using Deep Learning and Geo-Weighted Analysis — Mingze Chen, 裕美子 宝田, et al. · ISPRS International Journal of Geo-Information (2025) | TGRS Research Map | TGRS