Scholarlink

<p>The conventional guidelines for planning recreational open spaces (ROS) traditionally focus on isolated spaces, recommending their area, type, and hierarchical level while overlooking their spatial location. This study deviates from the approach, by exploring three landscape ecology-based models in a neighbourhood study, emphasising the significance of ROS spatial patterns and linking them to their usage. (1) The patch-matrix model uses Morphological Spatial Pattern Analysis (MSPA) in Guidos Toolbox to map ROS patterns and highlight fragmentation. (2) The patch-mosaic approach computes various metrics in Fragstats but does not present the pattern-use relationship visually. (3) The graph-based model in Graphab incorporates the recreational index and resistance values of surrounding land uses to depict connectivity graphically and statistically. While each model has limitations, they effectively map ROS connectivity and fragmentation, providing a comprehensive understanding of ROS quality and location in urban neighbourhoods. Future research could explore their application at a larger city scale.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Exploring landscape ecology-based models for mapping recreational open spatial patterns: evidence from a gated urban community in India

  • 期刊论文

  • 发表日期：

    2025年10月18日

查看全文
  • Rukhsana N. Badar,
  • Sarika P. Bahadure

摘要

The conventional guidelines for planning recreational open spaces (ROS) traditionally focus on isolated spaces, recommending their area, type, and hierarchical level while overlooking their spatial location. This study deviates from the approach, by exploring three landscape ecology-based models in a neighbourhood study, emphasising the significance of ROS spatial patterns and linking them to their usage. (1) The patch-matrix model uses Morphological Spatial Pattern Analysis (MSPA) in Guidos Toolbox to map ROS patterns and highlight fragmentation. (2) The patch-mosaic approach computes various metrics in Fragstats but does not present the pattern-use relationship visually. (3) The graph-based model in Graphab incorporates the recreational index and resistance values of surrounding land uses to depict connectivity graphically and statistically. While each model has limitations, they effectively map ROS connectivity and fragmentation, providing a comprehensive understanding of ROS quality and location in urban neighbourhoods. Future research could explore their application at a larger city scale.