Investigating rural public spaces with cultural significance using morphological, cognitive and behavioural data

N. Bai, Pirouz Nourian, A. Pereira Roders, Raoul Bunschoten, Weixin Huang*, Lu Wang

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
77 Downloads (Pure)


During the rural [re]vitalization process in China, national strategies required rural public spaces with cultural significance to be identified before planning decision-making. However, places identified as culturally significant by planners and visitors can differ from the ones mostly used and valued by locals. Even if there is a growing interest in integrating local perspectives and experiences in planning, studies seldom discuss and compare openly the adequacy of spatial configuration, cognition and behaviour to support it. This study took Anyi Historic Village Cluster as a case study to empirically investigate rural public spaces with three distinct, yet related approaches: (1) Morphological: spatial network centralities based on space syntax; (2) Cognitive: Lynchian village images with semi-structured interviews; (3) Behavioural: spatiotemporal occupation patterns using Wi-Fi positioning tracking. Significant places valued and used by locals and non-locals were detected with the multi-source data. Furthermore, multivariant regression models managed to characterize the relationship among different aspects of investigated rural public spaces, which also helped diagnose places of interest to prioritize in planning, demonstrating the advantage of integrating the sources of information in practice instead of studying them apart. Results can also assist rural planning on how to identify what to preserve, what to enhance, and how to develop such spaces, without overlooking the local needs or losing the rural identity.
Original languageEnglish
Pages (from-to)94-116
Number of pages23
JournalEnvironment and Planning B: Urban Analytics and City Science
Issue number1
Publication statusPublished - 2023


  • Rural Planning
  • Space Syntax
  • Cognition
  • Big Data
  • Activity Space


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