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  • 标题:Saliency Cognition of Urban Monuments Based on Verbal Descriptions of Mental-Spatial Representations (Case Study: Urban Monuments in Qazvin)
  • 本地全文:下载
  • 作者:Asieh Sameh ; Armin Bahramian ; Mohsen Faizi
  • 期刊名称:Space Ontology International Journal
  • 印刷版ISSN:2345-6450
  • 电子版ISSN:2423-7299
  • 出版年度:2020
  • 卷号:9
  • 期号:2
  • 页码:9-24
  • 语种:English
  • 出版社:Islamic Azad University
  • 摘要:Urban monuments encompass a wide range of architectural works either intentionally or unintentionally. These works are often salient due to their inherently explicit or hidden components and qualities in the urban context. Therefore, they affect the mental-spatial representations of the environment and make the city legible. However, the ambiguity of effective components often complicates their saliency evaluation and measurement. In addition, the literature of architecture and urban planning evidently lacks a systematic method for extracting and determining the architectural components affecting the saliency of urban monuments. After reviewing the research literature, this study aims to analyze the nature of these components by proposing a method of extracting and identifying them through a qualitative approach through case studies of urban monuments in Qazvin. For this purpose, given the importance of verbal descriptions of urban monuments in advancing the objectives of this study as a result of realizing mental-spatial representations of the environment, the “Reading of Verbal Descriptions” was integrated with the “Fuzzy Delphi technique” to extract the components that affect saliency. Based on these strategies, architecture and urbanism experts were surveyed using a questionnaire. In addition to determining the features of urban monuments and their examples, the results explained 16 effective components. Based on the percentages of referral and consensus, the components are then weighed and codified in a saliency model of urban monuments.
  • 关键词:Urban monument;Saliency;Mental-spatial representation;Verbal descriptions
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