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<p>The intangible cultural heritage (ICH) of traditional medicine (TMe) encompasses extensive knowledge and practices for illness prevention and treatment over millennia. Investigating TMe from the perspective of its spatiotemporal evolution and the factors that influence it is crucial. However, existing studies represent TMe’s spatial distribution with point elements, which fail to reflect its regional transmission characteristics. To address this issue, this paper proposes a novel method called point-area representation, using point-like symbols for community-based TMe and face-shaped symbols for regional TMe. First, the spatiotemporal evolution characteristics of TMe are discussed. Second, the physical geography, human geography, and historical factors influencing the distribution of TMe are analyzed using GeoDetector based on the spatialized TMe data. The results illustrate the efficacy of point-area representation for examining the local cultural identity and regional consistency of TMe from a macro perspective, and provide a novel approach to enhance the spatial distribution analysis of ICH.</p>

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An analysis of the spatiotemporal evolution of traditional medicine in China using point-area representation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月11日

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  • Xiaojing Gan,
  • Hong Wang,
  • Ling Ye

摘要

The intangible cultural heritage (ICH) of traditional medicine (TMe) encompasses extensive knowledge and practices for illness prevention and treatment over millennia. Investigating TMe from the perspective of its spatiotemporal evolution and the factors that influence it is crucial. However, existing studies represent TMe’s spatial distribution with point elements, which fail to reflect its regional transmission characteristics. To address this issue, this paper proposes a novel method called point-area representation, using point-like symbols for community-based TMe and face-shaped symbols for regional TMe. First, the spatiotemporal evolution characteristics of TMe are discussed. Second, the physical geography, human geography, and historical factors influencing the distribution of TMe are analyzed using GeoDetector based on the spatialized TMe data. The results illustrate the efficacy of point-area representation for examining the local cultural identity and regional consistency of TMe from a macro perspective, and provide a novel approach to enhance the spatial distribution analysis of ICH.