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<p>This study constructs a quantitative analysis toolkit for heritage site selection by integrating Monte Carlo simulation, spatial density analysis, kernel density estimation, and partial correlation analysis. Taking the Ming Dynasty Yansui defense district as an empirical case, based on vectorized historical spatial data and geographical simulation statistics, the “Geographical Environment-oriented Cognitive Framework for the Great Wall Site Selection” is proposed. The framework deconstructs the intricate relationships between the Great Wall and its geographical environment into three analytical dimensions—spatial representation, environmental preference, and defense features. It explains the spatial distribution characteristics of the Great Wall heritage under different geographical environments in the ecologically fragile Loess Plateau, and its differentiated siting preferences and synergistic evolution with topographic factors. The research provides scientific support for predicting Great Wall sites, conservation planning, and resource management, offering methodological references for studying the spatial locations and environmental variables of linear cultural heritage and settlement systems.</p>

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Interactions between the Ming Yansui Great Wall heritage and geographical environment via Monte Carlo simulation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月11日

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  • Li Yuan,
  • Zhaoyi Li,
  • Yizhen Wang,
  • Zhiguo Hao,
  • Chunlei Yu

摘要

This study constructs a quantitative analysis toolkit for heritage site selection by integrating Monte Carlo simulation, spatial density analysis, kernel density estimation, and partial correlation analysis. Taking the Ming Dynasty Yansui defense district as an empirical case, based on vectorized historical spatial data and geographical simulation statistics, the “Geographical Environment-oriented Cognitive Framework for the Great Wall Site Selection” is proposed. The framework deconstructs the intricate relationships between the Great Wall and its geographical environment into three analytical dimensions—spatial representation, environmental preference, and defense features. It explains the spatial distribution characteristics of the Great Wall heritage under different geographical environments in the ecologically fragile Loess Plateau, and its differentiated siting preferences and synergistic evolution with topographic factors. The research provides scientific support for predicting Great Wall sites, conservation planning, and resource management, offering methodological references for studying the spatial locations and environmental variables of linear cultural heritage and settlement systems.