Cultural Heritage Risk Assessment Based on Explainable Machine Learning Models: A Case Study of the Ancient Tea Horse Road in China DOI Creative Commons
Hao Zhang, Bo Shu, Yang Liu

и другие.

Land, Год журнала: 2025, Номер 14(4), С. 734 - 734

Опубликована: Март 29, 2025

As the core carrier of historical and cultural identity, heritage is facing multiple threats such as natural disasters, human activities its own vulnerability. There an increasing number studies on risk assessment around world, but in China has not been fully explored. In this paper, LightGBM model was used to quantitatively analyze main influencing factors along Ancient Tea Horse Road Sichuan, spatial analysis carried out by combining geographic information system (GIS) technology. order improve interpretability results, SHAP method introduced systematically evaluate contribution each factor heritage. This study identified seven major factors, including landslides, collapses, debris flows, earthquakes, soil erosion, urban road networks, vulnerability, constructed a framework that comprehensively considers vulnerability synthetic itself. The results divided sites into five levels: very low, medium, high high, showed 52.36% classified at medium above, revealing severe security situation faced region indicating urgent need take effective protective management measures deal with risks challenges.

Язык: Английский

Cultural Heritage Risk Assessment Based on Explainable Machine Learning Models: A Case Study of the Ancient Tea Horse Road in China DOI Creative Commons
Hao Zhang, Bo Shu, Yang Liu

и другие.

Land, Год журнала: 2025, Номер 14(4), С. 734 - 734

Опубликована: Март 29, 2025

As the core carrier of historical and cultural identity, heritage is facing multiple threats such as natural disasters, human activities its own vulnerability. There an increasing number studies on risk assessment around world, but in China has not been fully explored. In this paper, LightGBM model was used to quantitatively analyze main influencing factors along Ancient Tea Horse Road Sichuan, spatial analysis carried out by combining geographic information system (GIS) technology. order improve interpretability results, SHAP method introduced systematically evaluate contribution each factor heritage. This study identified seven major factors, including landslides, collapses, debris flows, earthquakes, soil erosion, urban road networks, vulnerability, constructed a framework that comprehensively considers vulnerability synthetic itself. The results divided sites into five levels: very low, medium, high high, showed 52.36% classified at medium above, revealing severe security situation faced region indicating urgent need take effective protective management measures deal with risks challenges.

Язык: Английский

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