A GIS-based model for determining safety indices to evaluate the post-disaster usability of urban open and green spaces in Amasya City Center, Türkiye

Celik, Kadir Tolga; Kurdoglu, Banu Cicek

doi:10.1016/j.ijdrr.2024.104439

International Journal of Disaster Risk Reduction

2024

DOI: 10.1016/j.ijdrr.2024.104439

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A GIS-based model for determining safety indices to evaluate the post-disaster usability of urban open and green spaces in Amasya City Center, Türkiye

Kadir Tolga Celik,

Banu Cicek Kurdoglu

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Multiple Bayesian models approach to assessing drivers of cultural heritage spatial distribution: Insights from Lushan County, China

Liu,

Du,

Bai

et al. 2024

Preprint

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Cultural heritage is a historical gift that connects the past and the present, carrying the material and cultural connotations of various historical periods. This study combines Bayesian modelling with geographic feature images to assess the general influence patterns and differential effects of drivers on the spatial distribution of cultural heritage in Lushan County. The results indicate that: (1) the hierarchical Bayesian model can effectively identify the potential heterogeneity of drivers across different heritage types and provide a quantification of the variations in the intensities of these drivers. (2) The spatial distribution of cultural heritage in Lushan County shows a "south-dense, north-sparse" pattern. The density of cultural heritage is generally negatively correlated with elevation, slope, and distances from water systems, settlements and cultural centers, while it is generally positively correlated with distance from geological hazard sites. (3) The effect of social factors on the spatial distribution of cultural heritage is significantly greater than that of natural factors, demonstrating that the formation and evolution of cultural heritage are profoundly shaped by human activities. (4) The effect of each driver varies in intensity for different types of cultural heritage, with significant differences in correlations. By comparing three Bayesian models, this study reveals the application potential of the hierarchical Bayesian model in research on the relationship between the spatial distribution of cultural heritage and its environment, with a view to providing data-driven methodological and theoretical references for research related to cultural heritage.

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Multiple Bayesian models approach to assessing drivers of cultural heritage spatial distribution: Insights from Lushan County, China

Liu,

Du,

Bai

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

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A GIS-based model for determining safety indices to evaluate the post-disaster usability of urban open and green spaces in Amasya City Center, Türkiye

Cited by 1 publication

References 19 publications

Multiple Bayesian models approach to assessing drivers of cultural heritage spatial distribution: Insights from Lushan County, China

Multiple Bayesian models approach to assessing drivers of cultural heritage spatial distribution: Insights from Lushan County, China

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