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<p>In this paper, in the context of red cultural heritage, GIS technology is firstly utilized to comprehensively classify the resources of the Long March National Cultural Park, including natural, humanistic and recreational resources in various aspects. Through spatial distribution assessment, the distribution characteristics of each type of resource in the park are revealed. Subsequently, the degree of influence of spatial differentiation of resources was calculated by selecting influencing factors with multi-dimensional considerations. Finally, multiple regression analysis was utilized to establish a quantitative model that assesses the degree of influence of each factor on the spatial differentiation of resources. Among the spatial differentiation influencing factors, market demand and natural factors had the highest weights, 0.5584 and 0.3588, respectively. In addition, it was proved that air quality and comfort had a high significance level of P&lt;0.05, which highlighted the importance of the climate environment. Meanwhile, the positive correlation between the number of scenic spots above the 3A level and trade volume and spatial structure, GDP as well and tourism income highlights the positive influence of red cultural heritage on the spatial differentiation of tourism resources.</p>
</abstract>

In this paper, in the context of red cultural heritage, GIS technology is firstly utilized to comprehensively classify the resources of the Long March National Cultural Park, including natural, humanistic and recreational resources in various aspects. Through spatial distribution assessment, the distribution characteristics of each type of resource in the park are revealed. Subsequently, the degree of influence of spatial differentiation of resources was calculated by selecting influencing factors with multi-dimensional considerations. Finally, multiple regression analysis was utilized to establish a quantitative model that assesses the degree of influence of each factor on the spatial differentiation of resources. Among the spatial differentiation influencing factors, market demand and natural factors had the highest weights, 0.5584 and 0.3588, respectively. In addition, it was proved that air quality and comfort had a high significance level of P<0.05, which highlighted the importance of the climate environment. Meanwhile, the positive correlation between the number of scenic spots above the 3A level and trade volume and spatial structure, GDP as well and tourism income highlights the positive influence of red cultural heritage on the spatial differentiation of tourism resources.

Analysis of Spatial Differentiation of Resources and Their Influencing Factors in Long March National Cultural Park in the Context of Red Cultural Heritage

Fuzhou University of International Studies and Trade

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In this paper, in the context of red cultural heritage, GIS technology is firstly utilized to comprehensively classify the resources of the Long March National...

Analysis of Spatial Differentiation of Resources and Their Influencing Factors in Long March National Cultural Park in the Context of Red Cultural Heritage

Publicado en línea: 11 dic 2023

Páginas: -

Recibido: 13 feb 2023

Aceptado: 21 jun 2023

DOI: https://doi.org/10.2478/amns.2023.2.01430

Palabras clave
Red cultural heritage, GIS technology, Spatial distribution, Dimensional considerations, Multiple regression analysis

© 2023 Yun Gao, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Analysis of Spatial Differentiation of Resources and Their Influencing Factors in Long March National Cultural Park in the Context of Red Cultural Heritage

Publicado en línea: 11 dic 2023

Páginas: -

Recibido: 13 feb 2023

Aceptado: 21 jun 2023

DOI: https://doi.org/10.2478/amns.2023.2.01430

Palabras claveRed cultural heritage, GIS technology, Spatial distribution, Dimensional considerations, Multiple regression analysis

© 2023 Yun Gao, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
Red cultural heritage, GIS technology, Spatial distribution, Dimensional considerations, Multiple regression analysis