中国红色旅游经典景点空间分布格局及其影响因素异质性

红色旅游是传承革命文化、推动爱国主义教育常态化和大众化、促进革命老区经济发展的重要方式。通过构建理论分析框架系统,综合运用多种空间分析方法与回归模型,对中国公布的300处红色旅游经典景区共763个景点的空间分布格局及影响因素异质性进行研究,并提出发展模式及对策。研究表明：（1）经典景点空间分布受资源、环境、社会和经济四大子系统综合影响;（2）核心区空间分布较其他旅游景区分散,形成7个一级核心区、7个及两大连片二级核心区、低密度与较低密度区等,空间关联性差异较大,关联效应伴随空间尺度缩小而减弱;（3）空间分布影响因素异质性明显,影响程度为红色旅游资源>海拔>政策力度>坡度>交通设施>市场需求>资源联动>消费水平;（4）提出采取网络、节点、廊道、共生—联动、跨区共促等发展模式及对策。研究可为红色旅游发展与管理、跨区联合等提供科学决策依据。

Spatial distribution pattern of classic red tourism scenic spots and heterogeneity of its influencing factors in China

Red tourism, as an important way to inherit revolutionary culture, can promote the patriotism education publicly and improve the economic development of old revolutionary areas. This paper studies the spatial distribution and heterogeneity of influencing factors of 763 scenic spots in 300 published red tourism classic attractions of China, by constructing a theoretical framework system, spatial analysis methods and regression models, so as to put forward the development mode and countermeasures. The results show that: (1) The spatial distribution of classic red tourism scenic spots is affected by four subsystems: resources, environment, society and economy. (2) In terms of spatial distribution, the core areas are more dispersed compared with other tourist attractions, which presents a pattern of seven first-class core areas, seven second-class core areas, two contiguous second-class core areas, low-density, lower-density areas and so on. The spatial correlations are quite different, and the correlation effect weakens with the reduction of spatial scale. (3) The influencing factors of classic red tourism scenic spots are different in different regions. The influence degree is red tourism resources > altitude > policy intensity > slope > transportation facilities > market demand > resource linkage > consumption level. (4) In the future, the construction of classic red tourism scenic spots should focus on the development mode and countermeasures of network, node, corridor, symbiosis linkage and cross-regional coordination. The conclusions can provide scientific decision-making basis for the red tourism development, management and cross-regional cooperation.