摘要
乡村旅游是乡村振兴与“双循环”背景下脱贫攻坚、推进乡村振兴和扩大内需的重要路径之一,而乡村旅游事业的发展离不开乡村旅游空间网络的构建,对其分析可为乡村旅游空间结构的优化提供实践指导和理论依据。环巢湖十二个乡镇的旅游空间互动模型网络中心性分析显示,环巢湖乡村旅游发展整体处于中等水平,三河镇构成较为突出的一极,乡村旅游发展初具规模,旅游进一步发展潜力大;旅游特征向量中心性值未出现较大变化,说明核心节点的辐射作用不足;旅游网络系统尚未健全,中心节点数量偏少,密度较低,有效连接性差。建议从空间结构上对环巢湖乡村旅游进行优化。
Rural tourism is one of the important ways to alleviate poverty,promote rural revitalization and expand domestic demand under the background of Rural Revitalization and“dual circulation”.The development of rural tourism is inseparable from the construction of rural tourism spatial network.An analysis of rural tourism can provide theoretical basis and practical guidance for the optimization of its spatial structure.The 12 towns around Chaohu Lake construct a tourism spatial interaction model,and a centrality analysis of the network shows that:The overall development of rural tourism around Chaohu Lake is at a medium level,and Sanhe Town stands out among the rest.Rural tourism has begun to take shape,with great potential for further development.There is no significant change in the tourism characteristic vector value,which indicates that the radiation effect of core nodes is insufficient.The tourism network system in this region leaves something to be desired,for example,the central nodes are small in number,low in density,and poor in effective connectivity.In view of these shortcomings,this paper puts forward some suggestions for the optimization of the spatial structure of rural tourism around Chaohu Lake.
作者
王汝幸
吴迪
张贺翔
张业臣
姚静静
李睿
WANG Ruxing;WU Di;ZHANG Hexiang;ZHANG Yechen;YAO Jingjing;LI Rui(School of Tourism and Exhibition, Hefei University, Hefei 230601, China;College of Architecture and Urban Planning, Suzhou University of Science and Technology, Suzhou 215129, China)
出处
《安徽农业大学学报(社会科学版)》
2021年第5期98-104,共7页
Journal of Anhui Agricultural University:SOC.SCI.
基金
安徽高校人文社会科学研究重点项目“环巢湖乡村旅游空间结构优化研究”(SK2019A0699)
合肥学院人才基金项目“大气环境污染对旅游行为的影响分析”(16-17RC33)。
关键词
环巢湖
空间互动模型
乡村旅游网络
网络中心性
around Chaohu Lake
spatial interaction model
rural tourism network
network centrality