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2018, 01, v.17;No.64 50-54+74
基于游客轨迹的景区智能辅助决策研究
基金项目(Foundation): 国家自然科学基金项目(41301514);; 南通市空间信息技术研发与应用重点实验室项目(CP12016005);; 江苏省大学生创新创业训练计划项目(201710304059Z)
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摘要:

以南通市啬园景区为实验样区,游客的行人轨迹为数据源,基于GIS空间技术,采用Voronoi方法,完成了景区的内部分区,及各分区不同时段的流量差异,给出了游客游览趋向.研究结果表明:游乐区、烧烤区作为游乐类和餐饮类功能性分区,客流量占整体的55%,属于热点区域;蝴蝶湖区、梅林区、花展区作为自然类观赏性分区,客流量共占整体的24%,客流量适中;茅亭区为服务类功能性分区,客流量占整体的5%,缺少较为完善的服务性设施,处于功能性分区与观赏性分区的过度地带;张謇墓区为人文类观赏性分区,客流量占整体的3%,客流量最少.对于功能性分区,应加强功能性建设,提高游乐设施的新颖性、多样性;对于观赏性分区,可利用其人文特性、自然特性,在固有设施的基础上完善其观赏性,提高景区的服务质量,从而增加景区的客流量,提升景区的核心竞争力.

Abstract:

Based on the tourist trajectory, a new method is proposed to study the tourist flow of Seyuan Park in Nantong by using GIS spatial analysis method. Voronoi Diagrams was used to divide the scenic area. Combined with pedestrians′ track, the traffic data were collected, managed, processed and analyzed in each district, statistic the flow differences between each partition in different periods, giving out tourist trend according to the pedestrian trajectory.The result of research revealed that recreation area, barbecue area as the recreation category and catering functional area, the passenger flow rate is 55%, the hot area; The butterfly lake district, merlin area and flower exhibition area are the natural ornamental areas. The passenger flow rate is 24%, the moderate passenger flow. As a functional partition of service, the thatched district with 5% of the total passenger flow, and there is no perfect service facility,which is in the excessive zone of functional zoning and ornamental partition. Zhangjian′s tomb area is a kind of humanistic ornamental area, with the passenger flow rate of 3% and the lowest passenger flow. For functional zone,Seyuan scenic area should strengthen the functional construction of the partition, improve the novelty and diversity of the district amusement facilities. To the appreciation of different emphasis on partition, on the basis of the proper facilities its cultural and natural features can be employed to complete its view and improve the service quality, thus more visitors will be attracted and core competitiveness will be enhanced.

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基本信息:

DOI:

中图分类号:F592.7

引用信息:

[1]盖宸德,周侗,孙晨星等.基于游客轨迹的景区智能辅助决策研究[J].南通大学学报(自然科学版),2018,17(01):50-54+74.

基金信息:

国家自然科学基金项目(41301514);; 南通市空间信息技术研发与应用重点实验室项目(CP12016005);; 江苏省大学生创新创业训练计划项目(201710304059Z)

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