河南省重点旅游城市入境旅游网络特征研究——基于流空间视角
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摘要
本文以流空间为视角,以高等级景区的空间分布为基础数据,借助Arc GIS分析河南省重点旅游城市入境旅游网络空间结构和节点等级体系。结果表明空间网络结构的演变形成了"钻石型"→"跳跃型"→"T型"→"直线型"→"三角形"→"网格型"的趋势,由几个中心点发起,然后以这些中心点为中心向外围辐射然后蔓延所有区域。入境旅游流的强度在空间上形成了"一带一点"格局,以郑汴洛旅游带为核心,外围形成南阳1个极核。旅游流强度的分布呈现出右偏态状态,以平均数的众数为中心,大多数旅游流在距离该中心的远距离外围区域呈集聚状态,而且河南省入境旅游流联系强度整体处于较低水平。重点旅游城市入境旅游网络节点在空间上呈现出明显的层次性和等级性,同时层次和等级的节点呈现出大致均匀分布的状况,且每个层次和等级城市数目基本保持一致。
In the perspective of flow space, on the basis of high grade scenic spot in the spatial distribution of data, with the Arc GIS analysis of inbound tourism the key tourist city of Henan province network spatial structure system and node level. Results show that the first inbound tourism flow due to the high, medium and low intensity of nine major cities inbound tourism flows spatial network structure intensity differences, caused the evolution of the space network structure formed a "diamond" → "jumping" → "T" → "linear" → "triangle" → the trend of "grid", initiated by several central point, and then to the center of radiation as the center to the periphery and then spread to all areas, the strength of the inbound tourism flow formed the "area" on the space pattern, zheng Bian Luo tourism zone as the core, periphery to form a polar nuclei, nanyang tourism flow intensity distribution presents the right state of skewness, on average the number, most of the tourist flow in distance from the center of the peripheral region of agglomeration state over a long distance, and the flow of inbound tourism in Henan province contact strength at a lower level; Second, key tourist cities inbound tourism network node in space presents obvious hierarchy and level, the focus of the four different levels and level entry tourism city nodes in regional inbound tourism network connection respectively play center, center, place the center of the inbound tourism network connection and the general role of inbound tourism node. At the same time, the nodes of the four levels and levels show a roughly uniform distribution, and the number of cities at each level and level is roughly the same.
In the perspective of flow space, on the basis of high grade scenic spot in the spatial distribution of data, with the Arc GIS analysis of inbound tourism the key tourist city of Henan province network spatial structure system and node level. Results show that the first inbound tourism flow due to the high, medium and low intensity of nine major cities inbound tourism flows spatial network structure intensity differences, caused the evolution of the space network structure formed a "diamond" → "jumping" → "T" → "linear" → "triangle" → the trend of "grid", initiated by several central point, and then to the center of radiation as the center to the periphery and then spread to all areas, the strength of the inbound tourism flow formed the "area" on the space pattern, zheng Bian Luo tourism zone as the core, periphery to form a polar nuclei, nanyang tourism flow intensity distribution presents the right state of skewness, on average the number, most of the tourist flow in distance from the center of the peripheral region of agglomeration state over a long distance, and the flow of inbound tourism in Henan province contact strength at a lower level; Second, key tourist cities inbound tourism network node in space presents obvious hierarchy and level, the focus of the four different levels and level entry tourism city nodes in regional inbound tourism network connection respectively play center, center, place the center of the inbound tourism network connection and the general role of inbound tourism node. At the same time, the nodes of the four levels and levels show a roughly uniform distribution, and the number of cities at each level and level is roughly the same.
引文
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(4)Demdder B,Witlox F,Faulconb Tidge,Jetal.Airline Data for Global City Network Research:Reviewing and Refining Existing Approches[J].Geojournal,2008,71(1):5-18.
(5)Hui T K,Yuen C C.A Study in the Seasonal Variation of Japanese Tourist Arrivals in Singapore[J].Tourism Management,2002,23(2):127-131.
(6)马晓龙.西安旅游区入境旅游时空演变及系统调控人文地理[J].2006,21(4):88-93.
(7)赵伟.福建省入境旅游流时空演变研究[J].泉州师范学院学报(自然科学版),2009,27(6):85-88.
(8)Lim C.The Major Determinants of Korean Outbound Trvavel to Australia[J].Mathematic and Computer in Simulation,2004,64(3):477-485.
(9)Pearce DG.Tourism Today:AGeographical Analysis[M].2nd ed.Hong Kong:Longman Scientific&Technical,1995.
(10)马耀峰,李永军.中国入境后旅游流的空间分布研究[J].人文地理,2001,16(6):44-46.
(11)刘宏盈.长三角入境旅游流西向扩散效应分析—以向陕西扩散为例[J].地域研究与开发,2010,29(4):93-98.
(12)任瑞萍,吴晋峰,王奕琪,等.旅华美国旅游流地理分布和网络结构特征研究[J].地域研究与开发,2013,32(5):144-150.
(13)Song H,Witt S F.Forcasting International Tourist Flows to Macau[J].Tourism Management,2006,27(2):214-224.
(14)雷可为,陈瑛.基于BP神经网络和ARIMA组合模型的中国入境游客量预测[J].旅游学刊,2007,22(4):20-25.
(15)Prideaux B.Factors Affecting Bilateral Tourism Flows[J].Annals of Tourism Research,2005,32(3):780-801.
(16)王洁洁,孙根年.20年来大陆-香港关系及重大事件对两岸旅游互动的影响分析[J].经济地理,2010,30(2):317-323.
(17)董亚娟,马耀峰,李振亭等.西安入境旅游流与城市旅游环境耦合协调关系研究[J].地域研究与开发,2013,32(1):98-101.
(18)郑鹏,马耀峰,王洁洁等.基于“推-拉”理论的美国旅游者旅华流动影响因素研究[J].人文地理,2010,25(5):112-117.
(19)高军,吴必虎,马耀峰.旅华英国游客O-D旅游客流动力机制研究[J].旅游学刊,2011,26(2):35-40.