云南省A级旅游景区与入境旅游质量的空间错位研究

入境旅游能够反映地区旅游业发展状况。根据空间错位理论,以云南省16个地市州为研究单元,借助重力模型及二维矩阵分析方法,探究了云南省A级旅游景区与入境旅游质量之间的空间错位问题。结果表明：(1)云南省A级旅游景区与入境旅游质量之间存在空间错位,二者重心错位0.11个经度,0.31个纬度。(2)云南省68.5%的地市州发生明显空间错位,集中连片分布呈东西向条带状贯穿整个省区,25%未发生明显错位的地市州呈团块状集中在云南省南部,东北部的昭通市未发生空间错位。(3)按照A级旅游景区丰度指数与入境旅游流流质指数组合划分的五种具体错位类型中,西双版纳州、红河州为双高区,普洱市、玉溪市、昭通市为双低区,昆明市、丽江市、大理州、迪庆州、保山市、楚雄州为顺向错位,怒江州、德宏州、临沧市、曲靖市、文山州为逆向错位;无中等错位州市。基于此,提出相应对策建议,为提升云南省入境旅游发展质量、促进云南省旅游业协调发展提供参考。     

边境地区旅游流空间场效应的时空动态及其影响因素——以云南省边境市州为例

基于地理集中指数、重心模型及旅游经济联系强度对2000—2016年云南省边境地区旅游流空间场效应的时空动态进行综合探究,并结合相关性系数法分析其影响因素.结果表明:(1)云南省边境各市州旅游场强层级区际差异显著,总体呈现以红河州为中心的单核分布模式;(2)旅游流重心总体呈现在波动中向东南方向偏移的态势,偏移速度总体呈现先快后慢的特征,各市州对旅游流吸引力的波动程度渐趋降低,但旅游吸引力空间差异在持续扩大;(3)西双版纳、普洱、红河及文山等市州形成了旅游经济联系高强度集聚区,怒江州与其他市州的旅游经济联系均较弱;各市州旅游经济联系总量表现出明显的"核心—边缘"式空间发展格局;(4)旅游资源禀赋、信息化水平、区域经济发展水平、交通通达性及旅游接待服务能力对旅游流空间场效应演化的影响程度依次递减,对外开放程度的影响程度最低.     

空间错位视角下江西省旅游发展时空演化研究

旅游资源、旅游设施和旅游服务是旅游发展的3大基本要素,旅游经济是旅游业发展以及旅游业在国民经济中重要地位的体现,据此构建了江西省旅游发展评价指标体系.基于熵权法、重力模型、旅游空间错位指数等方法结合ArcGIS可视化表达对2005～2015年江西省旅游发展进行评价,并对江西省旅游发展空间错位及时空演变过程进行分析.结果表明:1)在研究期内,江西省旅游资源、旅游设施、旅游服务和旅游经济的发展不均衡,各地市之间的差距都较大,但综合水平都不高,旅游设施成为江西省旅游发展的"短板",旅游资源逐渐成为影响江西省旅游均衡发展的关键;2)旅游资源和旅游经济重心整体向南迁移,旅游设施和旅游服务重心整体向北迁移,4个重心始终在江西省北部震荡徘徊,整体上呈现出布局分散的特点,而4个重心所形成的空间范围随着时间的演变在逐渐缩小;3)10 a间江西省旅游发展空间错位状况普遍存在且分异明显.高度错位区始终在江西省北部,错位程度逐渐南移,呈现出"北部凸显—中部凹陷—南部凸显"的空间布局演变特征.     

国家级夜间文旅消费集聚区与旅游收入空间错位分析

发展夜间旅游是延长旅游消费链、激发旅游经济活力的重要途径.以31个省（市、区）为研究样本，运用旅游空间错位指数、二维矩阵模型等数理方法，研究国家级夜间文旅消费集聚区与旅游收入空间错位关系，并利用ArcGIS软件将结果进行可视化表达.结果表明：(1)国家级夜间文旅消费集聚区、国内旅游收入与入境旅游收入三者间存在一定的空间错位现象；(2)集聚区与国内旅游收入总体空间错位较小，呈平衡状态；(3)集聚区与入境旅游收入空间错位较大，多数城市均处于匹配不佳阶段；(4)双收入重心空间错位差异明显，处于不同错位区的城市受限于不同的影响因素.基于以上分析结果，总结实际性发展建议，为我国夜间文旅产业发展提供有益参考.     

边疆省区旅游经济系统脆弱性评价、影响因素及其应对策略——以云南省为例

以云南省16个市州为研究单元,运用综合指数法及障碍度模型探究2004-2016年云南省各市州旅游经济系统脆弱性的时空格局演变特征及其影响因素.结果表明:(1)2004-2016年云南省各市州旅游经济系统脆弱性总体呈下降趋势,其绝对差异与相对差异均呈波动下降态势;(2)旅游经济系统脆弱性空间分布格局日益均衡,高脆弱性市州空间集聚态势明显,"核心—边缘"式空间结构逐渐形成,低脆弱性市州呈现"趋同俱乐部"空间态势,边境市州脆弱性低于内陆市州;(3)云南省六大旅游区旅游经济系统脆弱性均呈下降趋势,其中以滇西北下降幅度最大,滇东北与滇东南下降幅度较小;(4)敏感性对旅游经济系统脆弱性发挥主导作用,其应对能力的主要制约因素是基础设施建设滞后与区域经济对外开放程度偏低.     

东北地区旅游资源与旅游经济空间错位分析

以东北地区作为研究对象,采用重力模型和二维组合矩阵方法探究其旅游资源和旅游经济水平的空间错位问题.结果表明,东北地区的旅游资源重心和旅游经济重心均偏向南部.东北地区各地级市旅游资源和旅游经济水平的空间错位关系可以分为5种类型:大连市、哈尔滨市、长春市等属于最佳区;本溪市、抚顺市、辽阳市等属于中间区;辽源市属于双低区;丹东市、吉林市、盘锦市等属于正错位区;葫芦岛市、牡丹江市、伊春市等属于负错位区.针对不同空间错位类型提出了相对应的建议.     

游览人数-景区收入重心演变与空间错位分析——以新疆热门景区为例

以新疆69个热门景区为研究单元,运用重力模型刻画2010—2017年游览人数与景区收入时空演变轨迹,并结合空间错位指数模型度量二者的空间错位程度.结果表明,游览人数重心始终在"东南—西北"方向上回转与折返,并呈现三角板型空间特征.而收入重心轨迹沿"西南—东北—西—西南—东北"方向上折返后回转,呈"十"字型空间分布.游览重心总体向西南偏移11.82km;收入重心总体向西北移动46.70km.两类重心经纬度变化与其差值变化均显示新疆西部、北部地区景区竞争优势明显.43.48%的高、中错位区均以北部地区景区为主,其中那拉提、喀纳斯、国际大巴扎和天山天池景区ISM贡献度G值之和为50.5%,此为影响全局空间错位的关键区域.受新疆旅游资源产品转化程度、政府政策导向、景区产品差异化程度与景区管理能力差异等多方面影响,使二者空间格局发生变化,并出现错位分布的态势.     

福建省旅游收入与影响因素的空间错位分析

以福建省各设区市2019年旅游业发展的相关数据为研究对象,运用重力模型与二维矩阵模型对该省旅游收入及其影响因素进行空间错位分析,以期为区域旅游业协调发展提供参考.研究发现:从重力模型来看,旅游收入与资源、人口、经济、交通存在不同程度的空间错位现象.除A级旅游景区重心外,其他重心均位于几何中心的东南部.旅游收入与经济和交通的相关性更为显著,结合二维矩阵模型分析发现,各设区市空间错位状况存在同步与偏离两种类型,且旅游收入与资源、经济的空间错位分析中偏离区数量更为显著,而与交通这两种类型设区市数量基本相当.最后,根据位于不同区域的设区市提出相应对策.     

浙江省入境旅游流、旅游景区、星级酒店空间错位演化分析

运用重力模型和空间错位指数模型分别从宏观和微观两个方面对浙江省及11个地级市近10 a来的入境旅游流、旅游景区、星级酒店的空间错位进行分析.研究表明：近10 a来,从宏观上看：1)浙江省入境旅游流,旅游景区、星级酒店的重心均集中在绍兴市;2)三者之间的空间错位指数均不高于0.4,空间错位程度不明显,其中星级酒店－入境旅游流的空间匹配性最好,旅游景区－入境旅游流匹配性最弱;3)2007年是旅游景区与入境旅游流的空间错位指数转折点,2007年之后其匹配程度逐渐趋良好.从微观上看：1)整体而言,湖州的入境旅游流、旅游景区、星级酒店空间匹配性最好,而杭州最弱;2)2007年是部分地市在旅游景区－星级酒店和旅游景区－入境旅游流匹配度上的转折点,2007年之后这些地市的数值整体呈现下降的趋势,匹配逐渐趋于良好.     

新疆旅游资源与入境旅游质量的空间错位研究

以新疆14个地州市为研究对象,运用重力模型和二维矩阵模型,选取旅游资源丰度指数和入境旅游流流质指数作为空间错位评价指标,定量分析了新疆旅游资源与入境旅游质量之间存在的空间错位关系,结果表明:①新疆旅游资源与入境旅游流质量之间存在空间错位,两个重心错位2.13个经度,1.09个纬度。②新疆旅游资源与入境旅游流质量未发生明显空间错位的地州市成块状分布;发生明显空间错位的区域位于东部和南部;未发生空间错位的分布在中部。③空间错位可分成五种类型,其中双高区数量最少,正逆向区数量最多,双低区和正逆向区数量相当,缺少中等区。     

利用全局与局部相关函数分析流域降水空间变异性

为合理诊断流域降水的空间变异性,阐明了6种常见的全局和局部空间相关指标的联系与区别,并用空间相关函数进行统一表述,然后提出了同时从全局和局部2个方面对连续性与间断性并存的降水空间变异性进行综合分析的方法。采用全局半方差函数和局部Moran指数,对2003～2009年赣江流域降水空间变异规律进行了实例研究。结果表明:全局半方差函数便于描述流域降水的整体相关结构,而局部Moran指数可揭示降水的局部聚集形态和地带性规律,并能够诊断其中的奇异点。赣江流域年、月、日降水量在整体上呈显著的时变空间正相关性;在局部表现出较强的聚集性,并具有非平稳性和奇异性。同时,还初步指出了赣江流域降水空间变异性分析对于解释降水空间插值结果的作用。     

A Voronoi-based spatial algebra for spatial relations

Spatial relation between spatial objects is a very important topic for spatial reasoning, query and analysis in geographical information systems (GIS). The most popular models in current use have fundamental deficiencies in theory. In this paper, a generic algebra for spatial relations is presented, in which (i) appropriate operators from set operators (i.e. union, intersection, difference, difference by, symmetric difference, etc.) are utilized to distinguish the spatial relations between neighboring spatial objects; (ii) three types of values are used for the computational results of set operations-content, dimension and number of connected components; and (iii) a spatial object is treated as a whole but the Voronoi region of an object is employed to enhance its interaction with its neighbours. This algebra overcomes the shortcomings of the existing models and it can effectively describe the relations of spatial objects.     

A solution of spatial query processing and query optimization for spatial databases

Recently, attention has been focused on spatial query language which is used to query spatial databases. A design of spatial query language has been presented in this paper by extending the standard relational database query language SQL. It recognizes the significantly different requirements of spatial data handling and overcomes the inherent problems of the application of conventional database query languages. This design is based on an extended spatial data model, including the spatial data types and the spatial operators on them. The processing and optimization of spatial queries have also been discussed in this design. In the end, an implementation of this design is given in a spatial query subsystem.     

A solution of spatial query processing and query optimization for spatial databases

Recently,attention has been focused on spatial query language which is used to query spatial databases. A design of spatial query language has been presented in this paper by extending the standard relational database query language SQL. It recognizes the significantly different requirements of spatial data handling and overcomes the inherent problems of the application of conventional database query languages. This design is based on an extended spatial data model,including the spatial data types and the spatial operators on them. The processing and optimization of spatial queries have also been discussed in this design. In the end,an implementation of this design is given in a spatial query subsystem.     

基于GIS和空间句法的城市空间形态多尺度描述

空间拓扑关系是空间句法研究的基础．讨论了空间句法的系列变量,并以武汉市为例,提取武汉市的交通网络轴线地图,在GIS环境下讨论了不同尺度空间范围内的空间句法变量,得出空间可达性是评价城市空间形态的重要因子,而集成度是描述空间可达性的直接变量．利用空间句法变量可以进一步研究城市空间形态与人类活动的相互影响和相互关系。     

A solution of spatial query processing and query optimization for spatial databases

Recently, attention has been focused on spatial query language which is used to query spatial databases. A design of spatial query language has been presented in this paper by extending the standard relational database query language SQL. It recognizes the significantly different requirements of spatial data handling and overcomes the inherent problems of the application of conventional database query languages. This design is based on an extended spatial data model, including the spatial data types and the spatial operators on them. The processing and optimization of spatial queries have also been discussed in this design. In the end, an implementation of this design is given in a spatial query subsystem.     

乡村旅游空间分析与空间设计研究——以泰山马蹄峪为例

乡村旅游是目前比较受人欢迎的一种旅游形式。作为良好的旅游载体,乡村旅游空间越来越受到人们的重视。旅游空间是旅游者旅游过程中对景区的所有感受,引入建筑学中空间的概念,以泰山马蹄峪为例,对乡村的旅游空间进行分析和设计。     

A spatial entropy reflecting distribution of spatial objects

Decision trees are mainly used to classify data and predict data classes. A spatial decision tree has been designed using Euclidean distance between objects for reflecting spatial data characteristic. Even though this method explains the distance of objects in spatial dimension, it fails to represent distributions of spatial data and their relationships. But distributions of spatial data and relationships with their neighborhoods are very important in real world. This paper proposes decision tree based on spatial entropy that represents distributions of spatial data with dispersion and dissimilarity. The rate of dispersion by dissimilarity presents how related distribution of spatial data and non-spatial attributes. The experiment evaluates the accuracy and building time of decision tree as compared to previous methods and it shows that the proposed method makes efficient and scalable classification for spatial decision support.     

Federated spatial databases and interoperability

It is a period of information explosion. Especially for spatial information science, information can be acquired through many ways, such as man-made planet, aeroplane, laser, digital photogrammetry and so on. Spatial data sources are usually distributed and heterogeneous. Federated database is the best resolution for the share and interoperation of spatial database. In this paper, the concepts of federated database and interoperability are introduced. Three heterogeneous kinds of spatial data, vector, image and DEM are used to create integrated database. A data model of federated spatial databases is given.     

A spatial entropy reflecting distribution of spatial objects

Decision trees are mainly used to classify data and predict data classes. A spatial decision tree has been designed using Euclidean distance between objects for reflecting spatial data characteristic. Even though this method explains the distance of objects in spatial dimension, it fails to represent distributions of spatial data and their relationships. But distributions of spatial data and relationships with their neighborhoods are very important in real world. This paper proposes decision tree based on spatial entropy that represents distributions of spatial data with dispersion and dissimilarity. The rate of dispersion by dissimilarity presents how related distribution of spatial data and nonspatial attributes. The experiment evaluates the accuracy and building time of decision tree as compared to previous methods and it shows that the proposed method makes efficient and scalable classification for spatial decision support.