地图数据的空间关系与数据模型

详细论述了地图数据及其空间关系、地图数据的几何与属性的关系以及地图要素空间关系的建立与地图要素完整性之间的关系.提出了解决由于地图要素分层管理所带来空间关系分割问题和多图幅之间空间关系连接的方法.最后给出了基于地图数据空间关系的数据模型.     

地图数据的空间关系与数据模型

详细论述了地图数据及其空间关系,地图数据的几何与属性的关系以及地图地素空间关系的建立与地图要素完整性之间的关系。提出了解决由于地图要素分层管理所带来空间关系分割问题和多图幅之空关系连接的方法,最后给出了基于地图数据空间关系的数据模型。     

用专家系统技术确定地图要素的地图符号类型

地图要素与地图符号类型之间的关系长期被人们忽略。但它确是专题地图设计专家系统中不可缺少的重要环节,是地图符号设计的基础。本文给出了地图要素类型和地图符号类型的定义,详细阐述了两者之间的关系;作者用Turbo Prolog2.0语言在COMPAQ 386微机上建立的地图要素的地图符号类型确定专家系统模块,可以对一幅地图上各种类型的地图要素确定其地图符号类型,为下一步具体的符号设计工作打下了良好的基础。     

地图图形目标之间基本空间关系抽象的规律

以地图自动综合为目的,定义了空间目标的几种基本空间关系.总结了道路、水系、居民地等要素之间存在的典型空间关系,着重讨论了它们之间空间关系抽象的规则,为地图自动综合中有效保持空间关系的一致性提供必要的理论基础.     

地图空间关系认知元素分析

分析了目前地图空间认知的几种理论研究.从地图学史的角度出发,应用几幅著名的中外古地图,指出符号、注记以及空间拓扑关系在地图发展变化中的不变性,认为这3种元素构成了地图空间关系认知的基本元素,并分析了这3种元素在地图空间关系构建方面所起的作用.最后提出了在网络环境下,这3种元素在大众制图中的指导意义.     

基于空间关系认知的新模式地图设计——以路网构架图表达“一带一路”路线为例

地图所要表达的空间结构通常通过空间关系来建构和描述,包括距离关系、方向关系和拓扑关系。本文基于空间关系认知,从定名量表、顺序量表、间隔量表、比率量表4个量表分析了传统地图与新模式地图的空间关系分辨率的变化过程,并以路网架构图为例,对比了传统地图与新模式地图的认知效果,提出在制图中要重视认知效率和表现对象的细节程度。     

澜沧江流域(云南段)人口密度空间自相关分析

本文介绍了空间自相关的理论方法,利用澜沧江流域(云南段)人口分布数据计算了MoranI和Local Moran I.详细论述了自相关分析的技术路线,对人口分布的空间特征进行研究探讨,把GIS技术的空间拓扑关系及可视化制图功能等很好地融合于地理现象的空间模式中,分析了研究区域人口分布的时空特征,反映了该区域人口地理分布的...     

地图数据中的信息挖掘

将数据挖掘运用到地图数据中，从地图数据中挖掘出多方面的知识。通过统计分析可以研究各种现象在空间或一定时间范围内存在的变异、相互关系，从中找出事物内部的规律；通过统计分析可以研究各种现象的空间分布规律，相互联系，动态变化，建立各种数学模型等。     

保持空间分布特征的群点化简方法

群点目标隐含的空间结构化信息是空间分布分析、地图综合感兴趣的内容。对群点目标分布的信息内容区分为存在性、度量结构与拓扑结构，在Delaunay三角网及其对偶Voronoi图模型上对工量结构定义4个在量；分布范围、分布密度、分布中心及分布轴线，顾及视觉识别Gestalt邻近原则，运用三角形“剥皮”法，确立了非凸多边形所表达的群点分布范围，运用图像灰度表达群点分布密度并通过图像处理方法提取分布中心。建立了Voronoi图动态重建进行群点化简的方法，该方法通过边界点和内部点的分开处理，较好地保持了4个空间分布特征。     

2维矢量地图空间目标关系的组合式表达

矢量模式的地图平面空间目标是地图数据处理中常见的,其空间关系的描述与处理非常重要本文首先分析了平面地图上的尺度空间和拓扑空间的统一,以及点和直线段两两相互间的基本空间关系,并以这些基本窨绵组合为基础,试图利用组合式方法区分和描述地图空间点状、线状和面状空间目标两两相互间的空间关系,且得到各类空间关系的种数。     

半方差函数与Moran’s I在土壤微量元素空间分布研究中的应用——以寿光市为例

利用半方差函数与Moran’s I两种空间分析方法,研究了山东省寿光市土壤中微量元素的空间分布特征,以探讨不同空间分析方法的差异性与准确性。结果表明,无论表层土壤还是深层土壤,半方差函数分析得到的土壤微量元素的空间相关距离大约为20~60 km,而空间自相关图获得的正自相关距离为20~25km,负自相关距离为25~55 km。除深层土壤中的Zn元素外,其他元素均达到了显著的自相关水平。空间自相关方法对土壤微量元素空间相关性的判断要优于半方差函数法。     

Full Positional Accuracy Analysis of Spatial Data by Means of Circular Statistics

The positional error in spatial data is defined as a vector by comparing the coordinates between the true position and the measured position. The standard tests to assess the positional accuracy use only the magnitude of the vector and omit the azimuth. This article suggests that the use of both values allows a much more complete analysis of the positional error. A set of tests is proposed that are relevant for this purpose and demonstrate that some important features are not identified by the common procedures. The test samples come from two datasets. The first is obtained from the comparison of 100 homologous points in two conventional maps, and the second one comes from the geometric calibration of a photogrammetric scanner. The results are analyzed and discussed, showing that important issues such as error anisotropy are detected only by means of the circular statistics tests and density maps of distribution. Therefore, tests that assess the goodness of fit for uniform distribution in azimuths, such as Rayleigh and Rao tests, give low probabilities (P = 0 and P > 0.01). Moreover, density maps working with both magnitude and angle can locate the outlier candidate and offer more information about the spatial distribution of error.     

Positional Accuracy of Spatial Data: Non-Normal Distributions and a Critique of the National Standard for Spatial Data Accuracy

Spatial data quality is a paramount concern in all GIS applications. Existing spatial data accuracy standards, including the National Standard for Spatial Data Accuracy (NSSDA) used in the United States, commonly assume the positional error of spatial data is normally distributed. This research has characterized the distribution of the positional error in four types of spatial data: GPS locations, street geocoding, TIGER roads, and LIDAR elevation data. The positional error in GPS locations can be approximated with a Rayleigh distribution, the positional error in street geocoding and TIGER roads can be approximated with a log‐normal distribution, and the positional error in LIDAR elevation data can be approximated with a normal distribution of the original vertical error values after removal of a small number of outliers. For all four data types considered, however, these solutions are only approximations, and some evidence of non‐stationary behavior resulting in lack of normality was observed in all four datasets. Monte‐Carlo simulation of the robustness of accuracy statistics revealed that the conventional 100% Root Mean Square Error (RMSE) statistic is not reliable for non‐normal distributions. Some degree of data trimming is recommended through the use of 90% and 95% RMSE statistics. Percentiles, however, are not very robust as single positional accuracy statistics. The non‐normal distribution of positional errors in spatial data has implications for spatial data accuracy standards and error propagation modeling. Specific recommendations are formulated for revisions of the NSSDA.     

Mapping of Soil Micronutrients in Kashmir Agricultural Landscape Using Ordinary Kriging and Indicator Approach

Soil nutrient maps based on intensive soil sampling are useful to adopt site-specific management practices. Geostatistical methods have been widely used to determine the spatial correlation and the range of spatial dependence at different sampling scales. If spatial dependence is detected, the modeled semivariograms can then be used to map the interested variable by kriging, an interpolation method that produces unbiased estimates with minimal estimation variance. The objectives of this paper were to examine and map the spatial distribution of the soil micronutrients Cu, Zn, Fe and Mn on an agricultural area in Kupwara, J&K, under temperate climatic conditions. The ordinary kriging was first used to determine the values for the non-sampled locations, and then the indicator approach was used to transform the micronutrient content values into binary values having the mean values of each nutrient as the threshold content. All four elements analyzed showed spatial dependence using the indicator semivariograms. The strength of spatial dependence was assessed using the values of nugget effect and range from the semivariogram, the fitted range values decreased in the order Zn > Cu > Mn > Fe. The spatial dependence of the combination of two or more of the studied micronutrients was also examined using indicator semivariograms. In opposition to spatial analysis of individual microelements, indicator semivariograms obtained for the binary coding of the variables showed a great nugget effect value or a low proportion of sill. The maps for each nutrient obtained using indicator kriging showed some similarity in the spatial distribution, suggesting the delimitation of uniform management areas.     

顾及地图要素级别的几何信息量量测方法

类型和级别是作为地图要素表达的重要方式,但将其引入地图信息量量算是很困难的。本文在总结了传统量测方法不足的基础上,利用加权Voronoi图的空间划分特性,用各生成元面积比重新定义了熵的计算公式,基于经典信息量量算方法提出一种多级要素地图几何信息量量测方法;同时指出对多类地物应独立计算信息量。实验表明,该方法符合熵的相关结论,同时符合人的空间认知特性。     

面向双/多变量的连续面域拓扑图可视化方法

面域拓扑图是一种利用区域面积大小定量表达区域属性信息的可视化方法。由于其区域面积本身已经表示某一变量，因此这更有利于双/多变量的制图表达。针对目前基于面域拓扑图的双/多变量表达方法中存在的难以表达相邻区域之间基本状况和不利于不同地理现象的空间分布规律及差异表达的问题，本文提出一种面向双/多变量的连续面域拓扑图可视化方法。首先通过格网密度补偿和积分步长逐步试探的方法对基于扩散模型的连续面域拓扑图生成算法进行部分优化，完成基本变量的表达，然后分别通过空间内插和符号扩展完成第2和第3变量在连续面域拓扑图中的表达。最后以慕尼黑市人口密度和银行/ATM分布（双变量）数据以及奥格斯堡市人口密度数据、幼儿园分布以及规模数据（多变量）为试验数据进行可视化，并通过实证分析验证了该方法的有效性和优越性。