Entropy error model of planar geometry features in GIS

Positional error of line segments is usually described by using “g-band”, however, its band width is in relation to the confidence level choice. In fact, given different confidence levels, a series of concentric bands can be obtained. To overcome the effect of confidence level on the error indicator, by introducing the union entropy theory, we propose an entropy error ellipse index of point, then extend it to line segment and polygon, and establish an entropy error band of line segment and an entropy error donut of polygon. The research shows that the entropy error index can be determined uniquely and is not influenced by confidence level, and that they are suitable for positional uncertainty of planar geometry features.     

GIS中面元的误差熵模型

根据整个线元边缘分布的平均信息熵确定了“ε－带”的宽度，提出了线元的平均误差熵带模型，进一步扩展到面元的误差熵环模型。误差熵环的带宽取构成边界线的各线段误差熵的加权平均值。最后通过算例比较了面元的误差熵环和误差环模型，绘出了它们的可视化图形，得出了一些有益的结论。     

GIS中线元的误差熵带研究

基于现有的线元位置不确定性模型大多与置信水平的选取有关,而置信水平的选取带有一定程度的主观性,因而不能惟一确定。引入信息熵理论,提出了线元的误差熵带模型,并将它与"E-带"进行了比较,计算了落入其内的概率。该模型根据联合熵惟一确定,与置信水平的选取无关。     

误差熵不确定带模型

本文从信息论的基本理论出发，通过熵的极值定理和引入误差熵的概念 ，首次提出了误差熵不确定带模型。该模型与以往的误差模型有着本质的区别。它不是任何意义上的置信带，而是一种完全确定的，与置信水平无关的不确定带模型。     

GIS中随机误差点位不确定性描述法研究

考虑到G IS分析决策时后续计算的简便性,以及不确定性描述的简单性,本文罗列了点位精度描述的多种方法,包括数学描述以及计算置信度的方法,用直观的二维(三维)图形对抽象的点位质量可视化,并进行分析比较。为简化各种描述点位精度的置信度计算,以采用k值所对应的描述误差椭圆的概率值为置信度为前提,对各种描述方法进行分类和比较,得出结论:在各种描述点位精度的方法中,点位均方向误差和误差区间,形式很简单,容易描述和参与计算。其中,点位均方向误差和区间表示法具有较强的实用性、简易性、灵活性、优势互补性,很适合来描述G IS中随机误差点位不确定性。     

GIS中三维空间直线的误差熵模型

从信息熵的角度提出了三维空间直线的误差熵模型，该模型由以垂直直线的平面误差熵为半径的圆柱体和两端点的误差球组成，是一种完全确定的度量空间线元不确定性的模型。理论分析与实验表明，本文所提出的模型具有较好的效果。     

Positional error curves band of a planar line segment within GISs

1 Introductionffe well-for Meanboha Eno(MSRE),having advanop of talculang ndy,has bo widdyed to m the W of pont ednates inGIS' NY and gedop. N, it is Me tDtw the opiW eno Of a pont in whitw dirm-tion, while in praedce there is ned tO for the value ofghH or Of a trint in a peial boon SUCh asthe uha diW. The or curve of a glnt is ableto W twl the diAnbution wttiOn of twnt eno.ln an arbtw dich and it is the nd efhaive edfor dedbing forhed rm Of odnts in SUrVopng..mpneenng(Mithel, 1983…     

A general framework for error analysis in measurement-based GIS Part 1: The basic measurement-error model and related concepts

This is the first of a four-part series of papers which proposes a general framework for error analysis in measurement-based geographical information systems (MBGIS). The purpose of the series is to investigate the fundamental issues involved in measurement error (ME) analysis in MBGIS, and to provide a unified and effective treatment of errors and their propagation in various interrelated GIS and spatial operations. Part 1 deals with the formulation of the basic ME model together with the law of error propagation. Part 2 investigates the classic point-in-polygon problem under ME. Continuing to Part 3 is the analysis of ME in intersections and polygon overlays. In Part 4, error analyses in length and area measurements are made. In this present part, a simple but general model for ME in MBGIS is introduced. An approximate law of error propagation is then formulated. A simple, unified, and effective treatment of error bands for a line segment is made under the name of covariance-based error band. A new concept, called maximal allowable limit, which guarantees invariance in topology or geometric-property of a polygon under ME is also advanced. To handle errors in indirect measurements, a geodetic model for MBGIS is proposed and its error propagation problem is studied on the basis of the basic ME model as well as the approximate law of error propagation. Simulation experiments all substantiate the effectiveness of the proposed theoretical construct.This project was supported by the earmarked grant CUHK 4362/00H of the Hong Kong Research grants Council.     

线元点位误差带的“纺锤形”模型

对当前GIS界流行的以点位误差描述线元位置不确定性的误差带理论提出相反的观点。最早提出的线元误差带理论为"ε-带"模型,后来又提出了"E-带"模型和在其基础上发展的"G-带"模型。后两者均认为以控制点点位误差描述的线元的误差带的基本形状呈"哑铃"形,即认为线元上端点的位置不确定性大于端点之间的点的位置不确定性。笔者的看法与此相反,笔者认为线元上两控制点之间的点的位置不确定性应大于控制点的位置不确定性,且在两控制点的中间达到最大,即线元误差带的基本形状应为"纺锤形"而不是"哑铃形"。     

A general framework for error analysis in measurement-based GIS Part 2: The algebra-based probability model for point-in-polygon analysis

This is the second paper of a four-part series of papers on the development of a general framework for error analysis in measurement-based geographic information systems (MBGIS). In this paper, we discuss the problem of point-in-polygon analysis under randomness, i.e., with random measurement error (ME). It is well known that overlay is one of the most important operations in GIS, and point-in-polygon analysis is a basic class of overlay and query problems. Though it is a classic problem, it has, however, not been addressed appropriately. With ME in the location of the vertices of a polygon, the resulting random polygons may undergo complex changes, so that the point-in-polygon problem may become theoretically and practically ill-defined. That is, there is a possibility that we cannot answer whether a random point is inside a random polygon if the polygon is not simple and cannot form a region. For the point-in-triangle problem, however, such a case need not be considered since any triangle always forms an interior or region. To formulate the general point-in-polygon problem in a suitable way, a conditional probability mechanism is first introduced in order to accurately characterize the nature of the problem and establish the basis for further analysis. For the point-in-triangle problem, four quadratic forms in the joint coordinate vectors of a point and the vertices of the triangle are constructed. The probability model for the point-in-triangle problem is then established by the identification of signs of these quadratic form variables. Our basic idea for solving a general point-in-polygon (concave or convex) problem is to convert it into several point-in-triangle problems under a certain condition. By solving each point-in-triangle problem and summing the solutions, the probability model for a general point-in-polygon analysis is constructed. The simplicity of the algebra-based approach is that from using these quadratic forms, we can circumvent the complex geometrical relations between a random point and a random polygon (convex or concave) that one has to deal with in any geometric method when probability is computed. The theoretical arguments are substantiated by simulation experiments.This project was supported by the earmarked grant CUHK 4362/00H of the Hong Kong Research grants Council.     

GIS中空间数据不确定性的混合熵模型研究

基于信息理论和模糊集合理论，针对GIS中部分空间数据既具有随机性又具有模糊性的特点，建立了空间数据不确定性的混合熵模型。以GIS中线元不确定性为例，讨论了线元不确定性的统计熵、模糊熵和混合熵估计方法，并针对特例给出了线元不确定性的熵带分布。     

General Entropy Model of Line Segments Uncertainty in GIS

Spatial data uncertainty can directly affect the quality of digital products and GIS-based decision making. On the basis of the characteristics of randomicity of positional data and fuzziness of attribute data, taking entropy as a measure, the stochastic entropy model of positional data uncertainty and fuzzy entropy model of attribute data uncertainty are proposed. As both randomic-ity and fuzziness usually simultaneously exist in linear segments, their omnibus effects are also investigated and quantified. A novel uncertainty measure, general entropy, is presented. The general entropy can be used as a uniform measure to quantify the total un-certainty caused by stochastic uncertainty and fuzzy uncertainty in GIS.     

熵理论在确定点位不确定性指标上的应用

分析了传统点位不确定性指标的局限性，基于信息论中的联合熵和最大熵定理导出了n维随机点熵不确定指标以及落入其内概率的统一公式；提出了以熵误差椭圆与熵误差椭球作为2维、3维GIS中点元的位置不确定性度量指标。提出的熵指标具有唯一确定、不受置信水平选取的主观性影响等特点，适合于度量未知分布的点位不确定性。     

GIS中平面面位误差环的解析模型

本文基于随机场理论,导出了随机面元的分布函数和概率密度函数。为了衡量随机面元的位置不确定性,将点位误差椭圆和线位误差带进一步扩展到面位误差环指标。根据推求包括线的原理,导出了多边形面位误差环边界线的解析表达式,并分析了面位误差环的构成机理,证明了误差环边界线为连续闭合曲线的结论。最后通过实例绘制了面位误差环的可视化图形。     

General Entropy Model of Line Segments Uncerta,nty in GIS

Spatial data uncertainty can directly affect the quality of digital products and GIS-based decision making. On the basis of the characteristics of randomicity of positional data and fuzziness of attribute data, taking entropy as a measure, the stochastic entropy model of positional data uncertainty and fuzzy entropy model of attribute data uncertainty are proposed. As both randomicity and fuzziness usually simultaneously exist in linear segments, their omnibus effects are also investigated and quantified. A novel uncertainty measure, general entropy, is presented. The general entropy can be used as a uniform measure to quantify the total uncertainty caused by stochastic uncertainty and fuzzy uncertainty in GIS.     

点位落入误差椭圆的概率检验

在母体为一维正态分布的随机子样中,可以检验子样的方差、期望,将此方法推广至二维正态分布的子样检验.通过实测,得出一组随机点位(x,y).检验方法是:在给定的王信度下,检验(x,y)是否落入误差椭圆内,如果其值超过给定概率,则舍弃原假设.此检验适用于一组点位观测数据P(xi,yi)中剔除不合格的点位观测值.     

GIS 中基本几何要素的置信区域问题研究

以概率论为工具解析地研究了误差椭圆的2个重要性质，在此基础上分别为点、线及多边形建立了由椭圆和线段组成的置信域，并给出了所建置信域与其置信水平的关系。最后通过算例讨论了置信域的可视化表示问题。     

GIS中曲线误差带模型的一种算法

针对GIS中对曲线位置不确定性分析的要求,提出了一种采用数值方法计算拟合曲线点位误差的算法,给出了确定GIS中任意曲线误差带模型的具体计算步骤与计算公式,并结合实例,绘制了三次样条拟合曲线的误差带。     

矢量GIS空间随机线元等概率密度误差模型

从空间解析几何学的角度,基于平面随机线元等概率密度误差模型建模原理,研究了矢量GIS空间随机线元位置不确定性误差模型的建模原理,提出并证明了“空间线元上任意点Pt处用以构建空间线元等概率密度误差模型体的误差椭球三轴长在数值上等于相应空间点处标准误差椭球对应三轴长的[m(λA,t)]2倍,且该空间点处误差椭球三轴线各自对应的空间向量方位保持不变”的重要结论,这对于矢量GIS空间线状实体位置不确定性误差模型的建模具有指导意义。     

矢量GIS平面一般曲线误差模型定位精度

基于等概率密度误差模型建模原理和数值算法,研究矢量GIS平面一般曲线误差模型定位精度,给出定位精度捕述指标,并通过实例计算与分析,得出使川误差模型平均带宽比使用误差模型面积更能反应一般曲线的真实精度的结论,便于指导生产与应用。