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。     

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。     

非线性模型的误差传播及其在GIS中的应用

本文给出非线性模型的误差传播公式，并应用于ＧＩＳ空间数据误差分析和处理     

GIS中线元位置不确定性的误差圆带

分析了度量ＧＩＳ线元位置不确定性的“ε－带”和“Ｅ－带”指标后,提出了“误差圆带”新指标,并与前二者进行了比较。结果表明,后者不仅理论上更为合理,而且应用上更为简单。     

非线性模型的误差传播及其在GIS中的应用

本给出非线性模型的误差传播公式，并应用于ＧＩＳ空间数据误差分析和处理。     

GIS数字曲线复杂性的度量与误差建模中趋势项的分离

引入了衡量ＧＩＳ数字曲线复杂性的四种指标，提出了误差建模中趋势项分离的样条函数法，考察了分离一组具有不同复杂度模拟曲线的有效性，并与差分法进行了比较。     

分形分维估值在GIS地理特征描述中的应用

从ＧＩＳ地理特征分形分析入手,利用量规维数的求解来加归区域曲线的无标度区和分维值,并把这一分维值与ＧＩＳ中典型的分形特征相联系,探讨了分维值的含义及其作用,以获得ＧＩＳ下地图应用的新认识。     

GIS数字曲线复杂性的度量与误差建模中趋势项的分离

引入了衡量ＧＩＳ数字曲线复杂性的四种指标，提出了误差建模中趋势项分离的样条函数法，考察了分离一组具有不同复杂度模拟曲线的有效性，并与差分法进行了比较。     

GIS数字产品质量抽样检验方案探讨

针对ＧＩＳ数字产品生产过程,采用“二级检查,一级验收”的检查原则,初步探讨了对数字产品衽帛样检验的基本原理和抽样方案,以ＯＣ曲线分析了传统百分比帛样方法的不足,并提出了对ＧＩＳ数字产品采用挑选型一次极限质量方案作了生产单位的二级检查抽样方案,而采用挑选型一次检后平均不合格品率上限方案作为验收单位的一级验收抽样方案。     

宁夏基础测绘1：1万更新地形图生产安排的探讨

测绘工作是国家建设和社会发展的一项前期性、基础性工作 ,是构成地理信息产业的基础和主干 ,与国家重大工程项目的建设和广大人民群众的日常生活密切相关 ,因此 ,国家基础测绘都已列入各省、市、自治区国民经济可持续发展计划。“3Ｓ”(ＧＰＳ、ＧＩＳ、ＲＳ)技术在测绘领域中不断发展与应用 ,测绘最终成果也由单一的纸质地图发展到 4Ｄ〔数字栅格地图 (ＤＲＧ )、数字正射影像图 (ＤＯＭ )、数字高程模型 (ＤＥＭ )、数字线划图 (ＤＬＧ)〕地图产品。 4Ｄ产品还可以组合为新的数字产品 ,如“ＤＯＭ +ＤＬＧ”可生成数字正射影像地形图 ,“…     

扫描数字化对点误差的统计特性试验与分析

研究了通过扫描数字化试验，获取了GIS中特征点对点误差的基础数据，分析了误差的成因，讨论了误差的分布规律和统计特性，为扫描数字化精度控制及数据质量的评价提供了参考依据。     

Contour line simplification method based on the two‐level Bellman–Ford algorithm

The contour line is one of the basic elements of a topographic map. Existing contour line simplification methods are generally applied to maps without topological errors. However, contour lines acquired from a digital elevation model (DEM) may contain topological errors before simplification. Targeted at contour lines with topological errors, a progressive simplification method based on the two‐level Bellman–Ford algorithm is proposed in this study. Simplified contour lines and elevation error bands were extracted from the DEM. The contour lines of the elevation error bands were initially simplified with the Bellman–Ford (BF) algorithm. The contour lines were then segmented using the vertices of the initial simplification result and connected curves with the same bending direction were merged into a new curve. Subsequently, various directed graphs of the merged curves were constructed and a second simplification was made using the BF algorithm. Finally, the simplification result was selected based on the similarity between several simplification results and adjacent contour lines. The experimental results indicate that the main shapes of the contour groups can be maintained with this method and original topological errors are resolved.     

Analytical Modelling of Positional and Thematic Uncertainties in the Integration of Remote Sensing and Geographical Information Systems

This paper describes three aspects of uncertainty in geographical information systems (GIS) and remote sensing. First, the positional uncertainty of an area object in a GIS is discussed as a function of positional uncertainties of line segments and boundary line features. Second, the thematic uncertainty of a classified remote sensing image is described using the probability vectors from a maximum likelihood classification. Third, the "S-band" model is used to quantify uncertainties after combining GIS and remote sensing data.     

A measure of average error variance of line features

This article presents a new development in measuring the positional error of line features in Geographic Information Systems (GIS), in the form of a new measure for estimating the average error variance of line features, including line segment, polyline, polygon, and curved lines. This average error measure is represented in the form of a covariance matrix derived by an analytical approach. Corresponding error indicators are derived from this matrix. The error of line features mainly results from two factors: (1) an error propagated from the original component points of line features and (2) a model error of interpolation between these points. In this study, a method of average error estimation has been derived regarding the first type error of line features that are interpolated by either linear or cubic interpolation methods. The main contribution of the research is the provision of an error measure to assess the quality of spatial data in application settings. The proposed error models for estimating average error variance of line features in a GIS are illustrated by both simulated and practical experiments. The results show that the line accuracy from a linear interpolation is better than a line interpolated using a cubic model.     

Error model of curves in GIS and digitization experiment

IntroductionCurves are the fundamental geometric elementsin GIS. The uncertainty of their positions has ani mportant influence on those outputs from GISandis the reliable basis for reasonably evaluatingthose outputs .In contrast to measurement error theor…     

地理信息系统中几何特征不确定性的通用模型：从1维到N维

本文提出了描述地理信息系统中几何特征位置不确定性的一个通用模型，从１维到Ｎ维，在每１维中，ＧＩＳ中的特征被划分为点，线段及线性特征。由于ＧＩＳ中数据含有误差。这些特征在ＧＩＳ中位置未必与其现实世界中的真实位置一致，而其真实位置只是在围绕着ＧＩＳ中量测位置的某一个区域内，本文提出的模型给出了这些区域的统计描述。     

Error model of curves in GIS and digitization experiment

A stochastic error process of curves is proposed as the error model to describe the errors of curves in GIS. In terms of the stochastic process, four characteristics concerning the local error of curves, namely, mean error function, standard error function, absolute error function, and the correlation function of errors, are put forward. The total error of a curve is expressed by a mean square integral of the stochastic error process. The probabilistic meanings and geometric meanings of the characteristics mentioned above are also discussed. A scan digitization experiment is designed to check the efficiency of the model. In the experiment, a piece of contour line is digitized for more than 100 times and lots of sample functions are derived from the experiment. Finally, all the error characteristics are estimated, on the basis of sample functions. The experiment results show that the systematic error in digitized map data is not negligible, and the errors of points on curves are chiefly dependent on the curvature and the concavity of the curves.     

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。     

平面随机线元等概率密度误差模型边界包络线

线状实体误差模型包络线既是GIS位置不确定性研究的重要内容,又是GIS可视化研究的关键指标.为了充分利用计算机技术求解符合GIS精度要求的误差模型包络线,基于文献[1,2]中探讨过的等概率密度误差模型建模机理和数值算法,研究了平面随机线元等概率密度误差模型边界包络线的确定原理和计算方法,并通过实例辅以可视化分析,验证了原理的正确性和可操作性.