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.     

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.     

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。     

Relationship of uncertainty between polygon segment and line segment for spatial data in GIS

The mathematic theory for uncertainty model of line segment are summed up to achieve a general conception, and the line error band model of ?σ is a basic uncertainty model that can depict the line accuracy and quality efficiently while the model of ?m and error entropy can be regarded as the supplement of it. The error band model will reflect and describe the influence of line uncertainty on polygon uncertainty. Therefore, the statistical characteristic of the line error is studied deeply by analyzing the probability that the line error falls into a certain range. Moreover, the theory accordance is achieved in the selecting the error buffer for line feature and the error indicator. The relationship of the accuracy of area for a polygon with the error loop for a polygon boundary is deduced and computed.     

A new approach to simulate positional error of line segment in GIS

To determine the distribution of positional error of a line segment, Monte Carlo approach is applied to simulate the probability density function of a line segment with the assumption that the error of endpoints in a line segment follows a two-dimensional normal distribution. For such purpose, a stochastic generator used for uncertain endpoints with the two-dimensional normal distribution is presented. This forms the basis of the generation of random line segment for the simulation of the error model of a whole line segment. The error models cover the cases where two endpoints are either independent or dependent to each other, also including a special case that the distance between two random endpoints in a line segment is close enough.     

遥感云分类不确定性的多维混合熵模型评价

针对遥感影像提取信息分类过程中存在随机不确定性和模糊不确定性两种噪声,影响分类结果的准确性问题,该文在多光谱遥感影像处理中,通过对传统的混合熵模型进行多维化改进,提出多维混合熵的不确定性评价模型。采用云算法对遥感影像进行解译分类,获取相应的不确定性模型参数计算出信息熵和模糊熵,从像元和类别两个尺度构建出遥感云分类不确定性的多维混合熵评价模型。结果表明,多维混合熵模型能够充分考虑多光谱遥感数据的多维性,可以从不同尺度对遥感分类的随机不确定性和模糊不确定性进行有效全面地评价。     

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。     

GIS产品质量的熵权多层次模糊综合评价

传统多层次模糊综合评价中评价因子权重的确定通常通过专家经验法进行,该方法受专家主观因素影像较大,容易造成评价结果出现偏差。本文提出在权重的确定过程中除参考专家的主观权重外,引入熵权概念,将主观权重和熵权客观权重相结合,作为GIS产品质量评价因素的权重。本文以对DOM产品的质量评价为例,采用熵权模糊综合评价方法进行试验,试验结果表明由客观熵权值和专家主观权重相结合所确定的因子权重很好的将主观与客观因素结合起来,且评价结果客观、合理。     

空间线要素综合算法的不确定性讨论

简述了几种曲线综合算法思路,从综合算法阈值的计算,综合算例数据等方面对综合算法及其不确定性进行了量化的评价,并进一步总结了综合算法不确定的各种表现.     

Relationship of Uncertainty and Line Segment for Between Polygon Segment Spatial Data in GIS

The mathematic theory for uncertainty model of line segment are summed up to achieve a general conception, and the line error hand model of εσ is a basic uncertainty model that can depict the line accuracy and quality efficiently while the model of εm and error entropy can be regarded as the supplement of it. The error band model will reflect and describe the influence of line uncertainty on polygon uncertainty. Therefore, the statistical characteristic of the line error is studied deeply by analyzing the probability that the line error falls into a certain range. Moreover, the theory accordance is achieved in the selecting the error buffer for line feature and the error indicator. The relationship of the accuracy of area for a polygon with the error loop for a polygon boundary is deduced and computed.     

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。     

Relationship of Uncertainty Between Polygon Segment and Line Segment for Spatial Data in GIS

The mathematic theory for uncertainty model of line segment are summed up to achieve a general conception, and the line error band model of εp is a basic uncertainty model that can depict the line accuracy and quality efficiently while the model of εm and error entropy can be regarded as the supplement of it. The error band model will reflect and describe the influence of line uncertainty on polygon uncertainty. Therefore, the statistical characteristic of the line error is studied deeply by analyzing the probability that the line error falls into a certain range. Moreover, the theory accordance is achieved in the selecting the error buffer for line feature and the error indicator, The relationship of the accuracy of area for a polygon with the error loop for a polygon boundary is deduced and computed.     

Entropy error model of planar geometry features in GIS

Positional error of line segments is usually described byusing “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 do-nut 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.     

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.     

测量的广义可靠性研究

首次给出了广义可靠性的定义,对于测量误差理论进行了进一步论述,分析了偶然误差的系统性影响和系统误差的偶然化两大问题,讨论了目前流行的测量不确定度概念,指出了广义可靠性的研究内容和若干应用,对于测量方案设计、平差数据处理、仪器检定以及测量规范的理解等具有一定参考意义。     

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。     

人口地理数据的不确定性及其对策研究

从第五次人口普查建立人口地理信息系统的实践出发 ,对人口地理数据的不确定性进行了归纳和总结。人口地理数据的不确定性主要包括空间地理数据的不确定性、人口数据的不确定性和系统对人口地理数据处理和分析时引入的不确定性。在对各种类型的不确定性进行分析的同时 ,针对数据的不确定性存在的客观事实 ,探讨了在建立和应用人口地理信息系统时应注意的问题、采取的措施和策略     

Double vagueness: uncertainty in multi-scale fuzzy assignment of duneness

In the automation of identification of landscape features the vagueness arises from the fact that the attributes and parameters that make up a landscape vary over space and scale. In most of existing studies, these two kinds of vagueness are studied separately. This paper investigates their combination in identification of coast landscape units. Fuzzy set theory is used to describe the vagueness of geomorphic features due to the continuity in space. The vagueness resulted from the scale of measurement is evaluated by statistic indicators. The differences of fuzzy objects derived from data at differing resolutions (in size from 3×3 cells to 25×25 cells) are studied in order to examine these higher-order uncertainties.