共查询到19条相似文献，搜索用时 109 毫秒
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在考虑节点化简的基础上建立了节点数据不确定性评价模型,基于曲线光滑模型建立了线元模型不确定性评价模型,在此基础上,根据不确定性传播律构建了由数据不确定性和模型不确定性合成的线状要素多尺度表达不确定性的综合评价模型。实验表明,综合不确定性指标值作为线状要素多尺度表达不确定性的量化指标是有效的。可将其用于计算线元不确定带的宽度,解决线状要素多尺度表达不确定性空间分析和推理问题;并用于线状要素多尺度表达的质量评价与控制。 相似文献
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基于折线逼近的曲线位置与模型误差综合建模 总被引：1，自引：0，他引：1
针对目前GIS中曲线常通过一系列折线来逼近的情况,研究考虑由于折线逼近导致的模型误差和由于测量导致的点位随机误差综合影响的曲线不确定性模型。分析曲线拟合的分段准则,提出折线逼近产生的模型误差可由折线模型到真实曲线的垂直距离描述,建立集成模型不确定性与基于误差传播定律的位置不确定性的曲线误差综合量化模型。 相似文献
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城市人口GIS中数据的不确定性研究 总被引：8，自引：0，他引：8
针对系统数据源、数据模型的不确定性以及分析过程中引入的不确定性等问题进行了系统的研究，并归纳了各种不确定性的影响模型，进而提出了一套人口GIS数据优化建模以及分析过程中人口密度中心建模的思想和实用方法，用于克服人口GIS中数据的不确定性的影响。 相似文献
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在将ＧＩＳ数据不确定性分类为定义不确定性和量测不确定性的基础上,采用辩证法和认识论的观点讨论了二者之间的关系和适用范围。定义不确定性是指客观实体特征向地理信息系统空间目标转化过程中引起的不稳定性;量测不确定性是指对空间目标赋值的不确定性。最后给出了地理数据总体不确定性的度量模型。 相似文献
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遥感与地理信息系统数据的信息量及不确定性 总被引：8，自引：0，他引：8
讨论了遥感、GIS数据的不确定性与信息论中的不确定性间的联系，导出了GIS图形数据与遥感影像数据的信息量估算式，提出了位置疑义度和属性疑义度等概念。在统一的数学基础上，估算几何位置误差和属性正确率不足引起的不确定性，从而建立起遥感影像与GIS图形数据的信息量及不确定性的统一量度。 相似文献
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针对不确定性空间区域对象间拓扑关系不确定性的定量分析问题,提出了一种具有双隶属度函数的灰集表示模型,利用双隶属度函数的截集将不确定性空间区域对象转化为确定性区域对,借用相关的不确定性空间拓扑关系定性分析模型,将不确定性空间对象间拓扑关系的不确定性量化为一个可信度区间。 相似文献
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空间拓扑关系不确定性的定量评价可为多尺度拓扑关系一致性的自动评价、空间推理与空间查询等应用的可靠性提供依据。定义了基于几何度量的拓扑距离,构建了拓扑关系不确定性的粗集表达模型;提出了不确定性粗集表达中拓扑距离的量化方法;进而提出了基于粗集的多尺度空间拓扑关系不确定性度量指标。实例研究证明了本文提出模型的科学性与合理性,该方法可用于多尺度表达过程中引起的拓扑关系不确定性的定量评价。 相似文献
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三维激光扫描点位精度受光斑影响较大,激光点在光斑中呈现了不确定性,该不确定性的准确描述关系到激光点位精度的评价。将误差熵模型引入到点位不确定性的评价中,利用激光点位在光斑中不确定性的概率密度函数,推导了激光点位信息熵,并依据误差熵与信息熵的关系得到了激光点位的误差熵。通过分析误差熵与光斑面积的关系,得到点云光斑平均误差熵,实现了将平均误差熵引入到点云不确定性的评价中。通过设置不同扫描间隔得到的点云数据,分析了平均熵模型进行基于光斑影响下的点云精度评价的可行性,最终实现了对光斑中点云不确定性的准确评价。 相似文献
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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. 相似文献
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SHI Yufeng SHI Wenzhong 《地球空间信息科学学报》2007,10(1):61-66
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. 相似文献
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SHI Yufeng SHI Wenzhong School of Architecture Engineering Shandong University of Technology Zhangzhou Road Zibo China Key Laboratoryof Geospace Environment Geodesy Ministry of Education Wuhan University Luoyu Road Wuhan China. 《地球空间信息科学学报》2007,10(1):61-66
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. 相似文献
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GIS中空间数据不确定性的混合熵模型研究 总被引：4，自引：0，他引：4
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。 相似文献
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Most geospatial phenomena can be interpreted probabilistically because we are ignorant of the biophysical processes and mechanisms
that have jointly created and observed events. This philosophy is important because we are certain about the phenomenon under
study at sampled locations, except for measurement errors, but, in between the sampled, we become uncertain about how the
phenomenon behaves. Geostatistical uncertainty characterization is to generate random numbers in such a way that they simulate
the outcomes of the random processes that created the existing sample data. This set of existing sample is viewed as a partially
sampled realization of that random function model. The random function’s spatial variability is described by a variogram or
covariance model. The realized surfaces need to honour sample data at their locations, and reflect the spatial structure quantified
by the variogram models. They should each reproduce the sample histogram representative of the whole sampling area. This paper
will review the fundamentals in stochastic simulation by covering univariate and indicator techniques in the hope that their
applications in geospatial information science will be wide-spread and fruitful.
Supported by the National 973 Program of China (No. 2006CB701302). 相似文献
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归纳总结了位置不确定性、属性不确定性、时域不确定性、逻辑不一致性等方面的研究现状,重点归纳了位置不确定研究成果;最后指出了GIS不确定性研究存在的问题,并对GIS数据质量控制研究重点进行了分析。 相似文献