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The Multi-dimensional Problem of Quantifying Cartographic Generalization Uncertainty: Linear Features as an Example.

机译:量化制图概括不确定性的多维问题:作为示例的线性特征。

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摘要

This paper highlights cartographic considerations relevant during the process of quantification of generalization uncertainties, defined here as Generalization Factor (GF). The paper adds to current research on map or spatial database errors and uncertainties, but focuses on the complex nature of the quantification process of generalization uncertainties. Three main cartographic aspects or contexts are discussed in this paper: namely, feature complexity, map sources, and map purposes. The paper discusses the difficulties in producing a universal index as GF that accounts satisfactorily for generalization uncertainty. As a result, there is a need for a thorough study to account for all types of generalization uncertainty for each feature according to the cartographic consideration discussed in this study, although such contexts are not exhaustive. The study suggests that the uncertainty measures should result in a form of value that can be attached to each feature in the database, especially for those detailed databases that are designed for analysis purposes. The study suggests that it might well be possible to quantify generalization uncertainty more easily once the process of generalization is performed automatically or even semi-automatically, especially with the advent of new generalization tools.
机译:本文突出了在泛化不确定性的量化过程中相关的制图考虑,这里定义为泛化因子(GF)。本文增加了目前关于地图或空间数据库错误和不确定性的研究,而是专注于泛化不确定性的量化过程的复杂性。本文讨论了三个主要制图方面或上下文:即功能复杂性,地图来源和地图目的。本文讨论了普遍指数作为GF的难以满足普遍化不确定性的困难。结果,需要彻底的研究根据本研究中讨论的制图考虑,考虑每个特征的所有类型的概括不确定性,尽管这种情况并非详尽无遗。该研究表明,不确定性措施应导致一种值的形式,该值可以附加到数据库中的每个功能,尤其适用于设计用于分析目的的详细数据库。该研究表明,一旦概括的过程自动执行甚至半自动执行,就可以更容易地量化泛化不确定性,特别是在新的泛化工具的出现。

著录项

  • 作者

    Ali M. Al-Ghamdi;

  • 作者单位
  • 年度 2010
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng;ara
  • 中图分类

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