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APPLICATION OF THE RADICAL LAW IN GENERALIZATION OF NATIONAL HYDROGRAPHY DATA FOR MULTISCALE MAPPING

机译:激进法在多尺度映射中的国家水文中的概括中的应用

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The importance of automating feature generalization is increasing in conjunction with demands for updated data. Determining which features to represent at myriad scales is an important part of this process. The Principles of Selection, as proposed by Topfer and Pillewizer in 1966, provide cartographers with an empirically based generalization rule. Also known as the Radical Law, the principles provide an equation estimating the number of features depicted at smaller scales based on the relationship of map scale denominators. However, the applicability of the equation at large scales seems limited in its current form. With ongoing initiatives to automate cartographic processing and the digitization of data at large scales, there is utility in determining how many features to display on derived medium and small scale products. We evaluate the USGS National Hydrography Dataset and National Atlas hydrography to determine the existing length of features for comparison to expected results based on the Radical Law equation. The rate of feature selection is not the same along the continuum of scale. A new factor is added to the Radical Law equation to account for this variability. Results from a USGS flowline pruning tool by Stanislawski and Buttenfield are used to compare equation results to benchmark USGS hydrography at 5K, 24K, 100K and 2M scales. Increasing knowledge of existing hydrographic features can improve implementation of automated feature generalization and propagation through a wide range of scales.
机译:自动化特征概括的重要性与更新数据的需求一起增加。确定在Myriad Scales上表示的特征是此过程的重要组成部分。由Topfer和Pillewizer于1966年提出的选择原则,提供了具有凭证基于普遍规则的制图员。又称激进的法律,原理提供了一种等式估计基于地图比例分母的关系处于较小尺度的特征的数量。然而,在大尺度上的等式的适用性似乎有限于其目前的形式。通过正在进行的举措来自动化制图处理和大尺度数据的数字化,有实用程序确定在衍生的介质和小规模产品上显示有多少功能。我们评估USGS国家水文数据集和国家地图集水文,以确定现有的特征长度与基于激进的法律方程的预期结果。沿着规模连续的特征选择速率不一样。在激进的法律方程中添加了一个新因素,以解释这种可变性。 STANISLAWSKI和BUTTENFIELD的USGS流线修剪工具的结果用于将公式结果与5K,24K,100K和2M秤进行基准。越来越多的现有水文特征的知识可以通过各种秤改善自动特征泛化和传播的实现。

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