系统仿真学报 ›› 2016, Vol. 28 ›› Issue (2): 261-267.

• 仿真建模理论与方法 •    下一篇

基于分形维数的DEM聚类简化方法研究

张帆, 李晓阳, 刘欢, 胡伟, 李伟   

  1. 北京化工大学信息科学与技术学院,北京 100029
  • 收稿日期:2014-09-22 修回日期:2015-01-15 出版日期:2016-02-08 发布日期:2020-08-17
  • 作者简介:张帆(1981-),男,河南许昌,博士,副教授,研究方向为SAR成像仿真、高性能计算、科学可视化。
  • 基金资助:
    国家自然科学基金资助项目(61501018); 北京高等学校青年英才计划(YETP0500)

DEM Clustering Simplification Algorithm Based on Fractal Dimension

Zhang Fan, Li Xiaoyang, Liu Huan, Hu Wei, Li Wei   

  1. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
  • Received:2014-09-22 Revised:2015-01-15 Online:2016-02-08 Published:2020-08-17

摘要: 分形是自然场景的本质特征,可以描述地形表面的不规则程度,多用于数字地形生成。作为地形生成逆过程的数字地形简化,通常以曲率等几何特征作为衡量指标进行网格缩减,提高电磁计算、洪水模拟、视景仿真等问题的解算效率,而忽略了分形这个地形本质特征。针对现有DEM (Digital Elevation Model)简化算法难以识别地形变化复杂区域特征的问题,提出了一种新的基于分形维数的地形聚类简化算法,将分形特征应用于数字高程模型的简化过程,依据分形维数对不同子类区域数据进行简化合并。结果表明:相比传统简化算法,该算法具有高精度数据空洞小地形保持度高的特点,更加适合结构复杂、变化多样的地形。

关键词: 数字高程模型, 分形维数, 聚类算法, 网格简化

Abstract: Fractal is the essential characteristic of natural scenes. It can describe the irregular extent of surface topography, so it is used for digital terrain generation. As the inverse process of terrain generation, digital terrain simplification usually uses geometric properties such as curvature index as a measure to reduce the grid to improve the efficiency of electromagnetic solver calculations, flood modeling, visual simulation and other issues, while ignoring the fractal nature of the terrain features. Since a traditional simplification algorithm of DEM is difficult to identify the characteristics of complex topography, a new clustering simplification algorithm based on fractal dimension is proposed. The fractal characteristics are introduced in simplified process of digital elevation model, using the fractal dimension for data simplifying and merging in different subclasses. The experiment results show that compared with classical algorithms:this algorithm has the characteristics of higher precision, smaller voids and higher terrain retention, more suitable for the diversified and complex DEM.

Key words: digital elevation model, fractal dimension, clustering algorithm, simplification of grids

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