基于谱矩的地学特征因子提取方法及其应用

发布时间：2018-03-06 00:09

本文选题：数学地质　切入点：特征因子　出处：《地质论评》2017年01期 　论文类型：期刊论文

【摘要】：地学特征因子的提取是定量化数学地质分析的重要基础,可以为地貌类型识别提供有效的客观依据。基于谱矩分析,本文提出了一种描述表面数据粗糙程度的特征因子,并且分析了新特征因子的特点和其应用可能性。该方法以随机过程理论为基础,通过计算表面各阶谱矩以及相应的统计不变量来描述三维表面形貌的特征。以中国卫星重力测量数据和DEM数据为例,试验该方法运用于地貌类型识别的效果。理论模型数据与实际数据结果均表明,基于谱矩的新的地学特征因子不仅可以有效地反映数据起伏与变异特征,而且提取出的特征可以为地貌及重力构造单元划分提供客观依据。
[Abstract]:The extraction of geoscientific feature factors is an important basis for quantitative mathematical geological analysis, which can provide an effective objective basis for the recognition of geomorphological types. Based on the spectral moment analysis, a feature factor describing the roughness of surface data is proposed in this paper. The characteristics of the new feature factors and the possibility of their application are analyzed. The method is based on the stochastic process theory. The characteristics of 3D surface topography are described by calculating the surface spectral moments and the corresponding statistical invariants. The gravity data and DEM data of Chinese satellite are taken as an example. The experimental results show that the new geomorphological feature factors based on spectral moments can not only reflect the fluctuation and variation of the data effectively, but also show that the theoretical model and the actual data are effective. Moreover, the extracted features can provide an objective basis for the division of geomorphology and gravity tectonic units.
【作者单位】：中国地质大学(武汉)数学与物理学院;中国地质大学(武汉)地球物理与空间信息学院;
【基金】：教育部新世纪优秀人才支持计划(编号:NCET-13-1011) 国家自然科学基金资助项目(编号:11426210)的成果~~
【分类号】：P628

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