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地形图等高线成组综合的试验
引用本文:费立凡. 地形图等高线成组综合的试验[J]. 武汉大学学报(信息科学版), 1993, 0(Z1)
作者姓名:费立凡
作者单位:武汉测绘科技大学地图制图系 武汉珞瑜路39号
基金项目:国家教委霍英东教育基金
摘    要:
本文在讨论制图自动综合一般问题的基础上,着重分析了两种等高线自动综合的技术路线存在的优缺点。笔者提出,采用模拟人类专家智能的方法,从二维的等高线输入数据出发,提取地貌结构信息,从而对等高线进行成组的综合,直接形成经综合的二维等高线输出数据,有可能获得较为简捷,效果良好的综合结果。在对这条技术路线进行实验的过程中所涉及的人工智能问题,主要包括:对无序数字化等高线数据的整理、等高线上重要特征点的识别、正负向地貌特征的确定、谷地点的选出、谷底线的自动跟踪、谷地重要性的计算、谷间距的自动量算、对称谷地的寻找、综合后图形的生成等。

关 键 词:等高线  自动成组综合  人工智能

Experiments of Group-generalization of Contour Lines on Topographic Maps
Fei Lifan Dept. of Cartography WTUSM,Luoyu Rood ,. Wuhan,China. Experiments of Group-generalization of Contour Lines on Topographic Maps[J]. Geomatics and Information Science of Wuhan University, 1993, 0(Z1)
Authors:Fei Lifan Dept. of Cartography WTUSM  Luoyu Rood   . Wuhan  China
Affiliation:Fei Lifan Dept. of Cartography WTUSM,Luoyu Rood 39,430070. Wuhan,China
Abstract:
On the basis of discussing general problems in cartographic generalization, this pa-per analyses the advantages and disadvantages of two technical lines for automatic general-ization of contour lines. The author suggests that it is possible to get faster and better general-ization results if we simulate the faster intelligence of human experts in program designing,retrieve geomorphological structural in formation using the input data of 2-dimensional con-tour lines,and directly derive and output the generalized 2-dimensional contour lines. Theproblems of artificial intelligence include:ordering of randomly digitized contour line data,recognition of important feature points on the contour lines,determination of positive or neg-tive geomorphological features, selection of valley points, the automatic tracing of valleylines, the calculation of importance indices of valleys, automatic measurement of distances between valleys, recognition of symmetric saddles,generation of generalized contour graph-ics, etc. In addition to the basic principles,data structures,and concrete algorithms,this paperfinally shows the samples of generalization of contour lines from 1: 10000 scale to 1:50000.
Keywords:contour lines  automatic group-generalization artificial intelligence
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