空间图形的表达、识别与综合
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摘要
自从计算机技术应用于地图制图学领域的第一天起,地图自动综合就成为人们一直想要解决的问题,直到21世纪的今天,仍没能找到一个万全之策来解决这一国际性难题。本文在参阅和分析国内外有关文献资料的基础上,指出了地图自动综合中的根本矛盾,从一个全新的角度提出了空间图形自动综合的理论,并提出了若干新算法、新模型。从理论到实践,对空间图形的自动综合进行了全面系统的深入研究。本文研究的主要内容如下:
1.明确了地图综合的目的、本质、对象及方法。从地图综合概念的历史沿革,地图自动综合的理论、算法,现有研究机构及成果几方面进行了总结,提出了基于仿生学观点的地图综合概念。分析了地图自动综合中的困惑与误区,指出地理目标的无限性与载负量的有限性是地图综合的根本矛盾,地图自动综合应该是螺旋式上升的循环过程,并对地图自动综合的发展方向进行了预测。
2、指出地图空间由图形空间和属性空间组成,将图形空间中复杂的地理目标抽象成相对简单的空间图形——点(群)、线(群)、面(群),并对其进行了数学描述,研究了空间图形的空间关系。提出了空间图形自动综合的新理论,即自动综合的模式为空间图形的表达、识别与综合,是贯穿全文研究的理论基础。
3、构建Delaunay三角网对空间随机点群目标进行表达。以此为基础,从点群的外围轮廓特征,内部结构,中轴线以及单个点目标影响域几方面进行了形态识别。建立了随机点群目标的自动综合模型,并将其应用于海底地形的自动综合当中。
4、分析线状目标的结构特点,构造了弯曲Douglas二叉树对其进行空间表达。形态识别包括:局部特征点及其方向,弯曲的结构特征,整体描述参数以及拓扑特征。基于视觉连续性原理给出了线状目标的自动综合模型。选取海图中的海岸线、等深线进行了综合试验。
5、借助图论中图的概念,提出了路径系统模型,对网状目标进行图形表达,并识别其形态参数。分别选取了道路网、河流网这两种典型的网状目标进行了综合试验。
6、根据等高线的特性,通过构建等高线树和似Douglas变换模型来表达地貌形态,识别等高线的空间关系,地形特征点,地性线以及地貌类型。最后结合等高线综合的知识规则建立了地貌形态的自动综合模型,并通过试验验证了其有效性。
People always want to solve the problem of map automatic generalization since computer technology was applied in cartography. Until the 21st century, there is not a perfect method to solve it. After analyzing and studying the interrelated literature, the author puts forward the theory of automatic generalization for spatial graphics from a fire-new point of view, and there are also some new arithmetic and new models in this dissertation. From theory to practice, a systemic research is made by the author. The main achievements are the follows:1. The aim, essence, object and method of map automatic generalization are disused. The study makes a summarization including the history of map generalization concept, its theory, arithmetic, research institution and production, and then defines the concept of automatic generalization for spatial graphics. The author thinks that the main conflict is the infinite geography objects and the finite capability, the course of generalization should be spire. And forecast the developing orientation.2. The map space can be divided into graphics space and attribute space. The complicated geography objects are abstracted into simple spatial graphics, including point(s), line(s) and area(s). They are depicted using a math way and their spatial relationship are studied. A new theory of automatic generalization for spatial graphics is educed. That is representation, identification and generalization.3. To represent point-cluster, the study builds Delaunay triangular network. The shape identification includes outline, inside structure, center- axis and the extension of single point. The model of point-cluster automatic generalization is formed and applied in the seabed terrain.4. On the basis of analyzing the line object structure, the study presents curve Douglas binary tree to represent it. The shape identification includes the local character point and its direction, the curve structure, the global parameter and topology trait. The model of line automatic generalization accords with the seeing continuity theory. The coastline and the isobath are selected in the experimentation.5. The study represents net object by designing the path system model and identifies the shape parameter. A test is made using the road net and the river net which are typical.6. Using the contour tree and the similar Douglas conversion, the physiognomy is represented. The contour relationship, terrain character point, orographic character line and physiognomy style are identified. At last, the model of physiognomy automatic generalization is building and its validity is validated by the experiment.
1.明确了地图综合的目的、本质、对象及方法。从地图综合概念的历史沿革,地图自动综合的理论、算法,现有研究机构及成果几方面进行了总结,提出了基于仿生学观点的地图综合概念。分析了地图自动综合中的困惑与误区,指出地理目标的无限性与载负量的有限性是地图综合的根本矛盾,地图自动综合应该是螺旋式上升的循环过程,并对地图自动综合的发展方向进行了预测。
2、指出地图空间由图形空间和属性空间组成,将图形空间中复杂的地理目标抽象成相对简单的空间图形——点(群)、线(群)、面(群),并对其进行了数学描述,研究了空间图形的空间关系。提出了空间图形自动综合的新理论,即自动综合的模式为空间图形的表达、识别与综合,是贯穿全文研究的理论基础。
3、构建Delaunay三角网对空间随机点群目标进行表达。以此为基础,从点群的外围轮廓特征,内部结构,中轴线以及单个点目标影响域几方面进行了形态识别。建立了随机点群目标的自动综合模型,并将其应用于海底地形的自动综合当中。
4、分析线状目标的结构特点,构造了弯曲Douglas二叉树对其进行空间表达。形态识别包括:局部特征点及其方向,弯曲的结构特征,整体描述参数以及拓扑特征。基于视觉连续性原理给出了线状目标的自动综合模型。选取海图中的海岸线、等深线进行了综合试验。
5、借助图论中图的概念,提出了路径系统模型,对网状目标进行图形表达,并识别其形态参数。分别选取了道路网、河流网这两种典型的网状目标进行了综合试验。
6、根据等高线的特性,通过构建等高线树和似Douglas变换模型来表达地貌形态,识别等高线的空间关系,地形特征点,地性线以及地貌类型。最后结合等高线综合的知识规则建立了地貌形态的自动综合模型,并通过试验验证了其有效性。
People always want to solve the problem of map automatic generalization since computer technology was applied in cartography. Until the 21st century, there is not a perfect method to solve it. After analyzing and studying the interrelated literature, the author puts forward the theory of automatic generalization for spatial graphics from a fire-new point of view, and there are also some new arithmetic and new models in this dissertation. From theory to practice, a systemic research is made by the author. The main achievements are the follows:1. The aim, essence, object and method of map automatic generalization are disused. The study makes a summarization including the history of map generalization concept, its theory, arithmetic, research institution and production, and then defines the concept of automatic generalization for spatial graphics. The author thinks that the main conflict is the infinite geography objects and the finite capability, the course of generalization should be spire. And forecast the developing orientation.2. The map space can be divided into graphics space and attribute space. The complicated geography objects are abstracted into simple spatial graphics, including point(s), line(s) and area(s). They are depicted using a math way and their spatial relationship are studied. A new theory of automatic generalization for spatial graphics is educed. That is representation, identification and generalization.3. To represent point-cluster, the study builds Delaunay triangular network. The shape identification includes outline, inside structure, center- axis and the extension of single point. The model of point-cluster automatic generalization is formed and applied in the seabed terrain.4. On the basis of analyzing the line object structure, the study presents curve Douglas binary tree to represent it. The shape identification includes the local character point and its direction, the curve structure, the global parameter and topology trait. The model of line automatic generalization accords with the seeing continuity theory. The coastline and the isobath are selected in the experimentation.5. The study represents net object by designing the path system model and identifies the shape parameter. A test is made using the road net and the river net which are typical.6. Using the contour tree and the similar Douglas conversion, the physiognomy is represented. The contour relationship, terrain character point, orographic character line and physiognomy style are identified. At last, the model of physiognomy automatic generalization is building and its validity is validated by the experiment.
引文
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