【作者】 王涛；

【导师】 毋河海；

【作者基本信息】 武汉大学 ， 地图学与地理信息系统， 2005， 博士

【摘要】 地形地貌控制着地球表面上水分、热量的再分配,进而对气候、水文、土壤、生态乃至人类有着重要的影响,而它本身也是人类认识自然、改造自然的重要客体。近二十年来,电子和航天技术突飞猛进,在获取了关于大自然详细而又客观的定量数据的基础上,人类对自己生活的地球的认识早已脱离了质朴的探险活动所带来的感性体验,而这个基础就是海量的地理空间信息,其中最为重要的是地表形态的数据,因为它为所有其他地理要素提供了空间参考框架。地形地貌一直以来都是地学领域的重要研究对象之一,作为研究地表之上以位置为主导的所有现象和实体的描述表达和信息管理的学科,地图学与地理信息系统为地形数据的获取、数据管理、空间分析和工程应用提供了重要的理论和技术支撑,在等高线、规则高程格网、不规则高程三角网的数据结构上,各种可视化手段为人们提供了认识世界的直观而又高效的方式,坡度、坡向、曲率等基本的地形参数以及体积、通视性、水文参数等的计算为工程应用提供了基础,但是这些基础的计算尚不能满足大量更高层次应用的需要。同时一方面,当前的数据量已经巨大到惊人的程度,一方面,人们对于随时随地的使用高精度的数据有着更高的期望,这就要求数字地形数据能够以高效的方式在各种介质上传递并再现。另外,对于如此海量的数据无论使用何种逼真的可视化技术,也难以让人迅速有效的找到其中需要的知识,它已经远远超出了人脑认知的尺度范围。这一切都要求新型的数字地形模型。 早在计算机出现之前就被提出来的地性线模型为进一步的研究搭起了发展的桥梁。以地性线为基础构建面向对象的地形数据模型既可以大大压缩低层次数据表达方式的数据量,还能提高人们所能使用到的数据层次,并且可以为地貌自动综合、水文分析等高层次的分析提供支持。本文将以此为出发点开展研究。 首先,地形的地性线模型是以已有的低层次数据模型为基础构建的一种网络化数据结构,它通过地性点和特征线记录了地形的关键要素,它与面向对象的地形数据模型之间存在着高度的关联关系。 当前分别以等高线、高程格网、高程三角网为数据源的数字地形分析算法非常丰富,然而从现有数据中自动化的提取地性线的研究并未完全成熟。基于等高线的提取算法因为数据源的主要形式发生了重要转变而发展缓慢,同时已有算法提取结果的不稳定性也使得这类算法受到一定限制,高程三角网作为地形的矢量表达形式,在可视化和表达三维空间方面有着非常优越的性质,但是对于提取地性线的问题而言,目前的算法尚有待成熟。基于规则高程格网的算法有着众多研究成果,其中流水累积法、形态法和曲面分析法是其中最为重要的三种。本文结合前两种算法,设计了新的算法模型。第一步使用流水累积法提取出基本谷地线,更多还原

【Abstract】 Terrain is a fundamental feature in various research areas, which controls the local redistribution of energy and water. It has an important impact on the hydrological, soil, biological and geomorphological processes. In the recent years, the fast developing technologies in electronics and aeronautics give people the opportunity to re-understand our earth, especially terrain. The key is digital terrain data.Cartography and GIS provide a representation and management platform for the location based phenomena and further facilitate the spatial analysis and engineering applications. Among these, terrain plays an important role which sets a reference framework for other geographical features in the digital environment. Digital terrain analysis is coined as a research area which studies data model of digital terrain data, information derivation from elevation data, application in geosciences. The success in data acquiring technology poses a challenge for all the research topics because the availability of voluminous data with high accuracy and resolution makes human being lost. The recent research on promoting high-level representation from the primary digital elevation data models, which include contour, TIN and regular grid, are an active area. A basic result is surface network of terrain. The surface network, which has many its origins as structural lines, surface specific lines, Warntz Graph, Pflatz Network and contour tree, has lots of roles in automatic processes on terrain information. The geographical information generalization is an example which employes surface network as the terrain’s abstraction and generalize it instead of contour for the effectiveness. Currently the main type of the digital terrain data is regular grid. Nevertheless, surface network is not the only choice in all situations for grid. Contour has its name in representing terrain in an adaptive way and quality communication of geomorphological information. However the efficiency of contour threading algorithm in grid has to improve because of the data volume and user command.This paper studies the algorithm of valley lines extraction from grid data. Existing methods which can be classified into local concavity, water accumulation and polynomial surface analysis have limited success in different situations. Our algorithm combines the first two types methods. It has three stages in general. Firstly water accumulation is used to extract the primary valley lines. The original implementation of this algorithm has some potential to refine. We proposes a new depression filling algorithm which does not use the combining of depression and the window resizing. The filling process starts from the pit point and find the depression range in a circular way and the final boundary is not wider two points than the actual one. The threshold strategy is core idea of simulating valley as flowing process dominating area. But it is so subjective that the result is not pleasing because it may contain too detail valley lines in the lower area and miss a lot typical valley lines in the higher area. The second stage of our algorithm, which includes bottom-up and top-down analysis, serves as the extension based on the primary valley lines acquired in the first stage. The local concavity method is used here for its simplicity and robust in the area which contain typical valley lines. But the latter one is noise sensitive and produces clutter result. So we need clean it to an acceptable one in the third stage which first organizes thevalley lines in Strahler order based the flow direction of each point on the extracted valley lines in previous steps. Then we classify the clutter of valley lines into different categories and design corresponding rules to clean them. The minor valley lines in the final result can be pruned based on length and watershed area. The conversion from raster to vector is easy based on Strahler order and could have more application.As noted above contour line is a more adaptive way to represent terrain than grid and even has advantages in some situation. Here we design new algorithm for extracting contour lines from grid based on interval-tree index and bucket sorting index. The experiment showed that it is much more efficient that ever ones. Some tests recommend that latter index have better performances in construction and query.The further study is concentrated on the spatial relation of contour lines because we believe that the efficient application of contour lines must have both geometric data and the relation information. The framework we proposed is based on the directional adjacency of contour lines which define twelve kinds basic relation patterns. The relation is built based on the triangulation of original contour lines. The effectiveness of our framework is demonstrated by the applications. The first is on automatic elevation labeling which has many practical meaning in the conversion of contour lines from traditional media to digital ones. The second is identification and connection of broken contour lines which can be encountered in same process. The last one is about the construction of contour lines bounded area in which the open contour lines is hard to deal with in existing methods.更多还原