【作者】 李飞；

【导师】 周晓光；

【作者基本信息】 中南大学 ， 测绘科学与技术， 2013， 硕士

【摘要】 随着遥感和地理信息系统的发展,遥感数据成为GIS愈来愈重要的一种数据源。遥感分类后栅格数据矢量化是目前采用基于像元的遥感影像专题信息提取结果用于GIS空间分析的必然途径。因此迫切需要发展针对大数据量、复杂遥感分类数据的高效、快速矢量化算法。为此,本文较为系统地分析了遥感分类后栅格数据的特点、改进并实现了相应矢量化算法,主要研究工作包括：(1)改进了一种基于窗口的栅格数据矢量化算法。归纳总结了在2×2窗口内分类后栅格数据的15种像元分布类型,在此基础上设计了一种基于窗口的栅格数据矢量化算法。该算法采用2×2窗口提取图像结点、坐标点及其连接信息；利用它们间的连接信息跟踪弧段；然后依据结点和弧段连接信息组建多边形,同时建立拓扑关系。实验验证与比较分析发现：本文算法处理效率得到了提高,且可形成拓扑关系,能处理较大型图像。(2)改进了一种基于游程的栅格数据矢量化算法。该算法利用栅格数据相邻格点的相关性,采取以多边形为单位的方法来进行矢量化,多边形内、外圈提取和拓扑包含关系建立融合在一起执行。实验分析与比较发现：该方法可以在一般个人电脑上完成百兆数据量,图斑数超百万的大型分类栅格数据的矢量化,处理效率可满足实用要求,提取栅格中内、外圈过程中动态建立拓扑包含关系,可满足包含复杂岛屿多边形的分类栅格数据矢量化需求。(3)比较分析了基于窗口和基于游程的栅格数据矢量化算法对矢量化结果中三个问题(复杂岛屿多边形,自交多边形,矢量数据简化)的处理能力。根据地表覆盖分类影像数据量大、内部图斑复杂等特点,选择基于游程的栅格数据矢量化算法,在VS2008平台上,采用C#语言实现地表覆盖栅格数据矢量化与“伪变化剔除”等功能,包括：分类栅格数据读取和存储,分类(包括变化分类)影像批量矢量化(支持大型、具有复杂图斑的数据矢量化)以及剔除“伪变化”等。更多还原

【Abstract】 With the development of Remote Sensing and Geographic Information Systems, remote-sensing (RS) imagery has become an increasingly important data source in GIS application. Vectorization for RS classified raster data is the inevitable way to use such kind of data in GIS spatial analysis. Thus, there is an urgent need to develop highly efficient and fast vectorizing algorithm for very large and complicated classified raster data. Therefore, the characteristics of RS classified raster data is systematically studied, and the vectorizing algorithms are proposed and implemented in this thesis.The primary contents of the thesis can be summarized as follows:(1) A window based raster data vectorizing algorithm is proposed. The fitteen kinds of data types in a2×2window are summarized for RS imagery classified raster data, and a window-based vectorizing algorithm is designed on that basis. All nodes and the coordinates of the points and the connection information between them are extracted by moving through the image using a2x2template window. Then, arcs are tracked by using connection information between all vertor points. Polygons also can be formed based on the connection information between nodes and arcs and topological relations between polygons are established. The practical experiment and comparative analysis with other algorithms indicates that the processing efficiency of the proposed algorithm is improved, and topological relationships can be formed and comparatively large image can also be handled.(2) A raster data vectorizing algorithm based on Run coding is proposed. The algorithm employs the correlations of adjacent grid points in raster data. The process of vectorization is executed polygon by polygon. The extraction of outer ring and inner rings for polygon can be performed together with building topological contain relationships. Experiments on real RS classified data are carried on to demonstrate that this algorithm can process the large raster data on a PC which has the amount of data over100M and the number of polygons more than one million and the efficiency of algorithm can meet the practical requirements. In addition, the algorithm create dynamically topological contains relationships while executing the extraction of outer rings and inner rings simultaneously. Thus, this algorithm can adapt to the case of complex island polygon.(3) The capability of processing the problem in the result of vectorization, such as complex island polygon, self-intersecting polygon, reducing the vector data, is comparised between the window-based and run-coding based vectorizing algorithm. Considering the large volume and complex characteristics of the Landuse RS imagery classified raster data, run coding-based vectorizing algorithm is chosen in the prototype. Finally the vectorizing and false-change removing prototype system is implemented using Visual C#2008, including spatial data reading and storing, batch vectorizing of classified change information (supporting large, complex raster data), and false-change removing, etc. functions.更多还原