栅格数据矢量化及其相关问题的解决方法

矢量结构和栅格结构是GIS的两种主要数据结构形式,而栅格数据不能满足GIS中进行空间分析的要求,因此栅格数据的矢量化在GIS中具有十分重要的意义。本文在总结前人算法的基础上,以拓扑关系的原理为指导,提出了改进的栅格结构数据矢量化方法,即根据4个相邻栅格的异同关系来判定交汇点是坐标点还是结点,并且在提取结点和坐标点过程中,同时提取水平和垂直的所有线段信息,以便快速、有效地实现栅格数据的矢量化。此外,还采用动态打断和粗网格等方法,解决了在栅格数据矢量化过程中,经常出现的诸如多边形自交、孤岛等问题。作者用VisualC⁺⁺语言实现了本文的算法,与ENVI矢量化结果相比,该方法的矢量化结果具有简单方便、编辑工作量小、实用性强等显著优点。因此,该改进方法更有利于遥感图像的信息提取及其与GIS技术的集成。

Vectorization of Raster Data and Solution to Relevant Problems

Raster and vector are two major types of data format in GIS, especially at presenst, remote sensing images have been very important data resource of GIS. With the development of GIS, remote sensing data will play an even greater role in GIS. But however, remote sensing data is usually raster data, and cannot meet the requirements of spatial analysis in GIS, so a conversion of raster data into vector one is of great importance for GIS. Although there are many algorithms and softwares for vectorization of raster data, yet some problems still exist in the process of vectorizing raster data, for example, the vector images thus produced have some islands and self-intersect polygons, or there are only polylines without good topological relation. Hence this can hardly gratify the need of our work.On the basis of summarizing the existing algorithms and following the topological theory, an improved method for converting raster data to vector one is suggested in this paper. In other words, firstly it's determined by the relation of similarities or differences between four neighboring pixels(Fig.2) whether the crosses of neighboring pixels(Fig.1) belong to nodes or coordinate points, then in the process of searching nodes and coordinate points, both vertical and horizontal line segments are picked up at the same time in order to realize the vectorization of raster data more quickly and more efficiently. In addition, by use of the methods such as automatically breaking and widening grid size, some common problems in the course of vectorization of raster data such as self-intersected polygon and island are successfully solved. The authors programme a programme in Visual C⁺⁺ to realize the algorithm in this paper, and contrast its result with other softerwares or algorithms. The algorithm has some better virtues:1)it is easy and convenient to practice; and 2) it has perfect topological relation. Therefore, the improved method is of great benefit to retrieve useful information from remote sensing images, and to promote the integration of Remote Sensing and Geography Information System.