The Research And Implementation Of Data Compression In Vector Maps

With the application of GIS technology widely used, digital maps gradually replace the traditional paper maps and become the main carrier in geospatial data storage. As well as the rapid development of network technology and high-speed wireless network technology, WebGIS technology and mobile GIS technology have emerged. The size of geometric data sets in these applications is constantly increasing. Storing surface or volume meshes in standard uncompressed formats results in large files that are expensive to store and slow to load and transmit. The highly efficient compression of digital maps have become the key to resolve the issue. The vector data structure is compact, low redundancy, and conducive to network searching, so it becomes the most popular graphics data structure. Therefore the vector maps' compression research has far-reaching significance.This study is based on the real background and requirement mentioned above. And it is also involved in the research topic of the Development of General Urban Spatial Data Processing Platform and Research on Security for GIS's Application which is part of 2008 major project of Science and Technology Department of Zhejiang Province.The main contents of this thesis are as follows:1. Give a set of various methods of vector maps compression, and describe the code model of lossless compression in detail.2. Base on the LZW compression algorithm, and the characteristics of the BWT transform, a optimize method of vector map compression based on the BWT transform was proposed. According to the text file was used in spatial data storage in vector map, the paper will separate the coordinate data, and then use the BWT transform, so that the transformed data was more orderly and easy to compress, after that we can use the LZW compression algorithm as a further compression.3. Through the analysis of the vector map files, a new lossless compression algorithm for vector maps is proposed. In the algorithm, lossless transform differentiates the graphical data of vector maps into transformed coefficients, then, making use of the principle of reduction, these transformed coefficients are compressed reversibly. At the same time, BWT Block-Sorting Algorithm is adopted as a further compression algorithm so as to achieve the efficient results of the lossless compression for vector maps. Results of the experiments with practical maps show that, comparing with the existing method of "Needless Appended-Code-Book Dictionary-Based Compression" and other common lossless compression methods, the proposed method is fairly good at compression ratio, and the algorithm is very simple.4. With the foundation of the achievement described above, a software was desired which includes a lot of function, such as the browser of the digital map, compressing and decompressing the map, as well as do some simple analysis. The software can be used to test and verify the compression method.5. Summarize the main causes of data compression and give some approving suggestions.