【摘要】 GML(Geography Markup Language)已成为异构环境下地理空间数据编码、交换和集成的事实标准。由于GML空间数据具有海量性以及GML文档含有大量的冗余信息,导致GML文档体积庞大,影响了系统的集成性能。提出一种基于压缩技术的高效集成方法,将GML文档的结构和数据分离,对文档中的结构数据采用基于词组的字典压缩算法进行压缩,对坐标数据采用去精度的增量压缩的方法压缩。实验结果表明,该方法的压缩性能优于传统压缩方法,且能明显提高GML空间数据的集成性能。更多还原

【Abstract】 GML( Geography Markup Language) has become a de facto standard for geospatial data encoding,exchanging and integration in heterogeneous environment. GML documents are bulky,because they contain a great deal of redundant information and the GML-based spatial data have the property of mass,which affects the integration performance of the system. In this paper,we propose a compression technology-based efficient integration method. It separates the structure and data in GML documents,for structural data in documents it uses phrase-based dictionary compression method to compress,and for coordinate data the delta encoding method for precision removal is used to compress. Experimental results show that the method defeats conventional methods in compression performance and can obviously improve the integration performance of GML-based spatial data.更多还原