异构环境下的GML空间数据高效集成研究  

RESEARCH ON EFFICIENT INTEGRATION OF GML BASED SPATIAL DATA IN HETEROGENEOUS ENVIRONMENT

作　　者：李文全[1] 戴经国[1] 段琢华[1] 李丹[1] 

机构地区：[1]韶关学院计算机科学学院,广东韶关512005

出　　处：《计算机应用与软件》2015年第5期42-45,共4页Computer Applications and Software

基　　金：国家自然科学基金项目(61101134);广东省青年创新人才类项目(2014KQNCX209);广东高校优秀青年创新人才培养计划项目(LYM11116)

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。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 tech- nology-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.

关 键 词：异构环境 GML空间数据 压缩 增量编码 集成 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]