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面向海量数据场景的空间属性数据集成框架

The integration framework between GIS and attribute data for the scene of massive data
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摘要 空间数据集成分为空间属性数据集成,特别注意的是时空数据集成存储以及多源空间数据集成两个方面。对于空间属性数据集成方面,面向少数据量多分析性开发场景,Arc SDE是目前最佳的解决方案;但是针对海量性等开发场景,方案甚少,文中基于Sequoia DB与Mongo DB分布式数据库协同探索了该情况下的海量空间属性集成策略以及步骤框架,尤其是针对时空数据。 Spatial data integration is divided into spatial attribute data integration,specially contians spatiotemporal data integration storage and multi-source spatial data integration. For spatial data integration,when confronted with scenario which is more data analysis and low data volume scenarios,Arc SDE is the best solution at present; but when confronted with scenario which is massive,there are few schemes,massive spatial attribute integration ’s strategy and step framework are studied on based on Sequoia DB and Mongo DB aiming at the scenario of magnanimity,especially for the spatiotemporal data.
作者 徐强 范虹 XU Qiang;FAN Hong(School of Computer Science,Shaanxi Normal University,Xi' an 710100,China)
出处 《信息技术》 2018年第9期20-23,共4页 Information Technology
基金 国家自然科学基金(41271518) 陕西省自然科学基金(2014JM-6115) 陕西省科学技术研究发展计划(2012K06-36)
关键词 ARCSDE FME SequoiaDB 时空数据 ArcSDE FME SequoiaDB spatiotemporal data
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