Spatial index is a key issue in massive spatial data processing.
海量空间数据的处理需要通过空间索引来提高效率。
In recent years, many organizations successively have established respective GIS system, gathered and saved the massive spatial data.
近年来，许多机构先后建立了各自的GIS系统，采集和存储了大量的空间数据。
Spatial Database Engine; Spatial Database Management System; Seamless Integration of Multisource Spatial Data; Adjusting and Optimizing; Massive Spatial Data.
空间数据库引擎；空间数据库管理系统；多源空间数据无缝集成；调整和优化；海量空间数据。
The progressive transmission strategy is considered to be an effective way to balance contradiction between scheduling the massive spatial data and the real time user experience.
渐进传输被认为是解决目前海量空间数据传输与实时用户体验之间矛盾的有效方法。
Because it's massive and unstructured, Feature-Oriented Object Level (FOOL) and Multi-servers cluster system are used to integrate and manage spatial data effectively.
由于其海量和非结构化等特征，实体对象层次模型、群集多服务器体系被提出用以集成并实施高效的空间数据管理。
Currently, traditional spatial data model with the inherent limitations can not fully satisfy the scope of the global multi-resolution massive data dynamic management requirements.
当前，传统空间数据组织与模型的内在局限性已经不能完全满足大范围甚至全球多分辨率海量数据动态管理的要求。
At present, access efficiency of spatial and spatiotemporal data based on seamless massive table mechanism needs solid improvement.
当前，基于无缝海量大表的空间及时态空间数据的存取效率亟待提高。
How to express, organize and process the global multi-scale spatial data better, particularly the massive vector data, has become a problem that attracts common attention from the GIS scholars.
如何更好地表达、组织与处理全球多尺度空间数据，尤其是海量矢量数据，已成为GIS学者普遍关注的问题。
How to express, organize and process the global multi-scale spatial data better, particularly the massive vector data, has become a problem that attracts common attention from the GIS scholars.
如何更好地表达、组织与处理全球多尺度空间数据，尤其是海量矢量数据，已成为GIS学者普遍关注的问题。
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