基于多级信息网格的海量遥感数据存储管理研究

随着遥感探测技术的高速发展,空间信息呈爆炸式增长。针对目前现有遥感数据存储管理系统数据量大、数据来源丰富、查询检索慢等问题,本文提出了一种基于GeoSOT网格的遥感数据组织方案,并首次在关系型数据库中增加数组数据类型的剖分网格编码列,来存储遥感影像元数据中空间信息,对数据进行逻辑剖分索引,从而实现影像数据的统一存储与空间区域检索。试验选择Kingbase关系型数据库作为测试平台,通过模拟全球范围的影像数据,与Oracle平台进行对比试验。结果表明本文的检索效率具有明显优势,可有效提高遥感数据整合、检索效率,为现有遥感数据存储中心或管理系统提供了一种高效、可行的方案。

A Study on Data Storage and Management for Massive Remote Sensing Data Based on Multi-level Grid Model

With the rapid development of remote sensing technology,spatial information is exploding.For current remote sensing data storage management system,their data volume,rich data sources,query retrieves slow and other issues are problems to be solved.This paper then proposed a remote sensing data organization scheme based on GeoSOT.By firstly adding a GeoSOT code column which is array format in relational database,spatial information in the metadata can be stored and logically subdivided,in order to achieve unified storage and retrieval of image data space area.We compare our method with Oracle platform by simulating worldwide image data.Experimental results show that the retrieval efficiency of this article has obvious advantages and can effectively improve the integration of remote sensing data,retrieval efficiency.Our approach also offers a more effective storage management program for existing storage center or management system.