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