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Studies on RS Image’s Geo-Information Issue System
Hong-qiao Wu, Tian-he Chi, Zhang Xin, Jian-bang He Institute of Geographic Sciences and Natural Resources Research (IGSNRR) Chinese Academy of Sciences (CAS), Beijing 100101, China Jin-yun Fang Institute of Computer Technology (ICT), Chinese Academy of Sciences, Beijing 100080, China
Remote sense image data is becoming a main data source for spatial information with the development of observation and space flight technology. Meanwhile, the storage and management of RS image data has exerted an important effect on spatial information sharing and the implement of “Digital Earth”. The patterns of storage, management, promulgation and usage of spatial information has changed violently because of the development of network and distributing computing. Following the appearance of large spatial database management system supporting for spatial graphics, a popular study field for RS image data distributing storage and management has aroused.
There are some advantages for the storage and management of RS image data using current Relation Database Management System (RDBMS). RS image data provide more spatial information and becomes larger and larger, and RDBMS can cater for the requirement of large data distributing storage and information sharing; RDBMS is the mainstream commercial DBMS currently running with long-time development, strong function, stable performance and self-contained industrial standards. Some current enterprise RDBMS such as ORACLE, SQL Server, SYBASE, Informix adopt Client/Server architecture and provide security, integrality and multi-user sharing mechanism. All these properties are absolutely necessary for distributing storage and information sharing. Current RDBMS are not enough in storage and management of complicated data types such Binary Large Objects (BLOBs) as graph, image, sound etc, although they successfully solved storage and management of number and text string. Such BLOBs are lack of meaning, and RDBMS can not support query based on content or analyze them. Furthermore These BLOBs must be downloaded to use at a distributing environment and increase the transmitting data. An object-oriented database (OODB) study has put forth to solve the above problems but the current study are not satisfying. Such OODB can not optimize storage and accessing of the BLOBs. At the present time, an extended RDBMS (Object-Relation Database) can query such BLOBs data with SQL, but as for multi-resolution, multi-spectrum and multi-epoch RS data, there are still some problems and low efficiency. There are some difficulties in RS data sharing under the distributing architecture because of the multi-resolution, multi-spectrum, multi-epoch and large volume data of RS image. Parallel computing technique can alleviate the status. Currently, a parallel platform based on distributed sharing memory (DSM) has been successfully used in image processing. This paper has studied Organization of Parallel Platform To the point of parallel platform structure study, PC clusters and differ-structure system are different branches of network and are all key study fields. Usually, PC clusters refer to the LAN network and differ-structure system refers to Internet. Scientific American Journal(may,1997)acclaimed that the most fast computer system would be the PC clusters connected by LAN or internet. To the point of programming interface and memory management, parallel PC clusters are divided into message pass interface (MPI) and distributed sharing memory (DSM). In MPI system, each processor can only access their own memory and the communications between processors are completed by message transference with peculiar programming method. In DSM system, distributed memory is organized into a unified encoded memory space shared by all processors with a fixed program. Programmer are faced a huge linear memory space and need not change the programming way too much. This paper adopts DSM platform JIAJIA based on Linux, the following figure is the architecture of JIAJIA. 
In this architecture, the sharing memory is distributed at all nodes, each page has a home node, and each node has a cache. Each node’s page only records the information stored in cache. Processor only handle on local access when it accesses its home sharing page. Otherwise, it will store the page directly or have an interruption. Once an interruption occurs, the interruption service routine fetches the page from corresponding home node and deposits it to the page’s cache. The Pattern of Distributed Parallel Storage This paper studies the distributed storage, management and query of large image data based on DSM platform JIAJIA. A logic database of image data is constructed by the solid index of ‘pyramid, layer, block, section’, and the pattern has been implemented with current RDBMS. Figure 2 illustrated the pattern. This pattern has the following characters: Distributed storage In this pattern, the original image data is stored in distributing files system. The logic database establishes a mapping between logic database and data files by setting up a logical connection between the field of database table and the real data file. Parallel processing of data query and transaction The clients’ queries incur large transaction and computation and exert a severe pressure on server because of the large image data. All these transactions and computation can be assigned to PC clusters through programming following the programming interfaces provided by DSM platform JIAJIA. So server’ burden will be alleviated and provide fast speed. 
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