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Remote sensing has a range of access to information, access to information means more speed, short cycle and less restrictions, etc., and with the rapid development of aviation and aerospace technology, remote sensing data acquisition price is getting smaller and smaller, and has been widely used in land use in areas such as environmental monitoring, weather forecasting, remote sensing data, the amount of data is very large, and the temporal and spatial data include more than one data, there are a lot of historical data, so that makes remote sensing data storage is very difficult, taking up disk space than the more, and not easy to manage. Therefore, how to establish effective the raster spatial and temporal data model to describe the spatial and temporal characteristics of the geographic entity; how a very large amount of data to remote sensing image data compression process, thus saving disk space has become the current raster spatial and temporal database and its related fields of study hot spots. This paper briefly introduces the research background and significance, raster spatial and temporal data modeling foundation and several common raster spatial and temporal data model, design ideas and conceptual model of a double-base state with amendments model; Secondly, from concept the raster spatial and temporal database and logic both the design and analysis of raster data used several compression methods, improved the linear quadtree fast dynamic encoding algorithm, and the improved algorithm is applied to two dimensional run-length encoding, determined in the double-base state with amendments model-based 2D stroke dynamic coding compression algorithm; then, analysis, and how to find out the difference between the phases of raster data change issues, improved the raster spatial and temporal data difference analysis algorithms and differential accumulation algorithm; Finally, the relational database SQL Server 2000 on the design and establishment of the raster spatial and temporal database, developed using Visual Studio.Net 2005 C # language based on a grid space-time model based on the two-base state with amendments data management system, Liaocheng 1987-2005 three remote sensing image data, for example, double base state with amendments model ideas and proposed algorithm validation analysis. Validation analysis results show that, compared with the the general raster spatial and temporal data model and compression algorithms, double-base state with amendments model proposed in this paper is more reasonable to organize and manage raster spatial and temporal data, two-dimensional trip dynamic compression algorithm for compression of raster data speed faster, more efficient system developed on this basis to improve the of raster spatial and temporal data input, retrieval, query and update speed.
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