The Study Of Storage Mechanism And Application Of Raster Spatial Database Engine

With the development of remote sensing technology,raster data become increasingly at present.The current management is difficult to realize the storage and management of the massive data.Thus,we need an efficient management to meet the application demand.How to store and manage for massive raster data has already become one important subject of Geographical Information Science domain.On the basis of studying the key technologies and relative theories about raster spatial database engine(RasSDE),the feasibility of efficient management of massive raster is discussed in this dissertation.Finally,the self-designed spatial database and the prototype system of raster spatial database engine are developed.The following respects are discussed in this dissertation:1) Studied of the problem about the management of massive raster spatial data, including the concrete design in the physical and logic database of spatial database to solve the peculiar problem on raster data.2) Tile-pyramid model and tile-index are put forward for applications of massive raster data.More emphasis is given to study the rule of data blocking and common method of building tile-pyramid model and tile-index.On the other hand,some problems, such as visualization,target-tile searching and data compression are also investigated.3) Studied of the realized strategy of multi-source and isomeric spatial data interoperability under the distributed context.Emphatically,the design of Open Multi-source Spatial-data Access Component(OMSAC) is discussed in this dissertation.And the concrete implementation method is provided under the design model of FACADE.4) A prototype system(RasSDE) has been designed and realized based on studying of the management model of raster SDE,key technologies and realized method.Study and experimental results show that the self-designed spatial database can store and mange massive raster data efficiently.And RasSDE that is designed and developed independently can realize the management of the massive raster data basically with high data access efficiency.