Research On Semantic Rules-Based DEM And 2D Vector Data Integrtion

With the development of Information Science and Internet technology, Geographic Information System(GIS) has been more widely used in every walk of life. Due to the big difference in cognition, demands, collection methods, and modeling approaches, brings about the diversity among spatial models, database management, module access and data storage models. The information gap caused has become the barrier in the sharing of spatial data in different formats come from multi-source, which has caused the waste in data resource. The DEM and 2D vector data as the typical data sets in GIS, has the characteristic of big quantity and their own advantages and shortages. So the integration of these two types of data set, will expand the dimensionality of data, reduce the cost of data collection, enhance the efficiency of data use, and improve the data quality and accuracy. However, the difference among data and ignorance toward data semantics, the semantic error has been caused. The semantic error plays a bad effect on quality of data and visualization, and blocks the development of the use of spatial data and GIS. Therefore, how to analyze the geometry features and semantic features, how to use the semantic rules to control the data integration, to ensure the data consistency and semantic correctness, is the central idea of this paper.The paper studies basic methods in DEM and vector data integration. By comparing and analyzing, most methods and technologies only complete overlay between DEM and vector data, but ignore the semantic correctness in result dataset, and do not correct the semantic errors. In order to solve the semantic errors in data integration, a new data integration method is provided based on semantic rules of surface features, which can be used in integration between DEM and vector data.Embedding algorithm is also fulfilled. This algorithm is the base of semantic-corrected DEM and vector data integration. After embedding algorithm, the vector data get the height information. The algorithm ensures consistent of terrain morphology and accuracy of correct procedure.The paper also extracts the basic semantic rules from surface features according to their geometry features and semantic features. Based on these rules, the semantic errors can be corrected during integration. Firstly, semantic rules need to be formulized, then using Least Squares Theory and Linear Complementary Theory to compute classified height point. The whole procedure is a transform from semantic rules made to semantic rules computation, it is also a transform from qualitative to quantitative. Finally, the dataset according w ith semantic rules is obtained.Finally, design of semantic rules based DEM and vector data integration test is achieved. It tests and estimates the methods provided in this paper. The test demonstrates the correctness and effectiveness of the method. It is a typical,scientific, widely-fit method, which can correct the semantic errors and enhance the quality of data integration.