A new data integration approach for AutoCAD and GIS

GIS has its advantages both on spatial data analysis and management, particularly on the geometric and attributive information management, which has also attracted lots attentions among researchers around world. AutoCAD plays more and more important roles as one of the main data sources of GIS. Various work and achievements can be found in the related literature. However, the conventional data integration from AutoCAD to GIS is time-consuming, which also can cause the information loss both in the geometric aspects and the attributive aspects for a large system. It is necessary and urgent to sort out new approach and algorithm for the efficient high-quality data integration. In this paper, a novel data integration approach from AutoCAD to GIS will be introduced based on the spatial data mining technique through the data structure analysis both in the AutoCAD and GIS. A practicable algorithm for the data conversion from CAD to GIS will be given as well. By a designed evaluation scheme, the accuracy of the conversion both in the geometric and the attributive information will be demonstrated. Finally, the validity and feasibility of the new approach will be shown by an experimental analysis.