The Reconstruction And Application Of Building Model Based On Geographical Information

Geographic information system(GIS) has been widely used in the human social activities, and people are living with the system always. With the development of the Geographic information system, the requirements of the building 3D model are more important, especially in the aspect of building recognition. The institutions have posited plenty of solution of the 3D model construction problem, and they have great effect.However, these solutions have their complexity and problems: 1. The data of those methods need some special way to be gotten, and that will spend time and energy. 2. The current applications of GIS cannot combine well with the operations of users when they are showing the building information. In order to solve these issues, a method of constructing building model based on geographic information system has been posited in this thesis. Main works and contributions are as follows:1.The whole algorithm has been posited. The earth coordinate system and the pattern of the geographical information data have been defined. The methods of data dimension reduction, data sorting, edge rays collectiong and height calculation have been described. The algorithm can construct the building model, and it just use a large number of geographic information from the users.2.During the research of the core algorithm, the Cross Point Approximation(CPA) algorithm and Point Set Enclosing(PSE) algorithm are posited. Use the real data to validate the algorithms. The result shows that CPA algorithm is fit for the theory aspect, and the PSE algorithm is fit for the practical application.3.A practical application system of the algorithm is presented, and the design and the implementation of it are described. The implementation processes of the system are showed by partial codes. The system has been tested practically, and the results of the tests are showed, which are logical and acceptable.According to the analysis of the algorithms and the system, the improvement and the development of the algorithm and the system are described. The effect of the algorithm can be significantly improved by enhancing the accuracy of the algorithm and the stability of the data collecting. In the aspect of the system, the effect of the system will be better if more building data can be gotten and the building models can be more meticulous.