The Design And Implementation Of Large-Scale To Map Generalization Syst-Em Based On The Walkisurvey

Map generalization has been one of the most key and difficult problems in the field of cartography, the development of information technology promotes the cartographic generalization’s development from the traditional form to digital form. In the digital environment, different forms of a feature are required in different applications, resulting in multi-scales of the same map. As we all known, updating small scale data takes more time, the update of small scale data cannot meet the demand.Due to the idea that data of small scale are contained in the data of large scale, map generalization which means update between multi-scale databases was born. In our country, map generalization of1:50000to some smaller scale database have been finished successfully; many provinces are exploring ways of generalization between large scales and generalization from large scale to small scale. In addition, existing generalization software is mainly aimed at map generalization between small scales.Based on the practice of large-scale map generalization, which converts contour map from scale1:500to1:2000in some areas of Zhejiang province. Some rules of cartographic generalization are summarized. By using the WalkScript of WalkISurvey which is owned by ZheDaWanWei Ltd., the system transforms the scale of topographic map form1:500to1:2000which has been developed.Up to now, even although quiet a lot of researchers have researched the method and algorithm of cartographic generalization, as the reason of comprehensive forms of mapping elements, such as data in the environment of CAD, which need a process of preprocess. and the complex relationship between different features, most of the algorithms and methods have some limitations:some of them are inefficient, and others cannot get a good result. So, based on the environment of human-computer interaction, the system combined the generalization of existing algorithm of WalkISurvey with some excellent algorithm, in order to get a good map, at the same time, to promote the efficiency and reduce the burden of mapping workers as much as possible.