基于Voronoi邻近的移动地图自适应裁剪模型

Voronoi Neighbor-based Self-adaptive Clipping Model for Mobile Maps

当前移动地图采用距离关系裁剪模型生成,无法根据地理对象的分布变化自动调整裁剪窗口的大小,导致突出的信息失衡问题,直接影响移动地图的易读性。针对这一问题,提出一种基于Voronoi邻近的移动地图自适应裁剪模型,即通过移动用户的Voronoi邻近关系自适应调整裁剪窗口的大小,以实现移动地图的信息自适应均衡。实验证明,该模型可以有效地改善移动地图的信息均衡性。

Mobile maps are the important way to represent and communicate spatial information in LBS （location based services） field. Due to the asymmetric distribution of spatial objects in real world, taking traditional clipping model of desktop maps to generate mobile maps leads to information unbalance problem, the significant differences of spatial referents＇ number between different mobile maps. Information unbalance makes mobile maps difficult to read especially in moving environment, so the legibility of mobile maps is deteriorated. Based on the function analysis of neighbor relation for human spatial cognition in moving environment, this paper addresses information unbalance problem and proposes a self-adaptive clipping model. The model replaces distance relation with Voronoi neighbor relation to clip spatial referents of mobile maps, which includes ①the calculation of neighbor referents based on Voronoi neighbor② the calculation of self-adaptive scale③ the calculation of self-adaptive clipping window. Addressing the special conditions that neighbor relation maybe changes or becomes very unstable when users approach or move into spatial referents, special stipulations are defined to deal with it. An experiment has been done to validate the model, which takes sight spots of Yuelu mountain garden as the referents and generates mobile maps with two clipping model respectively. The experiment proves the model is effective and feasible to control information unbalance of mobile maps.