基于偏移四叉树投票的“大尺寸”点状符号多尺度无压盖可视化

为解决Web 2.0环境下点状符号地图混搭中的制图问题,本文研究并实现了一种可100%避免压盖的"大尺寸"点符号高效可视化方法。该方法的核心思想是四叉树网格单选,采用网格平移对多次单选结果投票来计算符号在各缩放级别的显著性等级,可解决符号在相邻网格的空间冲突。该过程不需要显式探测冲突,因而处理效率极高。随着地图放大,重要性较低的符号也逐级显现,实现了语义层次的多尺度表达。针对符号和网格大小比率关系、有效网格平移方案及图面利用率不足问题提出两种扩展:格网增选和多级符号叠加。对方法的可行性进行了试验验证,并分析了该方法在用户查询条件改变下的稳定性和不同数据量下的伸缩性(非优化实现可达到105量级数据的亚秒级处理)。

Clutter-free Visualization of Large Point Symbols at Multiple Scales by Offset Quadtrees

To address the cartographic problems in map mash-up applications in the Web 2.0 context,this paper studies a clutter-free technique for visualizing large symbols on Web maps.Basically,a quadtree is used to select one symbol in each grid cell at each zoom level.To resolve the symbol overlaps between neighboring quad-grids,multiple offsets are applied to the quadtree and a voting strategy is used to compute the significant level of symbols for their selection at multiple scales.The method is able to resolve spatial conflicts without explicit conflict detection,thus enabling a highly efficient processing.Also the resulting map forms a visual hierarchy of semantic importance.We discuss issues such as the relative importance,symbol-to-grid size ratio,and effective offset schemes,and propose two extensions to make better use of the free space available on the map.Experiments were carried out to validate the technique, which demonstrates its robustness and efficiency (a non-optimal implementation leads to a sub-second processing for datasets of a 105 magnitude).