面向自然连续面群边线的协同化简方法

自然连续面群边线化简是地形图中自然面状要素和地理国情普查数据中自然图斑自动制图综合的重要实施步骤。现有面要素边线化简算法大多以线化简算法为基础,未有效化简弯曲特征、保持面积平衡和满足图面视觉清晰性要求,且化简结果存在共享边界不一致、边线自相交和边线之间相交的拓扑问题。为此,结合自然连续面群表达特点和化简要求,本文提出一种面向自然连续面群边线的协同化简方法。首先将自然连续面群转换为拓扑数据结构组织,以待化简弧段及其相邻弧段为基础构建约束Delaunay三角网,标识化简区域;其次利用弧段双侧层次多叉树模型渐进式退化条带状弯曲、化简细小弯曲;最后自适应夸大狭窄“瓶颈”,实现边线的协同化简。以河南省某区域1:5万地形图中的植被与土质面要素进行化简实验,相较于对比方法,该方法能够有效保持自然连续面群边线化简前后的拓扑一致性、要素之间的面积平衡,充分化简目标尺度下的局部不清晰细节,化简结果精度高。

A Synergistic Simplification Method of Contours of Natural Continuous Polygons

The simplification of contours of natural continuous polygons is an important step of automatic cartographic generalization of natural polygons in topographic map and natural patches in general survey of geographical conditions. Most of the existing simplification algorithms of polygonal contours are based on the line simplification algorithms, which cannot effectively simplify bending features, maintain the area balance, and meet the requirements of graphic visual clarity. Moreover, there are topological problems in the simplification result, such as inconsistent shared contour, self-intersection of contour and intersection between contours. Therefore, combined with the expression characteristics and simplification requirements of natural continuous polygons, a synergistic simplification method is proposed for the contours of natural continuous polygons. First, the natural continuous polygons are transformed into topological data structure, and the constrained Delaunay triangulation is constructed based on the arc segment to be simplified and its adjacent arc segments to identify the simplified region. Second, the arc segment bilateral hierarchical multiple tree model is used to gradually remove or partially remove narrow bends and simplify small bends. Third, the narrow regions are adaptively exaggerated to avoid unclear details on the map. The simplification experiment of Vegetation and Soil polygons in 1:50000 scale topographic map of a region in Henan, China was carried out. Compared with the reference methods, our proposed method can effectively maintain the topological consistency and area balance among natural continuous polygons before and after the simplification and fully simplify the invisible details under the target map scale, and the position accuracy of our simplification results meet the requirement. Therefore, the proposed method has better superiority in terms of topological consistency, visual clarity, and area balance.