顾及多特征约束的建筑物组合化简方法

建筑物是大比例尺地图中的重要要素,其自动化简是制图综合领域的重要研究内容。针对当前化简方法仅侧重于某一方面的问题,本文提出一种顾及多特征约束的建筑物组合化简方法。首先,对建筑物进行冗余点删除、尖角去除等预处理操作;然后根据化简阈值筛选出需要化简的短边,并对其局部结构进行自动分类识别;然后,充分考虑建筑物的位置、面积、方向和形状等特征约束的影响,针对不同的结构类型采用不同的化简操作,在化简的过程中采用阈值逐渐增大的渐进式确定方法,直到满足化简要求为止;最后,从多个特征角度对化简结果进行评估,对不合理的化简实体进行调整修改。以OpenStreetMap数据为例进行实验,并与其它化简方法进行对比,实验结果表明,本文所提的方法可以有效保持建筑物的面积、形状、直角等基本特征,可以实现建筑物的自动连续化简,具备一定的通用性。

Combined Building Simplification Approach Considering Multi-Feature Constraints

Settlement generalization is an important step for scale transformation, data fusion and integration, data mining, etc. The methods of settlement generalization include selection, simplification, dimension reduction, merging, and typification, among which simplification has been commonly used method. In large scale data, settlement usually exists in the form of building polygon, so the building simplification has always been the focus of settlement generalization. The essence of building simplification is to delete or edit the points that constitute the boundary, and extract the original figure as a simple polygon, while keeping the basic features of the building. In view of the problem that the current simplification method only focuses on one aspect, this paper proposes a combined building simplification method considering multi-feature constraints. Firstly, redundant points and sharp corners are deleted. Then the short edges that need to be simplified are screened according to the simplification threshold, and their local structures are automatically classified and recognized. Furthermore, the influence of the characteristic constraints such as the location, area, direction, and shape of the building is fully considered, and different simplification operations are adopted for different structural types. In the process of simplification, a progressive method with gradually increasing threshold value is adopted until the simplification requirements are met. Finally, the simplification results are evaluated from multiple features and the unreasonable simplification entities are adjusted and modified. Taking OpenStreetMap data as an example, and compared with other simplification methods, the experimental results show that the proposed method can effectively keep the basic features of buildings, such as area, shape, and orthogonal angle, and realize automatic and continuous simplification of buildings, with certain universality.