1.武汉大学资源与环境科学学院,湖北 武汉,430079
2.中国科学院空天信息创新研究院,北京,100830
3.人工智能与数字经济广东省实验室(深圳),广东 深圳,518060
4.中国测绘科学研究院,北京,100036
郭庆胜,博士,教授,研究方向为地图制图综合、地理信息智能化处理与可视化。guoqingsheng@whu.edu.cn
收稿:2023-12-21,
纸质出版:2025-10-05
移动端阅览
郭庆胜,童莹,魏智威,等.使用正对投影的建筑物群毗邻化新算法[J].武汉大学学报(信息科学版),2025,50(10):2086-2096.
GUO Qingsheng,TONG Ying,WEI Zhiwei,et al.A New Algorithm for Building Groups Agglomeration with Facing Projection[J].Geomatics and Information Science of Wuhan University,2025,50(10):2086-2096.
郭庆胜,童莹,魏智威,等.使用正对投影的建筑物群毗邻化新算法[J].武汉大学学报(信息科学版),2025,50(10):2086-2096. DOI:10.13203/j.whugis20230232
GUO Qingsheng,TONG Ying,WEI Zhiwei,et al.A New Algorithm for Building Groups Agglomeration with Facing Projection[J].Geomatics and Information Science of Wuhan University,2025,50(10):2086-2096. DOI:10.13203/j.whugis20230232
毗邻化是建筑物群综合的一个重要算子,既能解决邻近建筑物之间的空间视觉冲突,还能保持建筑物的独立性。在自动判别建筑物之间正对投影线段的基础上,提出了一种顾及建筑物群整体直角分布特征的建筑物群毗邻化算法。首先,借助原始建筑物群数据的规则格网索引从原始数据中快速搜索符合毗邻化条件的所有正对投影线段;然后,基于建筑物原始直角边相关联的正对投影线段集合生成毗邻主方向线;最后,按照正对投影线段的端点与已生成的毗邻主方向线的不同关联程度,生成毗邻线上的新顶点,并调整建筑物图形轮廓上与这些新顶点直接相关的原始顶点。该方法用成对的正对投影线段可以直接生成建筑物之间的毗邻线,借助毗邻主方向线可以较好地保持毗邻化后的建筑物群整体直角分布特征。采用中国广东省广州市部分区域的大比例尺建筑物群作为实验数据,对不同类型建筑物群进行了毗邻化,分析了建筑物群毗邻化前后的5个建筑物空间特征指标的变化情况,实验结果验证了所提算法的有效性和适用性。
Objectives
2
Agglomeration is an important operator for map generalization of building groups
which can solve the visual conflicts between building symbols and maintain the independence of individual buildings simultaneously. However
the existing methods for agglomeration are difficult to maintain the orthogonality and spatial distribution of building groups. We propose an algorithm for building groups agglomeration considering the overall orthogonal features of building polygons based on identifying the facing projection segments between building polygons automatically.
Methods
2
First
all facing projection segments meeting the criteria of agglomeration can be found rapidly using the regular grid index of original data. Then
the agglomeration main direction lines are generated based on sets of facing projection segments associated with orthogonal segments of original building polygons. Finally
according to the degree of association between the vertices of the facing projection segments and the generated agglomeration main direction lines
the new vertices on the agglomeration lines are generated. And the original vertices of building polygons related with these new vertices must be adjusted.
Results
2
The building footprints data at large-scale in a part of Guangzhou city
Guangdong Province
China is the experimental data. The algorithm of building groups agglomeration has been implemented for different kinds of building groups. The change of five indices describing spatial characteristics between before and after the agglomeration of building groups in this experiment has been analyzed.
Conclusions
2
The experimental results have verified the effectiveness and applicability of the proposed algorithm . This proposed algorithm can directly generate the agglomeration lines between building polygons directly by means of paired facing projection segments
while the overall orthogonal features of building polygons agglomerated can be preserved based on agglomeration main direction lines.
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