张立华唐露露贾帅东戴泽源 |《测绘学报（英文版）》（JGGS）精选论文

Journal of Geodesy and Geoinformation Science

构建与学术的桥梁拉近与权威的距离

🔷Title l 题目

A Collaborative Simplification Method for Multiple Coastlines Based on the Hierarchical Triangulation Network Partition

🔷 Citation l 引文格式

Lihua ZHANG,Lulu TANG,Shuaidong JIA,Zeyuan DAI. A Collaborative Simplification Method for Multiple Coastlines Based on the Hierarchical Triangulation Network Partition[J]. Journal of Geodesy and Geoinformation Science, 2020, 3(2): 93-104.DOI: 10.11947/ j.JGGS.2020.0210.

🔷 Abstract l 摘要

For the current automatic coastline generalization method, only one-line element is considered separately, but the relationship between the nearby elements is not effectively considered. A synergistic simplification method for multiple coastlines based on the hierarchical triangulation network partition (HTNP) is proposed in this paper. Firstly, the constrained Delaunay triangulation is constructed to partition the regions that can be simplified. Then, a hierarchical binary tree model to structure the morphological characteristics of the above several coastlines and the spatial proximity between different coastlines is constructed. Finally, the small curved and curved invisible parts of the coastline are deleted according to the visual constraints, and the narrow part between the coastline itself or the different coastlines is exaggerated appropriately, and the automatic simplification of the coastline is realized. The experimental results show that: ① Relationships between the different coastlines are considered, and the shortcomings of considering the coastline separately are overcome; ② Under the condition of the multiple coastlines in complex sea areas, the problem of collaborative simplification is solved, the quality of the coastlines are improved obviously, and the proposed method can be applied into more types of coastlines.

🔷 Key words l 关键词

cartographic generalization; coastline simplification; hierarchy relationship; synergistic simplification

🔷 Authors l 作者

Lihua ZHANG, Lulu TANG, Shuaidong JIA, Zeyuan DAI.