中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Gestalt-Based Douglas-Peucker Algorithm to Keep Shape Similarity and Area Consistency of Polygons

文献类型:SCI/SSCI论文

作者Song X. M. ; Cheng C. X. ; Zhou C. H. ; Zhu D. H.
发表日期2013
关键词Gestalt Principle Douglas-Peucker Algorithm Similarity Polygon Area model
英文摘要Douglas-Peucker (DP for short) algorithm plays an important role in vector data simplification and map generalization field. However, it is difficult to keep the similarity between generalized data and original data, especially when an inappropriate tolerance is set for the DP algorithm. What's more, area of the simplified polygon by DP algorithm would change a lot in some specific tolerance distance cases. The paper proposed a Gestalt based Douglas-Peucker algorithm (GDP algorithm for short). The GDP algorithm took into account spatial distribution characteristics of all vertexes and adjusted some points generated by DP algorithm. It could keep similarity of vector data and made polygon area unchangeable. Finally, the paper applied GDP and DP algorithm with different tolerances in experiments of line generalization and polygon generalization. The results of Experiment showed that GDP algorithm is more stable and keeps higher data quality of vector data than DP algorithm. In addition, GDP algorithm can ensure that the area of polygon does not change after simplification.
出处Sensor Letters
11
6-7
1015-1021
收录类别SCI
语种英语
ISSN号1546-198X
源URL[http://ir.igsnrr.ac.cn/handle/311030/30261]  
专题地理科学与资源研究所_历年回溯文献
推荐引用方式
GB/T 7714
Song X. M.,Cheng C. X.,Zhou C. H.,et al. Gestalt-Based Douglas-Peucker Algorithm to Keep Shape Similarity and Area Consistency of Polygons. 2013.

入库方式: OAI收割

来源:地理科学与资源研究所

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