标题: A hexagon-based method for polygon generalization using morphological operators

作者: Wang, L (Wang, Lu); Ai, TH (Ai, Tinghua); Burghardt, D (Burghardt, Dirk); Shen, YL (Shen, Yilang); Yang, M (Yang, Min)

来源出版物: INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE DOI: 10.1080/13658816.2022.2108036 提前访问日期: AUG 2022

摘要: Numerous methods based on square rasters have been proposed for polygon generalization. However, these methods ignore the inconsistent distance measurement among neighborhoods of squares, which may result in an imbalanced generalization in different directions. As an alternative raster, a hexagon has consistent connectivity and isotropic neighborhoods. This study proposed a hexagon-based method for polygon generalization using morphological operators. First, we defined three generalization operators: aggregation, elimination, and line simplification, based on hexagonal morphological operations. We then used corrective operations with selection, skeleton, and exaggeration to detect, classify, and correct the unreasonably reduced narrow parts of the polygons. To assess the effectiveness of the proposed method, we conducted experiments comparing the hexagonal raster to square raster and vector data. Unlike vector-based methods in which various algorithms simplified either areal objects or exterior boundaries, the hexagon-based method performed both simplifications simultaneously. Compared to the square-based method, the results of the hexagon-based method were more balanced in all neighborhood directions, matched better with the original polygons, and had smoother simplified boundaries. Moreover, it performed with shorter running time than the square-based method, where the minimal time difference was less than 1 min, and the maximal time difference reached more than 50 mins.

作者关键词: Polygon generalization; hexagonal grids; mathematical morphology; raster data

地址: [Wang, Lu; Ai, Tinghua; Yang, Min] Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.

[Burghardt, Dirk] Tech Univ Dresden, Inst Cartog, Dresden, Germany.

[Shen, Yilang] Sun Yat Sen Univ, Sch Geospatial Engn & Sci, Zhuhai, Peoples R China.

通讯作者地址: Ai, TH (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.

电子邮件地址: tinghuaai@whu.edu.cn

影响因子：5.152