A self-global-best-fit road network Stroke generation method

doi:10.13474/j.cnki.11-2246.2022.0210

Abstract

Abstract: Stroke plays an important role in road network research. At present, most stroke connection strategies focus on the local and don't consider global performance. The paper presents a self-global-best-fit strategy for generating road network Stroke. Firstly, the Stroke tree is built under the constraints of connection rules with the selected road as the root node. Then, the best Stroke of each tree is selected by the random forest algorithm. The results show that the performance of the self-global-best-fit strategy is better than the self-fit strategy, self-best-fit strategy, and every-best-fit strategy in visual cognition and network function.

Key words: road network, self-global-best-fit, random forest, Stroke tree

CLC Number:

P208

Lü Zheng, SUN Qun, WEN Bowei, MA Jingzhen. A self-global-best-fit road network Stroke generation method[J]. Bulletin of Surveying and Mapping, 2022, 0(7): 93-99.

References

[1] THOMSON R C,RICHARDSON D E.The"good continuation"principle of perceptual organization applied to the generalization of road networks[C]//Proceedings of the 19th International Cartographic Conference.Ottawa:[s.n.],1999.
[2] 马京振.顾及尺度变化的道路和居民地融合处理理论与方法研究[D].郑州:信息工程大学,2020.
[3] 钱海忠,张钊,翟银凤,等.特征识别、Stroke与极化变换结合的道路网选取[J].测绘科学技术学报,2010,27(5):371-374.
[4] 马超,孙群,陈换新,等.加权网页排序算法在道路网自动选取中的应用[J].武汉大学学报(信息科学版),2018,43(8):1159-1165.
[5] 栾学晨.保持结构模式的道路网数据多尺度建模[D].武汉:武汉大学,2013.
[6] JIANG Bin.A topological pattern of urban street networks:universality and peculiarity[J].Physica A:Statistical Mechanics and Its Applications,2007,384(2):647-655.
[7] 王培,赵军喜,崔虎平,等.采用道路骨架线stroke的复杂道路匹配方法[J].测绘科学技术学报,2019,36(1):95-99.
[8] 徐柱,刘彩凤,张红,等.基于路划网络功能评价的道路选取方法[J].测绘学报,2012,41(5):769-776.
[9] LIU Yi,LI Wenjing.A new algorithms of stroke generation considering geometric and structural properties of road network[J].ISPRS International Journal of Geo-Information,2019,8(7):304.
[10] 杨敏,艾廷华,周启.顾及道路目标stroke特征保持的路网自动综合方法[J].测绘学报,2013,42(4):581-587.
[11] CHAUDHRY O,MACKANESS W.Rural and urban road network generalisation deriving 1:250,000 from OS MasterMap[C]//Proceeding of the 22nd International Cartographic Conference.Coruña:ICC.2005.
[12] ZHOU Qi,LI Zhilin.A comparative study of various strategies to concatenate road segments into strokes for map generalization[J].International Journal of Geographical Information Science,2012,26(4):691-715.
[13] 田晶,任畅,王一恒,等.对生成Stroke的自身最大适合策略的改进[J].武汉大学学报(信息科学版),2015,40(9):1209-1214.
[14] YANG Bisheng,LUAN Xuechen,LI Qingquan.Generating hierarchical strokes from urban street networks based on spatial pattern recognition[J].International Journal of Geographical Information Science,2011,25(12):2025-2050.
[15] 田晶,何青松,颜芬.道路网stroke生成问题的形式化表达与新算法[J].武汉大学学报(信息科学版),2014,39(5):556-560.
[16] REN Chang,FANG Huaqiang,LEI Yingzhe,et al.Network functionality oriented stroke building in road networks[C]//Proceedings of the 23rd International Conference on Geoinformatics.Wuhan:IEEE,2015.
[17] BREIMAN L.Random forests[J].Machine Learning,2001,45(1):5-32.
[18] 马京振,孙群,温伯威,等.结合轨迹数据的混合多特征道路网选取方法[J/OL].武汉大学学报(信息科学版):1-10[2021-08-11].https://doi.org/10.13203/j.whugis20190480.
[19] LATORA V,MARCHIORI M.Efficient behavior of small-world networks[J].Physical Review Letters,2001,87(19):198701.