[1]林杰,陈崇成.采用代表点插值的道路网提取方法[J].华侨大学学报(自然科学版),2018,39(1):98-102.[doi:10.11830/ISSN.1000-5013.201701112]
　LIN Jie,CHEN Chongcheng.Road Network Extraction Method Using Representative Points Interpolation[J].Journal of Huaqiao University(Natural Science),2018,39(1):98-102.[doi:10.11830/ISSN.1000-5013.201701112]
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采用代表点插值的道路网提取方法()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第39卷
期数:
2018年第1期
页码:
98-102
栏目:
出版日期:
2018-01-17

文章信息/Info

Title:
Road Network Extraction Method Using Representative Points Interpolation
文章编号:
1000-5013(2018)01-0098-05
作者:
林杰1; 2; 3;  陈崇成1; 3
1. 福州大学 空间数据挖掘与信息共享教育部重点实验室, 福建 福州 350002;2. 福建工程学院 数理学院, 福建 福州 350108;3. 福州大学 福建省空间信息工程研究中心, 福建 福州 350002
Author(s):
LIN Jie1; 2; 3;  CHEN Chongcheng1; 3
1. Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350002, China; 2. College of Mathematics and Physics, Fujian University of Technology, Fuzhou 350108, China; 3. Spatial Information Research Centre of Fujian, Fuzhou University, Fuzhou 350002, China
关键词:
轨迹数据;  道路网;  海量数据挖掘;  聚类算法;  插值算法
Keywords:
trajectory data;  road network;  massive data mining;  clustering algorithm;  interpolation
分类号:
TP391
DOI:
10.11830/ISSN.1000-5013.201701112
文献标志码:
A
摘要:
针对浮动车轨迹数据包含较多异常数据导致道路网提取效果不好的问题,提出一种渐近方式的代表点插值算法.首先,采用DBSCAN聚类算法对转弯点聚类求出路口位置,计算经过两个路口间的轨迹,合并轨迹.然后,采用改进的代表点算法提取代表点.最后,利用最短路算法在由代表点建立的Delaunay三角网上插值,从而得到道路网.实验结果表明:该方法能有效地从带有较多异常的轨迹数据中取出由复杂网络构建的道路网,具有较好的实用性.
Abstract:
Aiming at the problem of the floating car trajectory data which contains many abnormal data leading to the bad road network extracting, the paper proposes a way of asymptotic representative point interpolation algorithm. Firstly, the method uses the DBSCAN clustering algorithm to find the intersections position, computes the trajectories between two intersections, and then merge the trajectories. Then an improved representative point algorithm is used for the extraction of representative points. Finally, using the shortest path algorithm to interpolate in Delaunay triangulation net which is established according to the representative points, road network is obtained. The experimental results show that the road network constructed by complex network can be extracted with the trajectory data which contains abnormal data, and has good practicability.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2017-01-05
通信作者: 林杰(1980-),男,讲师,博士研究生,主要从事时空数据挖掘的研究.E-mail:fjlinjie@163.com.
基金项目: 国家自然科学基金资助项目(41471333)
更新日期/Last Update: 2018-01-20