测绘学报 ›› 2017, Vol. 46 ›› Issue (6): 770-779.doi: 10.11947/j.AGCS.2017.20160614
唐炉亮1, 牛乐1, 杨雪1, 张霞2, 李清泉1,2, 萧世伦1,3
收稿日期:
2016-12-02
修回日期:
2017-04-27
出版日期:
2017-06-20
发布日期:
2017-06-28
通讯作者:
牛乐
E-mail:niule_gis@163.com
作者简介:
唐炉亮(1973—),男,博士,教授,研究方向为GIS-T、时空GIS、轨迹大数据挖掘等。E-mail:tll@whu.edu.cn
基金资助:
TANG Luliang1, NIU Le1, YANG Xue1, ZHANG Xia2, LI Qingquan1,2, XIAO Shilun1,3
Received:
2016-12-02
Revised:
2017-04-27
Online:
2017-06-20
Published:
2017-06-28
Supported by:
摘要: 交叉口是城市交通路网生成、更新的重要组成部分。本文基于车辆时空轨迹大数据,提出了一种城市交叉口自动识别方法。该方法首先通过轨迹跟踪识别轨迹数据中包含的车辆转向点对;然后基于距离和角度的生长聚类方法进行转向点对的空间聚类,并采用基于局部点连通性的聚类方法识别交叉口;最后利用交叉口范围圆和转向点对提取城市各级别路网下的交叉口结构。以武汉市出租车轨迹大数据为例,对武汉市城区内189个交叉口进行了探测。试验结果表明,本文所提方法可以准确地从轨迹大数据中识别出城市交叉口及其结构。
中图分类号:
唐炉亮, 牛乐, 杨雪, 张霞, 李清泉, 萧世伦. 利用轨迹大数据进行城市道路交叉口识别及结构提取[J]. 测绘学报, 2017, 46(6): 770-779.
TANG Luliang, NIU Le, YANG Xue, ZHANG Xia, LI Qingquan, XIAO Shilun. Urban Intersection Recognition and Construction Based on Big Trace Data[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(6): 770-779.
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