载体轨迹停留信息提取的核密度法及其可视化

doi:10.11947/j.AGCS.2016.20150347

测绘学报 ›› 2016, Vol. 45 ›› Issue (9): 1122-1131.doi: 10.11947/j.AGCS.2016.20150347

载体轨迹停留信息提取的核密度法及其可视化

向隆刚^1,2, 邵晓天^1,2

1. 武汉大学测绘遥感信息工程国家重点实验室, 湖北武汉 430079;
2. 地球空间信息技术协同创新中心, 湖北武汉 430079

收稿日期:2015-07-08 修回日期:2016-04-05 出版日期:2016-09-20 发布日期:2016-09-29
通讯作者: 邵晓天 E-mail:shaoxiaotian@whu.edu.cn
作者简介:向隆刚(1976-),男,博士,副教授,主要从事空间数据库、轨迹数据处理分析与虚拟地球技术研究.E-mail:geoxlg@whu.edu.cn
基金资助:
国家自然科学基金资助项目（41471374；41001296）

Visualization and Extraction of Trajectory Stops Based on Kernel-density

XIANG Longgang^1,2, SHAO Xiaotian^1,2

1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;
2. Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China

Received:2015-07-08 Revised:2016-04-05 Online:2016-09-20 Published:2016-09-29
Supported by:
The National Natural Science Foundation of China (Nos.41471374;41001296)

摘要/Abstract

摘要： 轨迹停留蕴含重要语义信息，其有效提取是开展轨迹Stop/Move模型分析的前提。本文首先依据核密度思想，通过累计邻域点时空贡献来定义轨迹点的停留指数，在此基础上设计了停留指数图，以图形方式直观表达轨迹点的时空聚集程度变化。进一步针对源于停留指数的潜在停留段，提出了一种基于潜在停留段时空临近关系的逐级合并算法，以自动发现和提取停留。试验表明，该算法兼顾停留识别的完整性和准确性，可以有效识别复杂多样的轨迹停留，即使面对噪声严重的轨迹，停留提取的正确率依然较高。

关键词: 核密度, 轨迹, 停留指数, 停留, 时空贡献

Abstract: Trajectory stops imply important semantic information, and the extraction of trajectory stops is the premise to carry out advanced Stop/Move analysis. This paper, based on the idea of kernel density, firstly introduces the concept of stop index, which is derived by cumulating spatio-temporal contribution of neighboring points, and further designs stop index graph to intuitively visualize the evolution of spatio-clustering degree during a trajectory. Importantly, stops index and its graph are related to spatial scale through neighboring radius, which then can be exploited to analyze trajectory stops under multiple scales. In addition, this paper introduces stop sequence rooted from stop index, and proposes an algorithm for the automatic extraction of trajectory stops by progressively merging stop sequences. According to the algorithm, a stop under strong GPS signal exactly corresponds to a stop sequence, while a stop under weak GPS signal could be derived by merging multiple stop sequences. Experiments based on own-acquired and GeoLife trajectories show that the algorithm has achieves the balance between the completeness and accuracy of stop extraction, and could effectively discover and extract complex and diverse trajectory stops. Even facing trajectories with serious drift noises, the algorithm still achieves a high rate of accuracy on stop extraction.

Key words: kernel density, trajectory, stop index, stop, spatio-temporal contribution

中图分类号:

P208

向隆刚, 邵晓天. 载体轨迹停留信息提取的核密度法及其可视化[J]. 测绘学报, 2016, 45(9): 1122-1131.

XIANG Longgang, SHAO Xiaotian. Visualization and Extraction of Trajectory Stops Based on Kernel-density[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(9): 1122-1131.

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载体轨迹停留信息提取的核密度法及其可视化

Visualization and Extraction of Trajectory Stops Based on Kernel-density

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