地球信息科学学报

地球信息科学学报 ›› 2022, Vol. 24 ›› Issue (10): 1982-1992.doi: 10.12082/dqxxkx.2022.210601

• 城市功能 • 上一篇    下一篇

从多年份出租车出行分布数据中探测城市完备功能子区域的方法研究

甄卓1(), 康朝贵1,2,*()   

  1. 1.武汉大学遥感信息工程学院,武汉 430079
    2.中国地质大学（武汉）国家地理信息系统工程技术研究中心,武汉 430078
  • 收稿日期:2021-10-03 修回日期:2021-12-01 出版日期:2022-10-25 发布日期:2022-12-25
  • 通讯作者: *康朝贵（1986— ）,男,湖南衡阳人,教授,主要从事城市信息学研究。E-mail: kangchaogui@cug.edu.cn
  • 作者简介:甄卓（1996— ）,男,辽宁朝阳人,硕士研究生,主要从事地理可视分析研究。E-mail: lazzyzhen@whu.edu.cn
  • 基金资助:
    国家重点研发计划项目(2017YFB0503600);国家重点研发计划项目(2019YFE0106500);国家自然科学基金项目(41601484);国家自然科学基金项目(41830645)

Delineating Urban Subdistricts with Comprehensive Functions from Taxi Trajectory Data in Multiple Years

ZHEN Zhuo1(), KANG Chaogui1,2,*()   

  1. 1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
    2. National Engineering Research Center of Geographic Information System, China University of Geosciences (Wuhan), Wuhan 430078, China
  • Received:2021-10-03 Revised:2021-12-01 Online:2022-10-25 Published:2022-12-25
  • Supported by:
    National Key Research and Development Program of China(2017YFB0503600);National Key Research and Development Program of China(2019YFE0106500);National Natural Science Foundation of China(41601484);National Natural Science Foundation of China(41830845)

RichHTML

PDF (PC)

赞

摘要：

研究城市功能子区域的动态演变特征可以帮助人们理解城市发展规律和进行城市规划,然而对这种动态性进行分析的手段一直以来较为匮乏。城市出行大数据的出现虽然提供了刻画和分析功能子区及其动态的工具,但是在方法层面仍缺乏克服长时期出行数据内在时空随机性的方案。本研究尝试从长时间段人口稳定流动的层面来分析城市内部是否存在具有完备功能的子区域。将具有完备功能的子区域定义为城市结构中内部流量显著高于外部连通流量且相对稳定的子区域的集合,并利用多年份的出租车轨迹数据来构建城市居民出行网络,进而利用网络分析中的社团发现算法来探测城市的完备功能子区域及其随时间的动态变化。为了实现这一目标,本研究提出了一种针对时序轨迹数据的时空耦合网络模型,尝试克服多年份出租车出行数据中潜在的时空随机性（如：时空突变）,并在此模型的基础上提出了一种基于多层网络社团发现算法的城市完备功能子区动态探测手段,实现对城市完备功能子区域时空演变的追踪分析。最后,以北京市2012—2017年的出租车轨迹数据为例,使用该方法实现了北京市城区完备功能子区的动态探测,进而揭示了4类不同完备功能子区域的特征与发展态势。

关键词: 移动轨迹分析, 城市功能子区, 社团发现, 时空网络模型, 出租车数据, 北京市

Abstract:

With the penetration of portable devices such as mobile phones and navigators that carry GPS sensors, the trajectory data generated by people's daily life have rapidly increased. Such kind of large-scale trajectory data have been gradually applied to traffic planning, urban management, behavioral analysis, recommendation system, and other fields. In urban studies, urban sub-center detection has always been one of the important topics in the exploration of urbanization. In this paper, we define urban subdistricts with comprehensive functions as a collection of sub-regions within which the internal traffic is significantly higher than their external connected traffic. To detect these subdistricts, a spatiotemporal coupling network model for time series trajectory data is proposed. Based on this model, a multi-layer network community discovery algorithm is proposed to detect dynamic activity sub-area. Taking the taxi trajectory data of Beijing from 2012 to 2017 as an example, this method is used to realize the dynamic detection and analysis of subdistricts with comprehensive urban functions in Beijing.

Key words: trajectory analysis, urban functional area, community discovery, spatio-temporal network model, taxi trajectory, Beijing