| 城市邻近基站间人群流动时空变化同步性分析 |
| |
| 引用本文： | 朱菁玮,方志祥,杨喜平,尹凌.城市邻近基站间人群流动时空变化同步性分析[J].地球信息科学,2018,20(6):844-853. |
| |
| 作者姓名： | 朱菁玮 方志祥 杨喜平 尹凌 |
| |
| 作者单位： | 1. 武汉大学测绘遥感信息工程国家重点实验室,武汉 4300792. 地球空间信息技术协同创新中心,武汉 4300793. 陕西师范大学地理科学与旅游学院,西安 7101194. 中国科学院深圳先进技术研究院,深圳 518055 |
| |
| 基金项目： | 国家自然科学基金项目(41231171、41771473);中央高校基本科研业务费专项资金项目（2042017kf0235、 |
| |
| 摘 要： | 不同区域人群流量随时间的变化可以反映城市结构的空间差异。现有对于城市人群空间分布特性的研究大都以人群密度计算为基础,注重时空切片尺度,但是不能有效刻画邻域空间单元间流量变化的时空过程同步特性。本文提出一种基于基站间流量变化过程相似度的城市邻域基站流量变化同步性度量方法,量化分析不同区域的人群进出流量过程的相似程度,研究城市中具有相同人群流量变化过程的同步性区域空间分布规律。以深圳市为例,对城市同步性区域的空间分布与特点进行剖析。实验发现：计算同步性时参数选择需根据城市本身基站分布及流量特点分析,一般研究中,城市基站平均距离可作为邻近区域半径d,描述基站间流量变化相似度的特征阈值λ选取与邻近区域半径有关,半径越小,阈值取值越小。通过基站人群流量同步性得到的城市同步区域的空间分布不同于行政区域划分结果,同步区域面积小,划分更为精细;且规划级别越高的中心区,其范围内基站同步区域数目越多。最后,将同步区域结果与流量密度图对比,发现该方法不仅能够发现流量变化大的同步区域,并且能够发现城市中流量变化小的同步区域。本文提出的方法能量化衡量区域流量变化同步性并发现具有不同流量变化特点的同步性整体区域,对城市人群空间变化特点进行分析,可用于指导和评价城市规划与实际人群活动区域效果,以及城市服务设施布局等。
|
| 关 键 词： | 手机数据 时空轨迹相似度 流量同步性 同步区域 流量变化过程 |
| 收稿时间： | 2017-11-20 |
Flow Synchronization of Mobile Communication Network in Cities Areas |
| |
| ZHU Jingwei,FANG Zhixiang,YANG Xiping,YIN Ling.Flow Synchronization of Mobile Communication Network in Cities Areas[J].Geo-information Science,2018,20(6):844-853. |
| |
| Authors: | ZHU Jingwei FANG Zhixiang YANG Xiping YIN Ling |
| |
| Institution: | 1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China2. Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China3. School of Geography and Tourism, Shaanxi Normal University, Xi′an, 710119, China;4. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China. |
| |
| Abstract: | Distribution and movement of people in urban areas are important information for studying urban dynamics and crowd displacement rhythm. The temporal variation of people flow between different spatial regions shows how people interact with physical locations and is highly related to its function and structure in the city. Previous researches usually use density-based approaches to investigate the temporal variation of people flows in different spatial regions. This kind of approach can present time slice-based hot-spot maps but cannot reflect the consistency of changing processes. Therefore, this paper proposes an approach of synchronization measurement to fill in this gap. Our method is designed to measure the similarity of temporal people flow processes between stations in the 3D feature space and quantify property of synchronization of communication network areas based on the average similarity. An experiment of measuring synchronization was conducted using a dataset of mobile phone data in Shenzhen. The people flow processes within this city was derived from the mobile phone dataset. The results show: firstly, the neighboring-area radius and feature space threshold depend on the distribution of mobile station and flow process in corresponding serving areas. In most cases, the neighboring-area radius can be set as the average distance between mobile stations. The feature space threshold depends on the neighboring area radius, and the smaller the radius, the smaller the threshold should be. Secondly, different from administrative areas, the synchronized areas show the characteristics of human dynamics in the city with a smaller spatial unit. We found that the centers with higher level of planning have more synchronized regions with relatively small area in them. Finally, compared with the density map result, our approach indicates that the synchronized regions not only exist in the city centers with high flow changes but also in rural areas with relatively small flow changes. Combined with additional information such as land use attributes, the synchronized areas clarify the spatial structure of the population and its aggregated boundary effect in the city. This approach can be used to assess the output of urban planning and optimize the distribution of service facilities such as emergency management and transportation network design. |
| |
| Keywords: | mobile phone data space-time trajectory similarity flow synchronization synchronized areas flow processes |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《地球信息科学》浏览原始摘要信息 |
| 点击此处可从《地球信息科学》下载免费的PDF全文 |
|
