Spatio-temporal Dynamics of Population in Shanghai: A Case Study Based on Cell Phone Signaling Data

De, Wang; Zhong, Weijing; Yin, Zhenxuan; Xie, Dacheng; Luo, Xiao

doi:10.1007/978-3-319-51929-6_13

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…When the same mobile phone card is present in a particular area of the city, the time and duration of the mobile phone signaling generated in that area can be detected by the mobile phone base station. Therefore, the mobile phone signaling data can reflect the time and duration of the users in a particular location [15]. In this research, mobile phone base stations are used to detect the time intervals during the day when mobile phone signals appear in different city areas.…”

Section: -Hour Static Observation Of City-wide Cellular Signaling Datamentioning

confidence: 99%

Prediction of Traffic Volume of Motor Vehicles Based on Mobile Phone Signaling Technology

Shang¹,

Su²,

Hu³

et al. 2023

Computers, Materials &Amp; Continua

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Urban traffic volume detection is an essential part of traffic planning in terms of urban planning in China. To improve the statistics efficiency of road traffic volume, this thesis proposes a method for predicting motor vehicle traffic volume on urban roads in small and medium-sized cities during the traffic peak hour by using mobile signal technology. The method is verified through simulation experiments, and the limitations and the improvement methods are discussed. This research can be divided into three parts: Firstly, the traffic patterns of small and medium-sized cities are obtained through a questionnaire survey. A total of 19745 residents were surveyed in Luohe, a medium-sized city in China and five travel modes of local people were obtained. Secondly, after the characteristics of residents' rest and working time are investigated, a method is proposed in this study for the distribution of urban residential and working places based on mobile phone signaling technology. Finally, methods for predicting traffic volume of these travel modes are proposed after the characteristics of these travel modes and methods for the distribution of urban residential and working places are analyzed. Based on the actual traffic volume data observed at offline intersections, the project team takes Luohe city as the research object and it verifies the accuracy of the prediction method by comparing the prediction data. The prediction simulation results of traffic volume show that the average error rate of traffic volume is unstable. The error rate ranges from 10% to 30%. In this thesis, simulation experiments and field investigations are adopted to analyze why these errors occur.

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Section: -Hour Static Observation Of City-wide Cellular Signaling Datamentioning

confidence: 99%

Prediction of Traffic Volume of Motor Vehicles Based on Mobile Phone Signaling Technology

Shang¹,

Su²,

Hu³

et al. 2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…The mobility will be recorded once the user's phone is on. It can be used to infer the majority and represent the event with high probability (Wang, Zhong, Xie, & Ye, 2015), which is not only about user coverage but also about the trend of regional situation. As long as people use Tencent application, his/her move could be counted into a line between locations in the map.…”

Section: Human Movement and Traffic Flow From Tencent (Qq) Location B...mentioning

confidence: 99%

Deciphering the spatial structure of China's megacity region: A new bay area—The Guangdong-Hong Kong-Macao Greater Bay Area in the making

Hui

Chen

et al. 2020

Cities

191

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“…The process of collecting this data is also time-consuming and labor-intensive. With the big data era, a large number of new geographical data sources have emerged [7][8][9][10], such as geotagged photos [11][12][13], cell phone signaling data [14][15][16], and smart card data [17][18][19]. They provide a new direction for the study of urban tourism space.…”

Section: Introductionmentioning

confidence: 99%

A Novel Framework for Exploring the Spatial Characteristics of Leisure Tourism Using Multisource Data: A Case Study of Qingdao, China

Shang

Wen

Bai

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Spatial characteristics of leisure tourism resources is essential for human life, the urban economy, and tourism planning. This paper presents a novel framework to explore these characteristics based on multi-source data, such as points of interest (POIs), OpenStreetMap roads, Sentinel-2 Multispectral Instrument (MSI) images, and other data, and proposes a new tourism area identification method by integrating attractiveness of attractions with term frequency-inverse document frequency. The roles of the influencing factors were measured by using the geodetector and related statistical analyses. The results showed that the resources were centered on Jiaozhou Bay, and their axial direction was "northeast to southwest." The distribution of the overall resources was characterized by "one cluster with multiple core points," and different types of resources had different aggregation distributions. The Recreational Recreation (RR) and Cultural Leisure (CL) zones were more likely to be distributed in and near the center of each district, and their numbers were high, while the Shopping Leisure (SL) and Natural Recreation (NR) zones were the opposite. The distribution of each type of resource was the result of a combination of factors working together, except for NR resources, which were mainly influenced by natural factors, while others were mainly affected by socioeconomic factors. The study findings are instructive for tourism planning.

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Spatio-temporal Dynamics of Population in Shanghai: A Case Study Based on Cell Phone Signaling Data

Cited by 5 publications

References 14 publications

Prediction of Traffic Volume of Motor Vehicles Based on Mobile Phone Signaling Technology

Prediction of Traffic Volume of Motor Vehicles Based on Mobile Phone Signaling Technology

Deciphering the spatial structure of China's megacity region: A new bay area—The Guangdong-Hong Kong-Macao Greater Bay Area in the making

A Novel Framework for Exploring the Spatial Characteristics of Leisure Tourism Using Multisource Data: A Case Study of Qingdao, China

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