Estimation of Originating-Destination Trips in Yangon by Using Big Data Source

The ubiquitous massive mobile phone data generation presents new opportunities to determine the requirements of transportation, disaster management and public health care systems. Currently, data from mobile phone records can help in identifying the location of the users while they are making trips. Generally, this estimation is achieved using traditional data collection methods; however, these methods are difficult to apply in developing countries with rapidly growing cities owing to the high population and limitation in conducting a survey. Call detail records (CDRs) are used as base data because they are valuable data sources and can reduce the cost and time limitations. The aim of this study is to estimate origin-destination (OD) trips from each zone by using the CDRs. The OD trips are estimated by using the CDRs of one week taken from Myanmar Post and Telecommunication mobile operator for over 1.9 million users per day in Yangon, the economic center of Myanmar. The OD trips are estimated from CDRs based on the location of the base station in a limited time window and time frame. If the same mobile users is observed in two different the ones within the time limit, it is assumed that the mobile user is coming out from the first zone and the trips represents an originating trip. This trip would be the destination trip for zone where the mobile user enters. In this study, the originating (outgoing) and destination trips (incoming) from each township on a weekday and weekend are determined. These data are useful for infrastructure development and urban transportation planning.

Download Full-text

Exploring Urban Spatial Feature with Dasymetric Mapping Based on Mobile Phone Data and LUR-2SFCAe Method

Sustainability ◽

10.3390/su10072432 ◽

2018 ◽

Vol 10 (7) ◽

pp. 2432 ◽

Cited By ~ 8

Author(s):

Lingbo Liu ◽

Zhenghong Peng ◽

Hao Wu ◽

Hongzan Jiao ◽

Yang Yu

Keyword(s):

Land Use ◽

Spatial Heterogeneity ◽

Mobile Phone ◽

Census Data ◽

Base Station ◽

Distance Decay ◽

Base Stations ◽

Mobile Phone Data ◽

Dasymetric Mapping ◽

Spatial Feature

Dasymetric mapping of high-resolution population facilitates the exploration of urban spatial feature. While most relevant studies are still challenged by weak spatial heterogeneity of ancillary data and quality of traditional census data, usually outdated, costly and inaccurate, this paper focuses on mobile phone data, which can be real-time and precise, and also strengthens spatial heterogeneity by its massive mobile phone base stations. However, user population recorded by mobile phone base stations have no fixed spatial boundary, and base stations often disperse in extremely uneven spatial distribution, this study defines a distance-decay supply–demand relation between mobile phone user population of gridded base station and its surrounding land patches, and outlines a dasymetric mapping method integrating two-step floating catchment area method (2SFCAe) and land use regression (LUR). The results indicate that LUR-2SFCAe method shows a high fitness of regression, provides population mapping at a finer scale and helps identify urban centrality and employment subcenters with detailed worktime and non-worktime populations. The work involving studies of dasymetric mapping based on LUR-2SFCAe method and mobile phone data proves to be encouraging, sheds light on the relationship between mobile phone users and nearby land use, brings about an integrated exploration of 2SFCAe in LUR with distance-decay effect and enhances spatial heterogeneity.

Download Full-text

Residents’ Traveling Track and Analysis Methods Based on Mobile Phone Data

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.926-930.2730 ◽

2014 ◽

Vol 926-930 ◽

pp. 2730-2734 ◽

Cited By ~ 1

Author(s):

Pan Li ◽

Ye Wen Gao ◽

Ju Wei Wu ◽

Xu Li ◽

Bing Bing Wu

Keyword(s):

Mobile Phone ◽

Base Station ◽

Urban Transport ◽

Mobile Phone Data ◽

Analysis Method ◽

Station Data ◽

National Economic ◽

Gis Data ◽

Mobile Phone Base Station ◽

National Economic Development

To avoid traffic congestion’s becoming the obstruct of social and national economic development is the final goal that professionals in transportation field make great efforts to pursue. At the same time, with the increasing popularity of mobile phones, we can get a lot of phone base station data to identify the residents’ travelling track. Thus we can analyze the residents’ travelling behavior and get residents’ travelling patterns and mechanism. Also, residents’ travelling could be induced and guided in order that the condition of urban transport can be improved. Based on the above background, this paper is mainly based on mobile phone base station data and GIS data analysis method research on the urban transportation of residents’ travelling track.

Download Full-text

Evaluation of home detection algorithms on mobile phone data using individual-level ground truth

EPJ Data Science ◽

10.1140/epjds/s13688-021-00284-9 ◽

2021 ◽

Vol 10 (1) ◽

Author(s):

Luca Pappalardo ◽

Leo Ferres ◽

Manuel Sacasa ◽

Ciro Cattuto ◽

Loreto Bravo

Keyword(s):

Mobile Phone ◽

Ground Truth ◽

Mobile Phone Data ◽

Data Generation ◽

Individual Level ◽

Detection Algorithms ◽

Home Location ◽

Residence Location ◽

The Individual ◽

And Control

AbstractInferring mobile phone users’ home location, i.e., assigning a location in space to a user based on data generated by the mobile phone network, is a central task in leveraging mobile phone data to study social and urban phenomena. Despite its widespread use, home detection relies on assumptions that are difficult to check without ground truth, i.e., where the individual who owns the device resides. In this paper, we present a dataset that comprises the mobile phone activity of sixty-five participants for whom the geographical coordinates of their residence location are known. The mobile phone activity refers to Call Detail Records (CDRs), eXtended Detail Records (XDRs), and Control Plane Records (CPRs), which vary in their temporal granularity and differ in the data generation mechanism. We provide an unprecedented evaluation of the accuracy of home detection algorithms and quantify the amount of data needed for each stream to carry out successful home detection for each stream. Our work is useful for researchers and practitioners to minimize data requests and maximize the accuracy of the home antenna location.

Download Full-text

The impact of biases in mobile phone ownership on estimates of human mobility

Journal of The Royal Society Interface ◽

10.1098/rsif.2012.0986 ◽

2013 ◽

Vol 10 (81) ◽

pp. 20120986 ◽

Cited By ~ 87

Author(s):

Amy Wesolowski ◽

Nathan Eagle ◽

Abdisalan M. Noor ◽

Robert W. Snow ◽

Caroline O. Buckee

Keyword(s):

Mobile Phone ◽

Human Mobility ◽

Population Level ◽

Time Frame ◽

Data Sources ◽

Mobile Phone Data ◽

Human Populations ◽

Mobility Patterns ◽

Wide Range ◽

The Impact

Mobile phone data are increasingly being used to quantify the movements of human populations for a wide range of social, scientific and public health research. However, making population-level inferences using these data is complicated by differential ownership of phones among different demographic groups that may exhibit variable mobility. Here, we quantify the effects of ownership bias on mobility estimates by coupling two data sources from the same country during the same time frame. We analyse mobility patterns from one of the largest mobile phone datasets studied, representing the daily movements of nearly 15 million individuals in Kenya over the course of a year. We couple this analysis with the results from a survey of socioeconomic status, mobile phone ownership and usage patterns across the country, providing regional estimates of population distributions of income, reported airtime expenditure and actual airtime expenditure across the country. We match the two data sources and show that mobility estimates are surprisingly robust to the substantial biases in phone ownership across different geographical and socioeconomic groups.

Download Full-text

Analysis of Antenna Types Performance in Mobile Phone Base Station

10.23918/iec2017.14 ◽

2017 ◽

Author(s):

Saba Fadhel Jaf ◽

Muhamed Fadhel Jaf ◽

Niyaz Fadhel Jaf

Keyword(s):

Mobile Phone ◽

Base Station ◽

Mobile Phone Base Station

Download Full-text

The Potential GTX Travel Demand using Mobile Phone Data

Journal of The Korean Society For Urban Railway ◽

10.24284/jkosur.2019.3.7.1.077 ◽

2019 ◽

Vol 7 (1) ◽

pp. 77-84

Author(s):

Jin Ki Eom ◽

Kwang-Sub Lee ◽

Ho-Chan Kwak ◽

Ji Young Song ◽

Myeong-Eon Seong

Keyword(s):

Mobile Phone ◽

Travel Demand ◽

Mobile Phone Data

Download Full-text

Effects of social distancing on the spreading of COVID-19 inferred from mobile phone data

Scientific Reports ◽

10.1038/s41598-021-81308-2 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Hamid Khataee ◽

Istvan Scheuring ◽

Andras Czirok ◽

Zoltan Neufeld

Keyword(s):

Mobile Phone ◽

Basic Reproductive Number ◽

Mobile Phone Data ◽

Reproductive Number ◽

Expansion Phase ◽

Social Distancing ◽

Exponential Expansion ◽

Total Death ◽

Mobility Reduction ◽

Epidemiological Parameters

AbstractA better understanding of how the COVID-19 pandemic responds to social distancing efforts is required for the control of future outbreaks and to calibrate partial lock-downs. We present quantitative relationships between key parameters characterizing the COVID-19 epidemiology and social distancing efforts of nine selected European countries. Epidemiological parameters were extracted from the number of daily deaths data, while mitigation efforts are estimated from mobile phone tracking data. The decrease of the basic reproductive number ($$R_0$$ R 0 ) as well as the duration of the initial exponential expansion phase of the epidemic strongly correlates with the magnitude of mobility reduction. Utilizing these relationships we decipher the relative impact of the timing and the extent of social distancing on the total death burden of the pandemic.

Download Full-text

Did the NSA and GCHQ Diminish Our Privacy? What the Control Account Should Say

Moral Philosophy and Politics ◽

10.1515/mopp-2019-0063 ◽

2020 ◽

Vol 7 (1) ◽

pp. 29-48 ◽

Cited By ~ 1

Author(s):

Leonhard Menges

Keyword(s):

Mobile Phone ◽

Personal Information ◽

Real Life ◽

Mobile Phone Data ◽

Standard Account ◽

Do So

AbstractA standard account of privacy says that it is essentially a kind of control over personal information. Many privacy scholars have argued against this claim by relying on so-called threatened loss cases. In these cases, personal information about an agent is easily available to another person, but not accessed. Critics contend that control accounts have the implausible implication that the privacy of the relevant agent is diminished in threatened loss cases. Recently, threatened loss cases have become important because Edward Snowden’s revelation of how the NSA and GCHQ collected Internet and mobile phone data presents us with a gigantic, real-life threatened loss case. In this paper, I will defend the control account of privacy against the argument that is based on threatened loss cases. I will do so by developing a new version of the control account that implies that the agents’ privacy is not diminished in threatened loss cases.

Download Full-text