Inferring the Accurate Locations of Noise Records in Mobile Phone Location Data

被引:0
|
作者
Song, Xiaoqing [1 ]
Lu, Yi [1 ]
Jiang, Shumei [1 ]
Jiang, Wei [1 ]
Wu, Yue [2 ,3 ,4 ]
Long, Yi [2 ,3 ,4 ]
机构
[1] School of Geography and Tourism, Anhui Normal University, Wuhu, China
[2] Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing, China
[3] State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing, China
[4] Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
基金
中国国家自然科学基金;
关键词
Location based services - Smartphones;
D O I
10.1111/tgis.13261
中图分类号
学科分类号
摘要
The positioning uncertainty of mobile phone location (MPL) data greatly influences location services and crowd behavior analysis. Although many achievements have been made in controlling its main sources (signal drift and ping-pong effects), several problems, such as single-oscillation patterns, insufficient position optimization, and a lack of effective evaluation, remain. In this study, a set of MPL data quality optimization methods are proposed. First, the characteristics of drift records and the oscillation patterns of ping-pong records are discussed. The quality of the MPL data is subsequently controlled with the proposed feature-based drift-record detection method, complex oscillation pattern-based ping-pong-record detection method, and cumulative duration weighting-based ping-pong-record optimization method. These methods are applied to the MPL dataset of a major operator in Nanjing city, and the optimization effect is evaluated with GPS data collected synchronously. The results show that the proposed detection and optimization methods can effectively improve the accuracy of MPL data. © 2024 The Author(s). Transactions in GIS published by John Wiley & Sons Ltd.
引用
下载
收藏
页码:2668 / 2686
相关论文
共 50 条
  • [21] Methods for Inferring Route Choice of Commuting Trip From Mobile Phone Network Data
    Sakamanee, Pitchaya
    Phithakkitnukoon, Santi
    Smoreda, Zbigniew
    Ratti, Carlo
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2020, 9 (05)
  • [22] Temporality in the delimitation of functional regions: the use of mobile phone location data
    Halas, Marian
    REGIONAL STUDIES, 2024,
  • [23] Population movements based on mobile phone location data: the Czech Republic
    Halas, Marian
    Blazek, Vojtech
    Klapka, Pavel
    Kraft, Stanislav
    JOURNAL OF MAPS, 2021, 17 (01): : 116 - 122
  • [24] Using Mobile Phone Location Data to Develop External Trip Models
    Huntsinger, Leta F.
    Ward, Kyle
    TRANSPORTATION RESEARCH RECORD, 2015, (2499) : 25 - 32
  • [25] Estimating freeway traffic measures from mobile phone location data
    Gao Hongyan
    Liu Fasheng
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2013, 229 (01) : 252 - 260
  • [26] Comparing Visitors' Behavior Through Mobile Phone Users' Location Data
    Yamamoto, Masahide
    PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT, 2018, : 411 - 420
  • [27] Measures of Human Mobility Using Mobile Phone Records Enhanced with GIS Data
    Williams, Nathalie E.
    Thomas, Timothy A.
    Dunbar, Matthew
    Eagle, Nathan
    Dobra, Adrian
    PLOS ONE, 2015, 10 (07):
  • [28] Georeferenced Analysis of Urban Nightlife and Noise Based on Mobile Phone Data
    Elvas, Luis B.
    Nunes, Miguel
    Ferreira, Joao C.
    Francisco, Bruno
    Afonso, Jose A.
    APPLIED SCIENCES-BASEL, 2024, 14 (01):
  • [29] Inferring Origin-Destination Flows Using Mobile Phone Data: A Case Study of Senegal
    Demissie, Merkebe Getachew
    Antunes, Francisco
    Bento, Carlos
    Phithakkitnukoon, Santi
    Sukhvibul, Titipat
    2016 13TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING/ELECTRONICS, COMPUTER, TELECOMMUNICATIONS AND INFORMATION TECHNOLOGY (ECTI-CON), 2016,
  • [30] Inferring fine-grained transport modes from mobile phone cellular signaling data
    Chin, Kimberley
    Huang, Haosheng
    Horn, Christopher
    Kasanicky, Ivan
    Weibel, Robert
    COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 2019, 77