Positioning Error in Mobile Phone Tracking Data with Consideration of Geographic Environment Factors

Xiaoqing Song,Yi Long,Ling Zhang

doi:10.5194/ica-abs-1-344-2019

Xiaoqing Song, Yi Long + Show 1 more

Open Access

https://doi.org/10.5194/ica-abs-1-344-2019

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Abstract

Abstract. Summary. This research contributes to both theory and application. This is an important supplement to the research on the quality and uncertainty of spatial big data and it will help mobile phone data play a more effective application value in future research. In recent years, the rapid development of data acquisition means has led to the rapid accumulation of spatial data and generated spatial big data with geographic location information. However, the uncertainty in spatial big data leads to the quality problem of spatial big data, which is one of the main bottlenecks restricting the effective utilization of spatial big data. As an important part of spatial big data, it is necessary to study the quality and uncertainty of mobile phone data. In view of this, we delve into the key geographical environment factors that affect the positioning error of mobile phone data, extract error evaluation indexes and construct the spatial distribution model of positioning error with machine learning algorithms. To explore the distribution law of mobile phone data positioning error under different geographical scenarios. In addition, considering the high accuracy of personal travel GPS positioning, this study takes personal travel GPS positioning data as the comparative object of mobile phone data for analysis.

Highlights

With the rapid development of information and communication technology and social media network, it is possible to get massive individual trajectory data which contains time and space information of individual mobility or activity on different temporal-spatial scale
We explored the key geographic environment factors affecting the positioning error of mobile phone data
The GPS data and mobile phone tracking data of the same volunteer were plotted into the space-time trajectories respectively

Summary

Introduction

With the rapid development of information and communication technology and social media network, it is possible to get massive individual trajectory data which contains time and space information of individual mobility or activity on different temporal-spatial scale. It is urgent to study the positioning error in mobile phone tracking data, including the source of error, influence factors and distribution characteristics of positioning error. What are the key geographic environment factors that affect the positioning accuracy of mobile phone tracking data? How do these key geographic factors affect the positioning accuracy?

Results

Conclusion