透過您的圖書館登入
IP:18.227.13.219
  • 期刊

運用電信資料推估靜態人口參數之研究

Estimation of Static Population Parameters Based on Telecommunication Data

摘要


由於手機的普及,近年來運用手機信令資料分析探索人口活動行為,已成為人口相關研究的熱門議題。本研究運用內政部所彙整三家電信公司在2020年11月的信令資料,推估包括夜間停留、白天活動(又細分為上午活動及下午活動)以及早餐、中餐、午茶及晚餐等四項特定旅次的人口參數推估,並透過與戶籍人口的比較,探討戶籍人口與實際夜間停留及日間活動人口分布差異。綜整發現電信信令推估之各項人口統計資料,可以展現各地區人口活動與居住間的關聯。除此之外,透過平假日之差異,可反映國人在各地區的休憩活動的情形。本研究運用電信資料探討人口相關參數推估的初步結果,可以做為後續相關研究的參考。

並列摘要


Due to the popularity of mobile phones, using mobile phone signaling data to explore population activity behavior has become a hot topic in population-related research field in recent years. This study uses the signaling of three telecom companies in the month of November 2020 integrated by the Ministry of Interior to estimate the population parameters, including night stay, daytime activity (subdivided into morning activity and afternoon activity), and four specific trips, such as: breakfast, lunch, tea and dinner. And explore the difference in the distribution of the actual night stay and daytime activity population by comparing them with the household registration population. Overall speaking, we have found that in addition to the estimation of the population parameters, mobile phone signaling can also show the correlation between population activities and residence among regions. Furthermore, the difference of the parameters between weekdays and holidays can reflect the leisure activities in different regions. These preliminary results of population-related parameter estimation using mobile phone signaling data can be used as a reference for subsequent related research.

參考文獻


Ahas, R., Silm, S., Järv, O., Saluveer, E., and Tiru, M. (2010). Using mobile positioning data to model locations meaningful to users of mobile phones. Journal of Urban Technology, 17(1), pages 3-27.
Alexander, L., Jiang, S. Murga, M., and González, M. C. (2015). Origin-destination trips by purpose and time of day inferred from mobile phone data. Transportation Research Part C: Emerging Technologies, 58, pages 240-250.
Calabrese, F., Ferrari, L., and Blondel, V. (2014). Urban sensing using mobile phone network data: a survey of research. ACM Computing Surveys, 47(2), pages 1-20.
Demissie, M. G., Phithakkitnukoon, S., Sukhvibul, T., Antunes, F., Gomes, R., and Bento, C. (2016). Inferring passenger travel demand to improve urban mobility in developing countries using cell phone data: a case study of Senegal. IEEE Transactions on Intelligent Transportation Systems, 17(9), pages 2466-2478.
Duan, z., Lei, Z., Zhang, M., Li, W., Fang, J., and Li, J. (2017). Understanding evacuation and impact of a metro collision on ridership using lare-scale mobile phone data. IET intelligent Transpsort Systems, 11(8), pages 511-520.

延伸閱讀