More than one-fourth of people in Taipei during the day are from New Taipei City, making it the largest intercity commuter flow in Taiwan, data from mobile signals showed.
The Ministry of the Interior yesterday unveiled the data on mobile device signals in November last year and its analysis report on the de facto population distribution.
Taipei has the biggest intercity commuter traffic flow, as 25.2 percent of the city’s de facto population during the day comes from New Taipei City, followed by 2.0 percent and 1.4 percent from Taoyuan and Keelung respectively, the data showed.
Photo: Ann Wang, Reuters
It also showed that Taipei’s population during the day was 652,235 more than its nighttime population, or a 24.97 percent difference, the biggest among all cities and counties, followed by Taoyuan at 36,626 or 1.42 percent.
Transportation networks have connected surrounding residential areas to the industrial and commercial hotspots in Taipei, forming a commuter life circle that attracts substantial commuter inflow, the report said.
The data also showed that New Taipei City has the largest nighttime population, nearly 4.32 million people, followed by Taichung’s 3.05 million, Taipei’s 2.61 million and Taoyuan’s 2.58 million.
Taoyuan’s nighttime population has risen by 38,488 individuals, or 1.51 percent, from 2020 for the same period, it showed.
The city has seen the largest residential population inflow due to lower residential costs, emergent redevelopment projects and access to the Taoyuan International Airport MRT, the report said.
As for travel in different regions, the number of travelers to Miaoli County’s Nanjhuang Township (南庄), Taian Township (泰安) and Shihtan Township (獅潭); Hsinchu County’s Beipu Township (北埔), Wufong Township (五峰), Jianshih Township (尖石), Emei Township (峨嵋) and Hengshan Township (橫山); Pingtung County’s Wutai Township (霧台) and Taoyuan’s Fusing District (復興) more than doubled from weekdays to weekends during the afternoon, the report said.
They are key regions for local tourism development as most of them boast mountainous areas, hot springs and old streets, it added.
A table of commuters’ point of departure and destination during the day and at night has been included this year to better understand their commuting behavior, the report said, adding that the statistics are based on mobile signal data and that sensitive data such as gender, age and other private information were not accessed.
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