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This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 1 Land-Use Classification Using Taxi GPS Traces -
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- Publisher
- Springer International Publishing
- Copyright
- © Springer International Publishing Switzerland 2015
- ISBN
- 978-3-319-19341-0
- Pages
- 193 –217
- DOI
- 10.1007/978-3-319-19342-7_10
- Publisher site
- See Chapter on Publisher Site
Abstract
[Cities comprise various functional zones, including residential, educational, commercial zones, etc. It is important for urban planners to identify different functional zones and understand their spatial structure within the city in order to make better urban plans. In this chapter, we used 77,976,010 bus smart card records of Beijing City in one week in April 2008 and converted them into two-dimensional time series data of each bus platform, Then, through data mining and previous studies on citizens’ trip behavior, we established the DZoF (discovering zones of different functions) model based on SCD (smart card Data) and POIs (points of interest), and pooled the results at the TAZ (traffic analysis zone) level. The results suggested that DZoF model and cluster analysis based on dimension reduction and EM (expectation-maximization) algorithm can identify functional zones that well match the actual land uses in Beijing. The methodology in the present research can help urban planners and the public understand the complex urban spatial structure and contribute to the academia of urban geography and urban planning.]
Published: May 14, 2015
Keywords: Smart card data (SCD); Points of interest (POI); Functional zone; Human mobility; Beijing