Recognition of Functional Areas Based on Call Detail Records and Point of Interest Data


== Abstract ==

With the recent emergence of big data, there has been significant progress in the study of big data mining and rapid developments in urban computing. With the integration of planning and management in urban areas, there is an urgent need to focus on the identification of urban functional areas (UFAs) based on big data. This paper describes the concept of communication activity intensity, which is more meaningful than the number of communication activities or the user density in identifying UFAs. The impact of diverse geographical area subdivisions on the accuracy of UFA recognition is discussed, and a <jats:italic>k</jats:italic>-means clustering method for dynamic call detail record data and kernel density estimation technique for static point of interest data are established at the traffic analysis zone level. A case study on the region within Beijing’s 3rd Ring Road is conducted, and the results of UFA identification are qualitatively and quantitatively verified. The causes of large passenger flows on certain metro lines in Beijing are also analyzed. The highest identification accuracy is obtained for park and scenery areas, followed by residential areas and office areas. In conclusion, the proposed method offers a significant improvement over the identification accuracy of previous techniques, which verifies the reliability of the method.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_662980117-beopen865-8722-document.pdf</pdf>


== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.1155/2020/8956910 http://dx.doi.org/10.1155/2020/8956910] under the license http://creativecommons.org/licenses/by/4.0/

* [https://doi.org/10.1155/2020/8956910 https://doi.org/10.1155/2020/8956910]

* [http://downloads.hindawi.com/journals/jat/2020/8956910.pdf http://downloads.hindawi.com/journals/jat/2020/8956910.pdf],
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: [http://dx.doi.org/10.1155/2020/8956910 http://dx.doi.org/10.1155/2020/8956910] under the license cc-by

* [http://dx.doi.org/10.1155/2020/8956910 http://dx.doi.org/10.1155/2020/8956910],
: [https://doaj.org/toc/0197-6729 https://doaj.org/toc/0197-6729],
: [https://doaj.org/toc/2042-3195 https://doaj.org/toc/2042-3195] under the license http://creativecommons.org/licenses/by/4.0/

* [https://www.hindawi.com/journals/jat/2020/8956910 https://www.hindawi.com/journals/jat/2020/8956910],
: [http://downloads.hindawi.com/journals/jat/2020/8956910.pdf http://downloads.hindawi.com/journals/jat/2020/8956910.pdf],
: [https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002251707210534 https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002251707210534],
: [https://academic.microsoft.com/#/detail/3014605128 https://academic.microsoft.com/#/detail/3014605128]