Scipediacontent: Scipediacontent moved page Draft Content 718700765 to Zhou et al 2018d

2021-02-12T15:01:42Z

Scipediacontent moved page Draft Content 718700765 to Zhou et al 2018d

Scipediacontent: Created page with " == Abstract == Understanding commuting patterns has been a classic research topic in the fields of geography, transportation and urban planning, and it is significant for ha..."

2021-02-12T15:01:38Z

Created page with " == Abstract == Understanding commuting patterns has been a classic research topic in the fields of geography, transportation and urban planning, and it is significant for ha..."

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== Abstract ==

Understanding commuting patterns has been a classic research topic in the fields of geography, transportation and urban planning, and it is significant for handling the increasingly serious urban traffic congestion and air pollution and their impacts on the quality of life. Traditional studies have used travel survey data to investigate commuting from the aspects of commuting mode, efficiency and influence factors. Due to the limited sample size of these data, it is difficult to examine the large-scale commuting patterns of urban citizens, especially when exploring the spatial structure of commuting. This study attempts to understand the spatial structure characteristics generated by human commutes to work by using massive mobile phone datasets. A three-step workflow was proposed to accomplish this goal, which includes extracting the home and work locations of phone users, detecting the communities from the commuting network, and identifying the commuting convergence and divergence areas for each community. A case study of Shenzhen, China was implemented to determine the commuting structure. We found that there are thirteen communities detected from the commuting network and that some of the communities are in accordance with urban planning; moreover, spatial polycentric polygons exist in each community. These findings can be referenced by urban planners or policy-makers to optimize the spatial layout of the urban functional zones.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_718700765-beopen505-8509-document.pdf</pdf>

== Original document ==

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

* [http://dx.doi.org/10.3390/su10051435 http://dx.doi.org/10.3390/su10051435] under the license https://creativecommons.org/licenses/by

* [https://www.mdpi.com/2071-1050/10/5/1435/pdf https://www.mdpi.com/2071-1050/10/5/1435/pdf] under the license https://creativecommons.org/licenses/by/4.0

* [http://www.mdpi.com/2071-1050/10/5/1435/pdf http://www.mdpi.com/2071-1050/10/5/1435/pdf],
: [http://dx.doi.org/10.3390/su10051435 http://dx.doi.org/10.3390/su10051435] under the license cc-by

* [http://www.mdpi.com/2071-1050/10/5/1435/pdf http://www.mdpi.com/2071-1050/10/5/1435/pdf],
: [https://academic.microsoft.com/#/detail/2800899271 https://academic.microsoft.com/#/detail/2800899271] under the license https://creativecommons.org/licenses/by/4.0/

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Zhou et al 2018d - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 718700765 to Zhou et al 2018d

Scipediacontent: Created page with " == Abstract == Understanding commuting patterns has been a classic research topic in the fields of geography, transportation and urban planning, and it is significant for ha..."