2018
DOI: 10.1007/s41651-018-0013-y
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Exploring Regionalization in the Network Urban Space

Abstract: Isotropic homogeneity does not hold in urban areas. Street networks exert a great influence on human mobility. As a result, city structure is largely shaped by this network, especially the streets that carry a higher volume of traffic. In practice, small areas along network edges often need to be grouped into regions for management purposes. This work formalizes the extension to the P-regions problem that takes the network as the underlying constraint and proposes a heuristic-based approach to solve the proble… Show more

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Cited by 16 publications
(9 citation statements)
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“…It was found that the annual daytime SUHII values of these cities exhibited significant and positive relationships with the population (R 2 = 0.51, p < 0.05) and urban area (R 2 = 0.47, p < 0.05). Meanwhile, the altitude has little effect on the SUHII [58][59][60]. In this study, vegetation and anthropogenic heat emissions played a larger role in interpreting variations in the daytime and night-time SUHII values, respectively.…”
Section: The Effects Of Each Factor On Suhiimentioning
confidence: 70%
“…It was found that the annual daytime SUHII values of these cities exhibited significant and positive relationships with the population (R 2 = 0.51, p < 0.05) and urban area (R 2 = 0.47, p < 0.05). Meanwhile, the altitude has little effect on the SUHII [58][59][60]. In this study, vegetation and anthropogenic heat emissions played a larger role in interpreting variations in the daytime and night-time SUHII values, respectively.…”
Section: The Effects Of Each Factor On Suhiimentioning
confidence: 70%
“…Lastly, we also argue that social differentiation along class or gender influences experiences with work, migrancy and space (Ye et al, 2018). Class position and gender will make the experience of a free movement regime markedly different from one person to the other.…”
Section: Conceptualizing Differences In Mobility and Working Experiences Of Different Ecowas Migrantsmentioning
confidence: 79%
“…That is, to a group of nodes that have more dense ties within the group than to nodes outside the group ( Luthe & Wyss, 2016 ). Community detection provides a classical method for understanding the spatial structure of complex networks in geographical space ( Ye, She, & Benya, 2018 ; Zhong, Arisona, Huang, Batty, & Schmitt, 2014 ). For tourism research, it is a data-driven method of extracting tourism districts ( Shao, Zhang, & Li, 2017 ), which can be used in comparison with official administrative divisions.…”
Section: Methodsmentioning
confidence: 99%