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020 _a9789819781850
_9978-981-97-8185-0
024 7 _a10.1007/978-981-97-8185-0
_2doi
050 4 _aGF
072 7 _aRGC
_2bicssc
072 7 _aSOC015000
_2bisacsh
072 7 _aRGC
_2thema
100 1 _aZhou, Xingang.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_990267
245 1 0 _aJobs-Housing Balance and Self-Containment Using Cellphone Big Data
_h[electronic resource] :
_bCase Studies in Shenzhen and Shanghai /
_cby Xingang Zhou.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXIX, 91 p. 38 illus., 23 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aUrban Sustainability,
_x2731-6491
505 0 _aIntroduction -- Literature Review -- Research Design...
520 _aThis book addresses the analysis of self-containment of employment (SCE), which measures journey-to-work trips among the percentage of workers who work locally. High SCE encourages the use of non-motorized transport and reduces transport-related energy consumption. In this book, mobile phone location data is employed to assess journey-to-work trips and explore spatial variations in SCE at multiple geographic scales. It finds that SCE is significantly higher in the suburbs than that in the central urban areas and tends to decrease as the spatial analysis unit shifts from the macro to the micro scale. The relationship between Jobs–housing balance is found to be more important in self-containment of employment for secondary-sector workers compared with that for tertiary-sector workers. Secondary-sector workers tend to reside near their workplaces because of relatively balanced jobs and housing, whereas tertiary-sector workers tend to reside farther away from their workplaces to save housing cost. A mixed-use index (MUI) in terms of employment is examined. The interconnections between MUI and SCE are examined in both industrial and commercial areas, to gauge the effect of the industrial-residential mix or commercial-residential mix on SCE. This book will enhance readers’ understanding of the spatial variations in SCE at multiple scales. In addition, its investigation of the effect of mixed use on SCE will shed new light on the relationship between land use and journey-to-work patterns.
650 0 _aHuman geography.
_958506
650 0 _aBig data.
_957216
650 0 _aQuality of life.
_962149
650 1 4 _aHuman Geography.
_958506
650 2 4 _aBig Data.
_957216
650 2 4 _aQuality of Life Research.
_966153
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819781843
776 0 8 _iPrinted edition:
_z9789819781867
776 0 8 _iPrinted edition:
_z9789819781874
830 0 _aUrban Sustainability,
_x2731-6491
_969350
856 4 0 _uhttps://doi.org/10.1007/978-981-97-8185-0
912 _aZDB-2-SLS
912 _aZDB-2-SXS
999 _c66412
_d66412