3D space–time visualization of individual settlement pathways of Mainland China-born migrants in Queensland, Australia

By: Contributor(s): Material type: ArticleArticlePublication details: Sage, 2019.Description: Vol 51, Issue 2, 2019,(275-278 p.)Subject(s): Online resources: In: Environmental and planning A: Economy and spaceSummary: The number of migrants from Mainland China (MC) to Australia have been sharply increasing since 2000 and MC became the largest non-Commonwealth source country in 2011. The integration process of migrants to the host society involves the exposure and movement of migrants to the majority, which is reflected by the settlement pathways of migrants moving from ethnic to non-ethnic communities over time. Most of the existing research regarding migrants’ pathways is constrained by the limitations of cross-sectional data, which are usually available at the community or above levels. Little is known about the individual-level settlement pathways of migrants due to lack of data availability. In order to address this deficit, a 3D visualization is used to express the individual pathways of MC-born migrants based on primary survey data. This enables a more detailed, spatio-temporal picture of how long migrants live at each address and how they move across neighbourhoods.
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Item type Current library Collection Call number Vol info Status Date due Barcode Item holds
E-Journal E-Journal Library, SPAB Reference Collection Vol. 51, Issue 1-8, 2019 Available
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The number of migrants from Mainland China (MC) to Australia have been sharply increasing since 2000 and MC became the largest non-Commonwealth source country in 2011. The integration process of migrants to the host society involves the exposure and movement of migrants to the majority, which is reflected by the settlement pathways of migrants moving from ethnic to non-ethnic communities over time. Most of the existing research regarding migrants’ pathways is constrained by the limitations of cross-sectional data, which are usually available at the community or above levels. Little is known about the individual-level settlement pathways of migrants due to lack of data availability. In order to address this deficit, a 3D visualization is used to express the individual pathways of MC-born migrants based on primary survey data. This enables a more detailed, spatio-temporal picture of how long migrants live at each address and how they move across neighbourhoods.

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