Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2, 93-97, 2014
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-2/93/2014/
doi:10.5194/isprsarchives-XL-2-93-2014
© Author(s) 2014. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
11 Nov 2014
Geovisualization of Local and Regional Migration Using Web-mined Demographics
R. T. Schuermann and T. E. Chow Texas Center for Geographic Information Science, Department of Geography, USA
Keywords: Geography, Data Mining, Visualization, Animation, Spatial, Temporal Abstract. The intent of this research was to augment and facilitate analyses, which gauges the feasibility of web-mined demographics to study spatio-temporal dynamics of migration. As a case study, we explored the spatio-temporal dynamics of Vietnamese Americans (VA) in Texas through geovisualization of mined demographic microdata from the World Wide Web. Based on string matching across all demographic attributes, including full name, address, date of birth, age and phone number, multiple records of the same entity (i.e. person) over time were resolved and reconciled into a database. Migration trajectories were geovisualized through animated sprites by connecting the different addresses associated with the same person and segmenting the trajectory into small fragments. Intra-metropolitan migration patterns appeared at the local scale within many metropolitan areas. At the scale of metropolitan area, varying degrees of immigration and emigration manifest different types of migration clusters. This paper presents a methodology incorporating GIS methods and cartographic design to produce geovisualization animation, enabling the cognitive identification of migration patterns at multiple scales. Identification of spatio-temporal patterns often stimulates further research to better understand the phenomenon and enhance subsequent modeling.
Conference paper (PDF, 1057 KB)


Citation: Schuermann, R. T. and Chow, T. E.: Geovisualization of Local and Regional Migration Using Web-mined Demographics, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2, 93-97, doi:10.5194/isprsarchives-XL-2-93-2014, 2014.

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