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Temporal Sampling Implications for Crowd Sourced Population Estimations from Social Media
Samuel Lee Toepke
Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds
Understanding the movements of a population throughout the 24-hour day is critical when directing disaster response in an urban area. An emergency situation can develop rapidly, and understanding the expected locations of groups of people is required for the success of first responders. Recent advances in modern consumer technologies have facilitated the generation, sharing and mining of an extensive amount of volunteered geographic information. Users leverage inexpensive smart devices, pervasive Internet connections and social media services to provide data about geospatial locations. Using an enterprise system, it is possible to aggregate this freely available, geospatially enabled data and create a population estimation with high spatiotemporal resolution, via a heat map. This investigation explores the effects of different temporal sampling periods when creating such estimations. Time periods are selected, estimations are generated for several large urban areas in the western United States, and comparisons of the results are shown/discussed.
openurl:?ctx_ver=Z39.88-2004&rfr_id=info%3Asid%2Fidl.iscram.org%2F&genre=proceeding&title=Temporal%20Sampling%20Implications%20for%20Crowd%20Sourced%20Population%20Estimations%20from%20Social%20Media&stitle=Iscram%202017&issn=2411-3387&date=2017&spage=564&epage=571&aulast=Samuel%20Lee%20Toepke&pub=Iscram&place=Albi%2C%20France&sid=refbase%3AISCRAM
url:http://idl.iscram.org/show.php?record=2044
citekey:SamuelLeeToepke2017
citation:Samuel Lee Toepke. (2017). Temporal Sampling Implications for Crowd Sourced Population Estimations from Social Media. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 564-571). Albi, France: Iscram.
2017
ConferencePaper
text
Population estimation
emergency response
temporal sampling
volunteered geospatial information
data mining
file:http://idl.iscram.org/files/samuelleetoepke/2017/2044_SamuelLeeToepke2017.pdf
Iscram
English
2411-3387
Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management
2017
564
571
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