Spatial interpolation of mobile positioning data for population statistics

Aasa, Anto; Saluveer, Erki; Kamenjuk, Pilleriine; Raun, Janika; Šimbera, Jan

doi:10.34726/lbs2019.64

Record link:

https://doi.org/10.34726/lbs2019.64
http://hdl.handle.net/20.500.12708/663

Title:

Spatial interpolation of mobile positioning data for population statistics

Citation:

Aasa, A., Saluveer, E., Kamenjuk, P., Raun, J., & Šimbera, J. (2019). Spatial interpolation of mobile positioning data for population statistics. In G. Gartner & H. Huang (Eds.), LBS 2019 : Adjunct Proceedings of the 15th International Conference on Location-Based Services. Wien. https://doi.org/10.34726/lbs2019.64

reposiTUm DOI:

10.34726/lbs2019.64

CatalogPlus:

AC15512995

Publication Type:

Inproceedings - Full-Paper Contribution

Language:

English

Authors:

Aasa, Anto
Saluveer, Erki
Kamenjuk, Pilleriine
Raun, Janika
Šimbera, Jan

Published in:

LBS 2019 : Adjunct Proceedings of the 15th International Conference on Location-Based Services

Date (published):

2019

Event name:

15th International Conference on Location-Based Services

Event date:

11-Nov-2019 - 13-Nov-2019

Event place:

Wien, Austria

Number of Pages:

Publisher:

Wien

Keywords:

Mobile positioning; Population statistics; Spatial interpolation

Abstract:

Mobile positioning data has been mentioned in many agendas as a new input for official statistics. In current paper, we compared four different spatial interpolation methods of mobile positioning data. Best results to describe the population distribution appeared with adaptive Morton grid model where the R2 was 0.95. Widely used point-in-polygon and arealweighted interpolation gave much weaker results (R2 = 0.42; R2 = 0.35).

License:

CC BY 4.0