Proceedings of the 2016 International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2016)

Demographic Data Visualization on Continuous Area Cartograms

Authors
Lijing Ren, Zhengxu Zhao
Corresponding Author
Lijing Ren
Available Online September 2016.
DOI
10.2991/iccia-16.2016.51How to use a DOI?
Keywords
Cartogram; Population prediction; Curve fitting.
Abstract

Cartogram is a map depicting attributes of spatial data by distorting two dimensional original maps while preserving their topology. In this paper, a novel cartogram thematic map is adopted to express population growth. The best fitting model is proposed to predict the population of randomly selected modern cities in a provincial area of P R China. The result is visualized with cartograms to produce useful findings for scheming a population planning. It is expected that this method will be an essence for the study of population prediction models.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2016)
Series
Advances in Computer Science Research
Publication Date
September 2016
ISBN
10.2991/iccia-16.2016.51
ISSN
2352-538X
DOI
10.2991/iccia-16.2016.51How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Lijing Ren
AU  - Zhengxu Zhao
PY  - 2016/09
DA  - 2016/09
TI  - Demographic Data Visualization on Continuous Area Cartograms
BT  - Proceedings of the 2016 International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2016)
PB  - Atlantis Press
SP  - 276
EP  - 279
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-16.2016.51
DO  - 10.2991/iccia-16.2016.51
ID  - Ren2016/09
ER  -