TY - GEN
T1 - Visual abstraction improvement of interactive dot map
AU - Zhang, Di
AU - Zhu, Ligu
AU - Xiao, Zida
AU - Zhang, Lei
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/18
Y1 - 2016/7/18
N2 - The distribution of multiclass discrete data in geographic space is a research hotspot in the field of geographic-related visualization. As a basic visual presentation of such data, the advantages of dot maps are perceptual intuition and abundant details, but there is also the problem of poor readability due to the points overlap. The approach of density estimation by resolution is proposed in this paper to optimize dot maps, and to flexibly adjust sampling parameters of the current resolution, so as to show the details to the maximum extent and maintain the relative density characteristics of various types of property. In order to compensate the missing discrete features caused by sampling, a series of interactive tools are used to effectively improve the accuracy of visual analysis and assist the overall visual representation. Finally, the effectiveness of this approach is proved through case analysis and user research.
AB - The distribution of multiclass discrete data in geographic space is a research hotspot in the field of geographic-related visualization. As a basic visual presentation of such data, the advantages of dot maps are perceptual intuition and abundant details, but there is also the problem of poor readability due to the points overlap. The approach of density estimation by resolution is proposed in this paper to optimize dot maps, and to flexibly adjust sampling parameters of the current resolution, so as to show the details to the maximum extent and maintain the relative density characteristics of various types of property. In order to compensate the missing discrete features caused by sampling, a series of interactive tools are used to effectively improve the accuracy of visual analysis and assist the overall visual representation. Finally, the effectiveness of this approach is proved through case analysis and user research.
KW - density estimation
KW - dot maps
KW - enhance visual effectiveness
KW - geographic information
KW - interactive data analysis
UR - http://www.scopus.com/inward/record.url?scp=84983335318&partnerID=8YFLogxK
U2 - 10.1109/SNPD.2016.7515942
DO - 10.1109/SNPD.2016.7515942
M3 - Conference Proceeding
AN - SCOPUS:84983335318
T3 - 2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016
SP - 469
EP - 474
BT - 2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016
A2 - Chen, Yihai
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016
Y2 - 30 May 2016 through 1 June 2016
ER -