Spatio-Qualitative Data Visualization: SoftGIS and Weighted Average Visualization

Kamyar Hasanzadeh^1,

¹Department of Planning and Geoinformatics, Aalto University, Espoo, Finland

Cite this paper

Kamyar Hasanzadeh. Spatio-Qualitative Data Visualization: SoftGIS and Weighted Average Visualization. Journal of Geosciences and Geomatics. 2014; 2(1):38-41. doi: 10.12691/JGG-2-1-6

Abstract

In recent years there has been considerable breakthrough in acquisition of georeferenced qualitative data. These types of data have characteristics that distinguish them from quantitative datasets and therefore it is typically more challenging to discover knowledge from such spatio-qualitative data. SoftGIS is one of the most prominent attempts in in collecting such spatio-qualitative data that is capable of providing informative data with applications in different disciplines. This paper uses this dataset in a case of urban experience in Helsinki in order to propound a visual technique that can help with knowledge discovery process. The visualization method proposed in this study, namely weighted average visualization (WAV), is tailored to meet specific characteristics of the aforesaid dataset and is capable of discovering patterns that are not visible through current approaches.

Keywords

SoftGIS, visualization, spatio-qualitative data analysis, weighted average visualization

Copyright

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References

[1]	Guttman, L. 1944. A basis for scaling qualitative data. American sociological review, pp. 139-150.
[2]	Kahila, M. 2008. Possibilities of Web-based softGIS Method in Revealing Residents Evaluation Knowledge of the Living Environment. In FUTURE-Future Urban Research in Europe, The Electronic City Conference, Bratislava.
[3]	Kahila, M. and Kyttä, M. 2011. Web-based SoftGIS method in research and urban planning practices. The Electronic City, 1 p. 199.
[4]	Kahila, M. n.p. Possibilities of Webbased softGIS Method in Revealing Residents Evaluation Knowledge of the Living Environment. [report].
[5]	Kahila, M., & Kyttä, M. 2006. The Use of Web-based SoftGIS-method in the Urban Planning Practices. In Proceedings of the Conference on Urban Conditions and Life Changes.
[6]	Kahila, M., & Kyttä, M. 2009. SoftGIS as a bridge-builder in collaborative urban planning. In Planning support systems best practice and new methods, Springer Netherlands, pp. 389-411.
[7]	Keim, D. A. 2001. Visual exploration of large data sets. Communications of the ACM, 44 (8), pp. 38-44.
[8]	Kyttä, M., Broberg, A., Tzoulas, T., & Snabb, K. 2013. Towards contextually sensitive urban densification: Location-based SoftGIS knowledge revealing perceived residential environmental quality. Landscape and Urban Planning, 113, pp. 30-46.
[9]	Nikander, J. 2012. Interaction and visualization methods in teaching spatial algorithms and analyzing spatial data. Ph.D. Aalto University.
[10]	Shneiderman, B. and Plaisant, C. 2004. Designing the user interface. Boston: Pearson/Addison Wesley.
[11]	Slocum, T. A., 2005. Thematic cartography and geographic visualization. Upper Saddle River, NJ: Pearson/Prentice Hall.
[12]	Verd, J. M. and Porcel, S. 2012. An Application of Qualitative Geographic Information Systems (GIS) in the Field of Urban Sociology Using ATLAS. ti: Uses and Reflections. 13 (2).
[13]	Hasanzadeh, K. 2014. SoftGIS Data Mining and Analysis: A Case Study of Urban Impression in Helsinki. Master's. Aalto University.
[14]	Kwan, M. P., & Ding, G. 2008. Geo-Narrative: Extending Geographic Information Systems for Narrative Analysis in Qualitative and Mixed-Method Research∗. The Professional Geographer, 60 (4), 443-465.