Comparison of Map Visualization Techniques Used for Spatial and Spatio-Temporal Data: An Analytical Survey Applied to COVID-19 Data An Analytical Survey Applied to COVID-19 Data

Article Sidebar

PDF Download
Published Sep 20, 2022
DOI: https://doi.org/10.18103/mra.v10i9.3072

Downloads

Download data is not yet available.

Submit your own article

Register as an author to reserve your spot in the next issue of the Medical Research Archives.

Author Registration

Join the Society

The European Society of Medicine is more than a professional association. We are a community. Our members work in countries across the globe, yet are united by a common goal: to promote health and health equity, around the world.

Join Europe’s leading medical society and discover the many advantages of membership, including free article publication.

Membership

Main Article Content

Mohammad Shaito
phd candidate
Ramez Elmasri, Dr. David Levine, Dr.
Associate Professor of Practice

Abstract

Currently, there are numerous techniques that are either in use or proposed for use for spatial and spatio-temporal visualization of data. Visualization techniques are commonly used in various areas including errands of daily life, weather, medical care, economics, social media, politics, and science, among many others. We have previously demonstrated the application of several tools and spatial data visualization techniques to visualize and analyze COVID-19 data. In this study, we aim to investigate the frequency of encounter and the extent and type of use of six data visualization techniques, namely: Choropleth maps, Heat maps, Hexagonal binning, Dot maps, Bubble maps, and Cartogram maps, using a survey of popular techniques.

Keywords: Spatial Data, Spatio-Temporal Data, Visualization Techniques, Data Visualization and Analysis

Article Details

How to Cite
SHAITO, Mohammad; ELMASRI, Ramez; LEVINE, David. Comparison of Map Visualization Techniques Used for Spatial and Spatio-Temporal Data: An Analytical Survey Applied to COVID-19 Data. Medical Research Archives, [S.l.], v. 10, n. 9, sep. 2022. ISSN 2375-1924. Available at: <https://esmed.org/MRA/mra/article/view/3072>. Date accessed: 22 dec. 2024. doi: https://doi.org/10.18103/mra.v10i9.3072.
ABNT APA BibTeX CBE EndNote - EndNote format (Macintosh & Windows) MLA ProCite - RIS format (Macintosh & Windows) RefWorks Reference Manager - RIS format (Windows only) Turabian
Issue
Vol 10 No 9 (2022): Vol.10 Issue 9 September 2022
Section
Research Articles

The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.

 

References

1. Shaito M, Elmasri R. Map Visualization using Spatial and Spatio-Temporal Data: Application to COVID-19 Data. Paper presented at: The 14th Pervasive Technologies Related to Assistive Environments Conference, 2021; Corfu Greece.
2. Andrienko G, Andrienko N, Savinov A. Choropleth Maps: classification revisited. Paper presented at: ICC 2001, 2001; Beijing.
3. Kuhfeld WF. Heat Maps: Graphically Displaying Big Data and Small Tables. Paper presented at: SAS Institute Inc., 2017; Cary,North California.
4. Ayalasomayajula V. 7 Techniques to Visualize Geospatial Data. humans of data. October 5, 2016. Available at: https://humansofdata.atlan.com/2016/10/7-techniques-to-visualize-geospatial-data/. Accessed August 18, 2020.

5. Severino R. Bubble Map. The Data Visualisation Catalogue. 2017. Available at: https://datavizcatalogue.com/methods/bubble_map.html. Accessed June 30, 2020.

6. Nursat S, Kobourov. Visualizing cartograms: Goals and task taxonomy. ArXiv. 2015;abs/1502.07792.
7. GISGeography. Cartogram Maps: Data Visualization with Exaggeration. GISGeography. May 30, 2022. Available at: https://gisgeography.com/cartogram-maps/. Accessed June 15, 2022.

8. Tennekes M. tmap: Thematic Maps in R. Journal of Statistical Software. 2018;84(6):1-39.
9. Korycka-Skorupa J, Pasławski J. The beginnings of the choropleth presentation. Polish Cartographical Review. 2017;49(4):151–162.
10. Netek R, Pour T, Slezakova R. Implementation of Heat Maps in Geographical Information System – Exploratory Study on Traffic Accident Data. Open Geosciences. August 2018;10(1):367-384.
11. Snow J. On the Mode of Communication of Cholera. 2nd Edition ed. London; 1855.
12. Carr DB, Olsen AR, White D. Hexagon Mosaic Maps for Display of Univariate and Bivariate Geographical Data. Cartography and Geographic Information Systems. 1992;19(4):228-236.
13. Battersby S, Strebe D, Finn MP. Shapes on a plane: evaluating the impact of projection distortion on spatial binning. Cartography and Geographic Information Science. May 2016;44(5):1012.
14. Robinson AH. The 1837 Maps of Henry Drury Harness. The Geographical Journal. December 1955;121(4):440-450.
15. Field K. The Geographic Information Science & Technology Body of Knowledge: University Consortium for Geographic Information Science; 2017.