1. Visual Analytics for Spatial Clusters of Air-Quality Data.
- Author
-
Zhou, Zhiguang, Ye, Zhifei, Liu, Yanan, Liu, Fang, Tao, Yubo, and Su, Weihua
- Subjects
AIR quality ,AIR pollution ,VISUAL analytics ,CLUSTER analysis (Statistics) ,VORONOI polygons - Abstract
With the rapid development of industrial society, air pollution has become a major issue in the modern world. The development and widespread deployment of sensors has enabled the collection of air-quality datasets with detailed spatial and temporal scales. Analyses of these spatiotemporal air-quality datasets can help decision makers explore the major causes of air pollution and find efficient solutions. The authors designed a visual analytics system that uses multidimensional scaling (MDS) to transform the air-quality data from monitor stations into 2D plots and uses hierarchical clustering, Voronoi diagrams, and storyline visualizations to help experts explore various attributes and time scales in the data. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF