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Visual Analytic Design for Detecting Airborne Pollution Sources

Wood, J. ORCID: 0000-0001-9270-247X (2017). Visual Analytic Design for Detecting Airborne Pollution Sources. Paper presented at the IEEE VIS, VAST Workshop, 1-6 Oct 2017, Phoenix, USA.

Abstract

Using the VAST Challenge 2017 dataset as an illustration, the design choices of a visual analytic system for predicting the source of air pollution is described. Probabilistic Source Cones are visual symbols representing the probability of source location of a pollution event. Using transparency to indicate probability, multiple cones may be overlaid in order to provide a fuzzy triangulation of likely sources. This enabled the correct prediction and elimination of pollution sources at a precision far in excess of the spatial density of the sensors themselves.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Departments: School of Mathematics, Computer Science & Engineering > Computer Science > giCentre
URI: http://openaccess.city.ac.uk/id/eprint/18289
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