Air pollution is the second biggest environmental concern for Europeans after climate change and the major risk to public health. It is imperative to monitor the spatio-temporal patterns of urban air pollution. The TRAFAIR air quality dashboard is an effective web application to empower decision-makers to be aware of the urban air quality conditions, define new policies, and keep monitoring their effects. The architecture copes with the multidimensionality of data and the real-time visualization challenge of big data streams coming from a network of low-cost sensors. Moreover, it handles the visualization and management of predictive air quality maps series that is produced by an air pollution dispersion model. Air quality data are not only visualized at a limited set of locations at different times but in the continuous space-time domain, thanks to interpolated maps that estimate the pollution at un-sampled locations.
Visual analytics for spatio-temporal air quality data / Bachechi, Chiara; Desimoni, Federico; Po, Laura. - (2020). (Intervento presentato al convegno 24 International Conference Information Visualisation (IV2020) tenutosi a Victoria University, Australia & Technische Universität Wien, Austria nel 7-11 September 2020).
Visual analytics for spatio-temporal air quality data
Chiara Bachechi
;Federico Desimoni
;Laura Po
2020
Abstract
Air pollution is the second biggest environmental concern for Europeans after climate change and the major risk to public health. It is imperative to monitor the spatio-temporal patterns of urban air pollution. The TRAFAIR air quality dashboard is an effective web application to empower decision-makers to be aware of the urban air quality conditions, define new policies, and keep monitoring their effects. The architecture copes with the multidimensionality of data and the real-time visualization challenge of big data streams coming from a network of low-cost sensors. Moreover, it handles the visualization and management of predictive air quality maps series that is produced by an air pollution dispersion model. Air quality data are not only visualized at a limited set of locations at different times but in the continuous space-time domain, thanks to interpolated maps that estimate the pollution at un-sampled locations.File | Dimensione | Formato | |
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Dashboard_IV2020.pdf
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