Exploring actionable visualizations for environmental data : air quality assessment of two Belgian locations
Abstract: Organizations collect an ever-increasing amount of data concerning environmental parameters. Non-experts may be confronted with an information overload, making the data meaningless. A way to circumvent this problem is visualizing the trends in the pollution concentrations measured over time. However, non-experts do not have a mental model to derive air quality information from displayed concentration profiles. Therefore, a large fraction of the stakeholders remains unable to read/interpret such data effectively. To improve communication with stakeholders, we superposed health risk in... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2021 |
Schlagwörter: | Chemistry / Biology / Engineering sciences. Technology / Computer. Automation |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-28877326 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://hdl.handle.net/10067/1831910151162165141 |
Abstract: Organizations collect an ever-increasing amount of data concerning environmental parameters. Non-experts may be confronted with an information overload, making the data meaningless. A way to circumvent this problem is visualizing the trends in the pollution concentrations measured over time. However, non-experts do not have a mental model to derive air quality information from displayed concentration profiles. Therefore, a large fraction of the stakeholders remains unable to read/interpret such data effectively. To improve communication with stakeholders, we superposed health risk information from 9 different Air Quality Indices (AQIs) on different kinds of graphs. The visualization methods are applied on data collected by the Belgian Environment Agency from two monitoring stations located in contrasting regions, Ghent and Vielsalm. Supplementary, spatially distributed pollution is shown using data collected from Sentinel-5p satellite. Despite some limitations of the AQIs, the applied visualizations methods successfully translate the data obtained into actionable information.