Abstract
Some phenomena, such as crimes in a city, fires occurred in a country and road accidents can be interpreted as sets of spatio-temporal events. A spatio-temporal event is described by a geographic location, a time instant and other characterising attributes.The cartographic visualisation of spatio-temporal events remains unresolved, due to the challenges related with portraying multiple dimensions simultaneously: the spatial, the temporal and the semantic (zero or more dimensions) phenomenon's components. In this context, this article presents the Attenuation and Accumulation Maps (AA-Maps). The main idea of this visualisation analytic approach consists in showing in a map, the resulting effect of combining attenuation and accumulation, from a temporal reference of observation, given a spatio-temporal Level of Detail (LoD). Imagine the footprints of people crossing a garden in various directions. They leave different traces that summarize the cumulative effect of the footprints on the grass, which is attenuated as time goes by.AA-Maps support different combinations of attenuation and accumulation functions. In addition, this method also enables analysis with different Levels of Detail (LoD), both spatial and temporal. This allows distinct analytic perspectives of the phenomenon while promoting the search for the most suitable parametrization for its characteristics.
Original language | English |
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Title of host publication | Proceedings - 2017 21st International Conference Information Visualisation, iV 2017 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 292-295 |
Number of pages | 4 |
ISBN (Electronic) | 9781538608319 |
DOIs | |
Publication status | Published - 2017 |
Event | 21st International Conference Information Visualisation, iV 2017 - London, United Kingdom Duration: 11 Jul 2017 → 14 Jul 2017 |
Conference
Conference | 21st International Conference Information Visualisation, iV 2017 |
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Country/Territory | United Kingdom |
City | London |
Period | 11/07/17 → 14/07/17 |
Keywords
- Cartographic representation
- Geovisual analytics
- Spatio-temporal events