Treemap Cartography for showing Spatial and Temporal Traffic Patterns
Bibliographic Data
| ID | 16840995 |
|---|---|
| Authors | Aidan Slingsby (0000-0003-3941-553X, City, University of London, corresponding author), Jo Wood (0000-0001-9270-247X, City, University of London), Jason Dykes (0000-0002-8096-5763, City, University of London) |
| Year | 2010 |
| Volume | 6 |
| Issue | 1 |
| Pages | 135-146 |
| Publication date | 2010-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Maps (JOURNAL) |
| Journal identifiers | ISSN: 1744-5647 • E-ISSN: 1744-5647 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.4113/jom.2010.1071 |
| OpenAlex | W2154881740 |
| Language | EN |
| Citations received | 6 |
| References cited | 7 |
Please click here to download the map associated with this article. Depicting spatial and temporal aspects of traffic flows of different types is challenging. We use a treemapbased technique that is able to show multiple aspects of large quantities of spatial and temporal traffic data simultaneously. Treemaps present multivariate data as a hierarchy of rectangles that are nested within each other. Each level of the hierarchy is used to carry information about one variable, with rectangle size, arrangement and colour being potential information-carrying ‘channels’ for reflecting properties of the data. We show information about the vehicles operated by eCourier (UK) Ltd. by location, vehicle type, day of the week and hour of the day. Our two maps use colour to show the volumes and speeds of traffic at each of 82,320 combinations of location, vehicle type, day of week and hour of day, concurrently. Crucially, we use a regular grid to represent location, give all the treemap nodes a constant size and order them spatially. This cartographic representation allows multiple aspects of large traffic datasets to be viewed concurrently, such that spatial and temporal patterns can be identified
Cartography · Geography · Computer Science · Data Management and Algorithms · Data Visualization and Analytics · Remote Sensing and LiDAR Applications
| Citations per year | 0.55 |
|---|---|
| Citation span | 2015 - 2021 (7) |
| Highly cited | No |