Issues of Change Detection in Animated Choropleth Maps
Bibliographic Data
| ID | 14701075 |
|---|---|
| Authors | Kirk Goldsberry (Michigan State University, corresponding author), Sarah E Battersby (0000-0003-2716-4382, University of South Carolina), Sarah Battersby (University of South Carolina) |
| Year | 2009 |
| Volume | 44 |
| Issue | 3 |
| Pages | 201-215 |
| Publication date | 2009-09-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Cartographica The International Journal for Geographic Information and Geovisualization (JOURNAL) |
| Journal identifiers | ISSN: 0317-7173 • E-ISSN: 1911-9925 |
| Publisher | University of Toronto Press Inc. (UTPress) (PUBLISHER) |
| DOI | 10.3138/carto.44.3.201 |
| OpenAlex | W2047148641 |
| Language | EN |
| Citations received | 11 |
| References cited | 28 |
One primary utility of animated maps is their ability to depict change over time and space; unfortunately, recent research suggests that humans frequently fail to perceive changes within dynamic graphics. However, different types of dynamic graphics include different manifestations of change. For example, an animated proportional-symbol map possesses different change properties than an animated choropleth map. This article examines issues of change on animated choropleth maps. We identify relevant limitations of the human visual system that pertain to animated map reading, including change blindness and foveal versus peripheral attention, and introduce methods to quantify the magnitude of change that separates individual scenes within choropleth animations. These methods are useful for measuring and describing changes that confront users of animated choropleth maps. We also characterize the transitional behaviours of enumeration units and discuss the influences of data classification and other cartographic controls on change within animated choropleth maps
Animation · Cartography · Change detection · Computer graphics (images · Foveal · Geography · Graphics · Computer Science · Data Visualization and Analytics · Spatial Cognition and Navigation · Visual and Cognitive Learning Processes · Artificial Intelligence
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| Unique citing works | 11 |
|---|---|
| Citations per year | 0,73 |
| Citation span | 2011 - 2025 (15) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 11 |