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An Automated Displaced Proportional Circle Map Using Delaunay Triangulation and an Algorithm for Node Overlap Removal

Datos Bibliográficos

ID14701808
AutoresDavid Lamb (0000-0002-0598-5369, University of South Florida, autor de correspondencia)
Año2017
Volumen52
Número4
Páginas364-370
Fecha de publicación2017-12-01
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaCartographica The International Journal for Geographic Information and Geovisualization (JOURNAL)
Identificadores de la revistaISSN: 0317-7173 • E-ISSN: 1911-9925
EditorialUniversity of Toronto Press Inc. (UTPress) (PUBLISHER)
DOI10.3138/cart.52.4.2016-0007
OpenAlexW2778189778
IdiomaEN
Referencias citadas17

Proportional circle maps are a popular method for visualizing quantitative data on a map. Circles are scaled proportionally based on the data provided; larger circles represent larger quantities. The circles require two values, a location and a numeric quantity. For data that have a wide range of values, the resulting map will produce clutter and overlap in which large symbols obscure the information contained in smaller circles. Some previous solutions to this problem are modifying and improving the contrast between symbols, or using stacking algorithms so all symbols are visible. This article proposes the displaced proportional symbol map, which displaces the symbol's location based on the amount of overlap between neighbouring circles. At the same time, it preserves the location of non-overlapping symbols, which distinguishes it from the circular cartogram. The displacement is automated through the proximity stress model algorithm for node overlap removal. This algorithm was originally designed for graph layouts with overlapping nodes, but was modified here for circular symbols and map layout. The result is a map with improved clarity and the ability to add labelling to a cluttered proportional circle map

Algorithm · Clutter · Computer vision · Delaunay triangulation · Geometry · Graph · Node (physics · Range (aeronautics · Symbol (formal · Triangulation · Computer Science · Data Management and Algorithms · Data Visualization and Analytics · Geographic Information Systems Studies · Mathematics · Artificial Intelligence · Theoretical Computer Science

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Altamente citadoNo
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