Quantitative Measures for Cartogram Generation Techniques

dc.contributor.authorAlam, Md. Jawaherulen_US
dc.contributor.authorKobourov, Stephen G.en_US
dc.contributor.authorVeeramoni, Sankaren_US
dc.contributor.editorH. Carr, K.-L. Ma, and G. Santuccien_US
dc.date.accessioned2015-05-22T12:51:51Z
dc.date.available2015-05-22T12:51:51Z
dc.date.issued2015en_US
dc.description.abstractCartograms are used to visualize geographically distributed data by scaling the regions of a map (e.g., US states) such that their areas are proportional to some data associated with them (e.g., population). Thus the cartogram computation problem can be considered as a map deformation problem where the input is a planar polygonal map M and an assignment of some positive weight for each region. The goal is to create a deformed map M0, where the area of each region realizes the weight assigned to it (no cartographic error) while the overall map remains readable and recognizable (e.g., the topology, relative positions and shapes of the regions remain as close to those before the deformation as possible). Although several such measures of cartogram quality are well-known, different cartogram generation methods optimize different features and there is no standard set of quantitative metrics. In this paper we define such a set of seven quantitative measures, designed to evaluate how faithfully a cartogram represents the desired weights and to estimate the readability of the final representation. We then study several cartogram-generation algorithms and compare them in terms of these quantitative measures.en_US
dc.description.number3en_US
dc.description.sectionheadersGeospatial Visualizationen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume34en_US
dc.identifier.doi10.1111/cgf.12647en_US
dc.identifier.pages351-360en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12647en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.titleQuantitative Measures for Cartogram Generation Techniquesen_US
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