Visualizing and comparing multivariate scalar data over a geographic map.
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Date
2009-10-05
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Abstract
Recent technological advances and innovations have given us ways to
easily and quickly extract large sets of data, but the increasing
amounts of raw information only highlight the lack of good
visualization or pattern recognition techniques to interpret the data.
The objective of the research is to build techniques to effectively
visualize multivariate scalar entities over a topographical map. Our
goals are; a. rapid interpretation of the magnitude of a scalar entity
at a particular spatial location; b. rapid comparison of the
magnitudes of different scalar entities ; c. rapid comparison of the
scalar entities across different regions of the map. Based on past
research, I chose to investigate creating a texture of symmetrical
units called texels. Each texel contains a fixed number of
color-mapped hexagonal blocks representing each scalar entity. Users
can dynamically choose the static variables to be visualized and the
size of the texels. The research started as an experiment to visualize
the United States Election results to represent the degree of
variation in the results and the votes shared among the contestants.
In addition to the election data my technique has also been applied
to the United States census data, geographical and meteorological data
to highlight interesting results.
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Keywords
cartography, hexagonal grids, visualization
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Degree
MS
Discipline
Computer Science