Apoala Project

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Geographic Visualization (geovisualization)
Geovisualization involves the use of computer graphics to stimulate the human visual system to recognize patterns that would not otherwise be obvious. Geovisualization can be extremely beneficial in all stages of exploratory data analysis (EDA). Below are some examples of geographic visualization in the Apoala project.

Visualization of a time-space cube in IBM Data Explorer allows a climatologist to visually search for periodicity in high-intensity rainfall events in both time and space. In this case, daily total precipitation data over a 1 year period are displayed for the Susquehanna River Basin in Pennsylvania.

The image above is a parallel coordinate plot with certain data records highlighted using brushing. This brushing technique can be linked to other representations including maps, scatter plots (see below), and the data cubes illustrated above in order to allow a user to interactively explore subsets of the data.

This is an example of linked brushing, as described above, in a scatterplot matrix.

This 3-dimensional shaded relief representation of a portion of Pennsylvania uses color to represent maximum daily temperature. The ability to display multiple data sets at once, combined with the power to interactively change the display of such data, helps users quickly and intuitively explore their data. Visualization can help users to both confirm existing hypothesis as well as formulate new ones.

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Copyright © 1998-2000 Pennsylvania State University


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	Geographic Visualization (geovisualization) Geovisualization involves the use of computer graphics to stimulate the human visual system to recognize patterns that would not otherwise be obvious. Geovisualization can be extremely beneficial in all stages of exploratory data analysis (EDA). Below are some examples of geographic visualization in the Apoala project. Visualization of a time-space cube in IBM Data Explorer allows a climatologist to visually search for periodicity in high-intensity rainfall events in both time and space. In this case, daily total precipitation data over a 1 year period are displayed for the Susquehanna River Basin in Pennsylvania. The image above is a parallel coordinate plot with certain data records highlighted using brushing. This brushing technique can be linked to other representations including maps, scatter plots (see below), and the data cubes illustrated above in order to allow a user to interactively explore subsets of the data. This is an example of linked brushing, as described above, in a scatterplot matrix. This 3-dimensional shaded relief representation of a portion of Pennsylvania uses color to represent maximum daily temperature. The ability to display multiple data sets at once, combined with the power to interactively change the display of such data, helps users quickly and intuitively explore their data. Visualization can help users to both confirm existing hypothesis as well as formulate new ones.


.	Copyright © 1998-2000 Pennsylvania State University