A User Study on 2D Wind Visualization Methods
Many visualization methods exist in the field of scientific visualization, and new
methods are being created each year. However, there has been very little research on
how effective existing methods are in revealing important features of the underlying data
they represent. In fact, lack of empirical user studies has been identified as one of the
major problems within the field of scientific visualization. This thesis contributes to this
area by comparing the effectiveness of several commonly used visualization methods for
2 dimensional wind data through user testing. The term ¡°effective¡± was re-defined in the
context of visualization, and two experiments were carefully designed to target at wind
speed and direction respectively. Data gathered through these experiments was used
towards the evaluation of the visualization technique involved.
In the first experiment dealing with wind speed, the following six visualization methods
were tested: (1) Arrows, (2) Cones, (3) Streamlines, (4) Arrows w/ Color Map, (5) Cones
w/ Color Map, and (6) Streamline w/ Color Map. Users were asked to locate the
strongest wind within a visualization. Data collected was analyzed to determine the
difference between the user selected wind speed and the actual maximum wind speed in
the given picture.
The second experiment focused on wind direction, and five visualization methods were
evaluated, namely (1) Arrows, (2) Cones, (3) Streamlines, (4) Normalized Arrows, and
(5) Normalized Cones. Users were asked to identify the wind direction pattern type in
each picture, and the number of correct answers was recorded and analyzed.
Statistical analyses of the data using Analysis of Variance (ANOVA) and pairwise t-test
showed that the Cones, Arrows w/ Color map, and Cones w/ Color Map methods
outperformed the rest of the methods in experiment one, and that the Streamlines method
outperformed all other methods in experiment two. Users¡¯ subjective opinions regarding
the ease of use of each visualization methods agreed with the statistical results.
Advisor:Donald J. Morton; Rudy A. Gideon; Yolanda Jacobs Reimer
School:The University of Montana
School Location:USA - Montana
Source Type:Master's Thesis
Date of Publication:09/19/2007