Michael B. Gousie, Professor of Computer Science Germany World Cup Champs 2014

Research

My research includes areas in Computational Geometry, Geographic Information Systems (GIS), Computer Graphics, and Visualization. The main areas currently under investigation are:
  • DEM Error Visualization - many digital elevation models (DEMs) are constructed from less-than-perfect data, and along with the computations necessary to create the final surface, errors are inevitable. This research seeks to determine the severity of the error.
  • Surface Reconstruction - creating a 3D (actually 2.5D) surface from 2D sources, such as contour lines (isolines) or other sparse data arranged on a grid. The data is interpolated or otherwise used to create a digital elevation model (DEM). A DEM is useful for visualization and analysis of a particular region. Some of this work has been done in conjunction with Wm. Randolph Franklin (Electrical, Engineering, and Systems Engineering Department, Rensselaer Polytechnic Institute)
  • Interdisciplinary Research - I am in collaboration in other areas with researchers such as Mike Smith (School of Earth Sciences and Geography, Kingston University, London), John Grady (Department of Sociology, Wheaton College), and Michael Drout (Department of English, Wheaton College).
    Go to information visualization work: Top Ten Actors, Social Stratification.
  • Student Research/Projects - students are involved with a variety of research or other interesting projects, often in the summer.

Information Visualization: Top Ten Actors Over Time

This research is being done in collaboration with John Grady of Wheaton College's Department of Sociology; much of the implementation of the visualization was done by Melissa Branagan '14. Movie stars represent a persona - a model social type - that captures the public's imagination and embodies their desires and dreams for a short period of time and, in some cases, much longer. It seems that this symbolic space is limited to only a few stars that the viewing public can adore at any one given time. In this visualization project, we hope to find these ''alpha stars" and their interconnections. We also hope to find patterns concerning race/ethnicity, gender, and so forth. We are working to make this web-based tool more general so as to work with other top ten data sets, such as baseball batting averages, to name just one example.
Click on the image to run a prototype visualization (v0.2).


Relevant Publications/Presentations

  • Gousie, M.B., Grady, J., and Branagan, M. Visualizing Trends and Clusters in Ranked Time-Series Data. In Visualization and Data Analysis 2014 (San Francisco, 2014), P. C. Wong, D.L. Kao, M.C. Hao, and C. Chen, Eds., vol. 9017, IS&T/SPIE, pp. 90710f-1 -- 90710f-12.
  • Grady, J., Gousie, M., and Branagan, M. Visualizing the Hollywood Pantheon, presented at the International Visual Sociology Association (IVSA) Annual Conference, University of London, July, 2013.

Information Visualization: Social Stratification

This research was also done in collaboration with John Grady of Wheaton College's Department of Sociology. The idea is to use metaphors to create easy-to-use visualizations in order to see patterns in socio-economic data gathered from the US Census. The Java applets allow the user to compare different social classes, ethnic background, job type, and income in a dynamic way. With the help of students, we have created web-based prototypes using three different metaphors:
  1. The Target
    This is the original metaphor, where the center of a dart board represents the highest income level and the rings representing progressively lower levels. Each "hit" represents 160,000 individuals at that income level.
    Click to run Target 1.0

    Students Sarah Milewski '07 and Chris Stuetzle '07 implemented a newer applet of The Target which addressed some of the shortcomings of the original version.
    Click to run Target 2.0

  2. The Mountain Climber
    In this metaphor, the goal is to climb to the peak of a mountain, where the highest income levels exist. The different "mountains" can be moved or stacked to more easily compare desired parameters. This is a nice improvement over The Target.

    This applet was implemented by Sarah Milewski '07 and Chris Stuetzle '07.
    Click to run MountainClimber

  3. CensusSquared
    Students Ben Burrage, Robby Grossman, Dave Machado, all from the Class of 2007, implemented this metaphor, wherein equal-size boxes are stacked on top and next to one another so as to allow easy comparisons. The higher the income, the more a box is filled. Although this is perhaps a less-strong metaphor, the regularity of each box makes it much easier to move about and stack to produce data patterns. This implementation also has no inherent clustering effect that both The Target and Mountain Climber have, as the area gets smaller as the income level rises in both of the latter implementations.
    Click to run CensusSquared
Relevant Publications/Presentations
  • Gousie, M.B., Grady, J., Burrage, B., Grossman, R., Machado, D., Milewski, S., and Stuetzle, C. Using Metaphors in Dynamic Social Stratification Visualizations. In IV08: 12th International Conference on Information Visualization (London, 2008), IEEE, pp. 485-490. (paper)
  • Gousie, M.B. and Grady, J. Targeting Social Stratification, presented at the International Visual Sociology Association (IVSA) Annual Conference, San Francisco, August 12, 2004. (talk)

Student Research/Projects

There are many research or independent study projects available in the topics listed above but also in computer graphics and information visualization in general. Please see me to discuss your interests. You may be surprised at the opportunities available to you!
Image of student project
Scene from Lord of the Rings by Pat Sagui '04


Student Publications/Presentations
  • Upshur, R. Viewing Three-Dimensional Terrain with Focus in Context. Poster presented at the Fifteenth Annual Consortium for Computing Sciences in Colleges Northeast Conference, April 2010. (poster)
  • Stuetzle, C. Computer Modeling and Visualization of Luminescent Crystals: The Role of Energy Transfer and Upconversion. Honors Thesis, Wheaton College, 2007. (thesis)
  • Bowe, S. Error Detection and Visualization in Digital Elevation Models. In Journal of Computing Sciences in Colleges, Proceedings of the Tenth Annual CCSC Northeast Conference (2005), pp. 103-104.
  • Williams, G. An Autoscheduling Optimizer for Perl. Honors Thesis, Wheaton College, 2003.
  • Williams, G., Doolittle, N., and Agnitti, T. A Surface Reconstruction Research Environment. In Journal of Computing in Small Colleges, Proceedings of the Seventh Annual CCSC Northeast Conference (2002), pp. 301-302.

DEM and Error Visualization

Traditional geographic information systems (GIS) have many capabilities to compute DEM error and/or uncertainty, but they require the user to go through many complex steps. Often the result is simply a number or a 2D visualization. This research seeks to make the process much easier and faster, as well as produce a better error visualization.

View of a DEM The current system, DEMView (formerly DEMEV), is shown at right, displaying a DEM of Franconia, NH. The system includes visualizations for relief, raster height colors, slope, height classes, curvature error, local elevation difference error, and local curvature difference error. A vertical profile cutter allows the user to view a desired profile of two surfaces simultaneously within the context of the 3D surface visualization.

Relevant Publications/Presentations

  • Gousie, M.B. The Case for 3D Visualization in DEM Assessment. In Advances in Spatial Data Handling: Geospatial Dynamics, Geosimulation and Exploratory Visualization, S. Timpf and P. Laube, Eds., Advances in Geographic Information Science, Springer, 2013, pp. 27-43.
  • Gousie, M.B. Focus + Context for Visualizing Uncertainty in DEMs. Poster presented at the IEEE Information Visualization Conference, 2011. (poster)
  • Gousie, M.B., and Smith, M.J. DEMView: 3D Visualization of DEM Error. In Accuracy 2010, Proceedings of the Ninth International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences (Leicester, UK, July 2010), N.J. Tate and P.F. Fisher, Eds., ISARA, pp. 165-168. (slides, paper)
  • Gousie, M. B. and Milewski, S. A System for 3D Error Visualization and Assessment of Digital Elevation Models. In Proceedings of the 2007 IEEE International Geoscience and Remote Sensing Symposium (IGARSS '07) (Barcelona, 2007), pp. 4064-4067. (paper)
    Note: Author Milewski is a member of the Wheaton class of '07.
  • Gousie, M. B. Digital Elevation Model Error Detection and Visualization. In The 4th Workshop on Dynamic & Multi-dimensional GIS (Pontypridd, Wales, UK, 2005), C. Gold, Ed., ISPRS, pp. 42-46. (paper)
  • Gousie, M. B., Williams, G., Agnitti, T., and Doolittle, N. CompSurf: An Environment for Exploring Surface Reconstruction Methods on a Grid. Computers & Geosciences 29, 9 (2003), 1165-1173. (paper)

Surface Reconstruction Algorithms

In this research, we begin with digitized contour maps, like the one shown below depicting Mt. Washington, NH: Image of a contour map From this sparse data set, a full DEM is computed by interpolation and/or approximation methods while preserving the accuracy of the surface defined by the data. An example of a DEM derived by our Intermediate Contour Method is shown below (red=high elevation, blue=low): Image of a contour map with intermediate contours Surface Reconstruction Animation

Another method for creating a DEM is by simulating a thin plate being draped over the sparse data points to create a surface. It takes many iterations of the thin plate method to completely fill in a regular grid of elevation points. This animation shows how a sample contour map is filled in with a thin plate approximation after intermediate contours are computed.


Relevant Publications/Presentations
  • Smith, M.J., Rose, J., and Gousie, M.B. The Cookie Cutter: A Method for Obtaining a Quantitative 3D Description of Glacial Bedforms. Geomorphology 108 (July 2009), 209-218.
  • Smith, M.J., Rose, J., and Gousie, M.B. A Method of Quantifying Subglacial Sediment Transport/Deformation. Poster presented at Geomorphology & Earth System Science, BGRG International Conference, Loughborough, UK, June 2006. (poster)
  • Gousie, M. B. and Franklin, W. R. Augmenting Grid-Based Contours to Improve Thin Plate DEM Generation. Photogrammetric Engineering & Remote Sensing 71, 1 (2005), pp. 69-79. (paper)
  • Gousie, M. B. and Franklin, W. R. Constructing a DEM from Grid-based Data by Computing Intermediate Contours. In GIS 2003: Proceedings of the Eleventh ACM International Symposium on Advances in Geographic Information Systems (New Orleans, 2003), E. Hoel and P. Rigaux, Eds., pp. 71-77. (paper)
  • Franklin, R and Gousie, M. Terrain Elevation Data Structure Operations. In 19th International Cartographic Conference & 11th General Assembly of the International Cartographic Association (ICA) (Ottawa, 1999). (paper)
  • Gousie, M and Franklin, R. Converting Elevation Contours to a Grid. In Proceedings, Eighth International Symposium on Spatial Data Handling (1998), T. Poiker and N. Chrisman, Eds., pp. 647-656. (paper)
  • Gousie, M. B. Contours to Digital Elevation Models: Grid-Based Surface Reconstruction Methods. PhD thesis, Rensselaer Polytechnic Institute, 1998. (thesis)

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