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,
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
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).
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,
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
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:
- 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
- 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
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
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.
Gousie, M.B. and Grady, J. Targeting Social Stratification, presented at
the International Visual Sociology Association (IVSA) Annual Conference,
San Francisco, August 12, 2004.
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!
Scene from Lord of the Rings by Pat Sagui '04
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.
Stuetzle, C. Computer Modeling and Visualization of Luminescent Crystals:
The Role of Energy Transfer and Upconversion. Honors Thesis,
Wheaton College, 2007.
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),
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.
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.
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,
Gousie, M.B. Focus + Context for Visualizing Uncertainty in DEMs.
Poster presented at the IEEE Information Visualization Conference, 2011.
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.
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),
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.
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.
Surface Reconstruction Algorithms
In this research, we begin with digitized contour maps, like the one shown below
depicting Mt. Washington, NH:
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,
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.
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.
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.
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).
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.
Gousie, M. B. Contours to Digital Elevation Models: Grid-Based
Surface Reconstruction Methods. PhD thesis, Rensselaer Polytechnic
Institute, 1998. (thesis)