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David J. Lieske, Ph.D.|
David J. Lieske is an Associate Professor in the Department of Geography
and Environment, and is the Director of the Mount Allison University
Geospatial Modelling Lab (GML).
His research expertise encompasses spatial
statistical modelling, geographic information systems (GIS), and geovisualization.
David is particularly interested in the application of these methods to assist
environmental monitoring, mapping and conservation planning.
David is also the author of the Tantramar Community
Adaptation Viewer (TCAV), a web-based decision support toolkit for viewing
community flood risk vulnerability.
Link to David's Workshop on the R Statistical Package:
His contact information is as follows:
David J. Lieske
Dept. of Geography
144 Main Street,
How Can I Pursue an Honours Thesis in the GML?
An Honours Thesis is an excellent opportunity to explore a research topic in depth, to
make a contribution to human knowledge, and to really hone
your verbal and written communication skills.
Completing an honour's thesis prepares you for anything, whether it be graduate school;
designing a research study, gathering information, and conducting an analysis;
or speaking on a stage or in a boardroom. It will make you a
better thinker, and a better communicator.
An Honours thesis is a significant commitment, however - both for you, the student,
as well as your faculty supervisor. To pursue an Honours project in the GML you
need to be able to fulfill the following criteria:
- A term/session (e.g., year #3) GPA of 3.2 or higher.
- Interest in and good performance (B+) in the department's GIS course
- Interest in completing a project with a significant spatial focus,
including, but not limited to:
- Species distribution modelling, i.e., modelling the relationships
between the geographical occurrence of a species, and the key environmental factors
to which it responds (e.g., habitat, climate).
- Land cover classification, land cover analysis.
- Spatial statistics, e.g., hotspot analysis, spatial predictive modelling
- Development of special visualizations for exploring relationships in time
- Assessing how people perceive and interpret spatial information.
- Geocomputing, e.g., web mapping or custom development of a geoprocessing
- Risk mapping, e.g., pollution risk.