Department of Geography, Michigan State University

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Remote Sensing and GIS at MSU

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COURSES |  FACILITIES |  PUBLICATIONS

GIS research and teaching at MSU focus on both theory and application of GIS technology to the spatial analysis of a variety of phenomena.  Also, work in GIS is closely linked with research emphases in Cartography and Remote Sensing.  The use of GIS requires the digital representation of geographic phenomena and a much more explicit understanding of the basic issues of scale, data quality, and semantic classification than traditional mapping and map analysis methods.  To address these basic issues, faculty have pursued research on the sensitivity of digital representations to scale, the use of fuzzy sets to respresent classed variables that exhibit non-discrete boundaries, and the identification of systematic error within digital elevation data.

fuzzy vegetation

MSU faculty and graduate students have undertaken research and application projects using GIS in a variety of different settings, including: automated mapping of landforms and vegetation types, investigation of archaeological site potential, management of county health department data and facilities, investigation of potential surface and ground water quality problems in the vicinity of the Kellogg Biological Station, database development in support of regional land use/cover change analyses, and digital terrain analysis for geomorphological and hydrological investigation.

dune DEM

empty  RESEARCH AND TEACHING FACILITIES

The GIS teaching and research program is supported by the Department's computing facilities.  The facilities include two primary teaching labs: a PC-based lab with 15 workstations and a Sun-Ultra Unix lab with 10 workstations.  Additional PC and Unix workstations are dedicated to student and faculty research projects.  The University has a campus site license for ESRI (makers of Arc/Info) products.  Other supported software includes PCI Easi/Pace and Erdas Imagine for image processing.

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empty  GIS COURSES

A typical program for a graduate student in GIS might include the following courses:

GEO886: Research Design in Geography (required),

GEO865: Advanced Quantitative Methods in Geography,

GEO826: Seminar in Cartography/Geoprocessing,

and one or more of the following electives:

GEO425: Geographic Information Systems
(normally a part of a specialization in GIS unless an equivalent course was taken elsewhere)

GEO423: Map Production and Design

GEO823: Map Automation

GEO825: Geoprocessing

GEO424: Advanced Remote Sensing

It is generally recommended that students interested in concentrating on GIS consider a secondary concentration in another geographic sub-field.  For example, GIS students might take supporting courses in Physical Geography, Regional Development, or Economic/Urban Geography. Students should also have experience with and/or coursework on at least one programming language (e.g., Fortran, C, C++, Visual Basic, AML, Avenue).  If the student does not have computer programming in their background they should include it in their graduate program.

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empty  RECENT PUBLICATIONS, THESES AND DISSERTATIONS

Recent publications that typify the research undertaken by the unit include:

Brown,D.G., In press. Classification and boundary vagueness in mapping presettlement forest types. International Journal of Geographical Information Science.

Brown, D.G., Lusch, D.P., and Duda, K.A., In press. Supervised classification of glaciated landscape types using digital elevation data. Geomorphology, 19.

Krist, F.J. and Brown, D.G. 1994. GIS modeling of Paleo-Indian period caribou migrations and viewsheds in Northeastern Lower Michigan. Photogrammetric Engineering and Remote Sensing, 60(9): 1129-1137.

Brown, D.G. and Bara, T.J. 1994. Recognition and reduction of systematic error in elevation and derivative surfaces from 7-1/2 minute DEMs. Photogrammetric Engineering and Remote Sensing, 60(2): 189-194.

Brown, D.G., Bian, L., and Walsh, S.J. 1993. Response of a distributed watershed erosion model to variations in input data aggregation levels.Computers and Geosciences, 19(4): 499-509.



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