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For the M.S. and Ph.D degrees, a minimum of 24 and 42 credits, respectively, of graduate course work 
plus thesis must be taken as a graduate student. Joint degree programs with other departments arc also 
possible and encouraged. The program requires course work in "depth," "breadth," "interdisciplinary 
synthesis and analysis," and "analytical skills". 
Depth courses cover such areas as fundamentals of remote sensing, digital data analysis, image 
interpretation, airphoto interpretation, photogrammetry, remote sensing instrumentation, image 
processing algorithms for remote sensing, G IS, and computer cartography. Courses in an Area of 
Concentration are required for the Ph.D. This is a group of discipline/tool-oriented courses that must 
form a coherent (focused) group. Breadth courses are environmentally-related courses dealing with such 
topics as environmental decisionmaking, environmental ethics, environmental systems concepts, modeling 
and analysis of environmental systems, science and government, analysis of environmental impact, and 
global sustainability. Interdisciplinary Synthesis and Analysis are accomplished through attendance at 
the Environmental Monitoring Seminar, a weekly colloquium of guest speakers and group discussion, 
and completion of a comprehensive practicum. The practicum is a multidisciplinary team project 
oriented toward the use of remote sensing and GIS for solving a "real world" environmental problem or 
conducting a natural resource assessment. The Analytical Skills requirement calls for course work in 
calculus, statistics, and research methods. All students are required to have a working knowledge of a 
computer programming language. A thesis is required of all M.S. and Ph.D. candidates. 
REMOTE SENSING RESEARCH 
Although remote sensing research is principally centered in the IES Environmental Remote Sensing 
Center (ERSC), related research is also conducted in individual departments. Research projects at 
ERSC have been many and varied, as have been the cooperators and sources of support for the projects. 
Listed below is a representative sample of the areas of study to which remote sensing has been applied 
by ERSC investigators. 
Land cover classification - integration of expert system, GIS, and remote sensing technologies for land 
cover classification; digital land cover classification of urban/urbanizing watersheds for inclusion in 
hydrology models assessing pollutant and sediment runoff; inventory' of critical land resources using 
Landsat and SPOT data; remote sensing inputs to GIS; computer-based land use suitability analysis; 
regional and global land cover changes. 
Water quality - design of a prototype water quality monitoring system for the Great Lakes combining 
SPOT, Thematic Mapper, AVHRR and GOES data; trophic classification of Wisconsin lakes from 
Landsat MSS data; measurement of aquatic plant growth and algae blooms from remote sensing imager)'. 
Geology/hydrology - temporal analysis and mapping of glacial terrain using Landsat imagery; 
improvement of streamflow estimates in watersheds with data derived from Landsat and SPOT imagery. 
Wetlands - generalized statewide wetland mapping from Landsat imagery; quantitative photo 
interpretation for wetland mapping; comparison of data collection and analysis methods used to monitor 
impacts over time in severely disturbed wetlands. 
Forestrv/wildlife — effects of differences in spatial and spectral resolution on the information content 
of SPOT' and Landsat TM satellite data; timber type mapping, mensuration, and damage detection using 
SPOT and Thematic Mapper data; development of a remote-sensing-based hazard rating system for 
spruce arid jack pine budworm infestations; use of airborne Lidar data to remotely measure woody and 
foliar biomass; application of Airborne Imaging Spectrometer (AIS) data to understand forest canopy 
chemistry and structure; monitoring of deforestation trends in Indonesia and Malaysia; use of GIS in 
forest management; evaluating wildlife habitat using SPOT and Landsat data; using satellite data to 
monitor the lood supply and environmental conditions present during spring migration of waterfowl. 
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