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Title
Modern trends of education in photogrammetry & remote sensing

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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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