AbstractsGeography &GIS

Mountain glaciers are an important resource for monitoring how regions are being affected by global environmental changes because their advance and retreat are influenced by fluctuations in precipitation and temperature. Using Mt. Shasta in northern California as the study area, this thesis employed a time-series approach to remote sensing image analysis coupled with a Markov-based procedure to demonstrate how remote sensing can be used to define the environmental trajectories active in the region and project those trends into the future. This experimental approach was applied to a series of yearly images from 1985 to 2010 to examine the long-term implications of environmental change and then the trends were projected forward in varying increments to 2110. The long-term change signal showed that El Nino cycles strongly influenced regional land cover patterns and controlled glacial advance and retreat. When this pattern was projected into the future, two scenarios were observed: 1) growth if El Nino cycles strengthen or 2) recession if El Nino cycles weaken.