Master of Environmental Studies (MES)
Geography & Environmental Studies
Faculty of Arts
This study attempts to introduce elements of data uncertainty into the Shore and Safranyik model for approximating risk and susceptibility ratings for Mountain Pine Beetle attack in the Morice Forest District of British Columbia, Canada. Data uncertainty is introduced into the modeling procedure by introducing attribute uncertainty and spatial (boundary) vagueness into representations of Forest Inventory Polygon data, an essential component of the Shore and Safranyik modeling system, for the purposes of assessing the effects of uncertainty on the results of the Shore and Safranyik susceptibility modeling procedure. Introducing uncertainty into the forest inventory data is done by introducing spatial vagueness to the discrete forest polygon data (accomplished using a geostatistical approach) as well as attribute uncertainty through a neighbourhood-based weighting algorithm, resulting in a forest inventory representation which incorporates both spatial and attribute uncertainty and can be incorporated into the Shore and Safranyik modeling procedure. The impacts of data uncertainty are assessed by comparing the results of the Shore and Safranyik model derived using representations of forest data which incorporates uncertainty, versus the use of traditional or discrete data inputs.
Alfano, Anthony L., "Modeling uncertainty in mountain pine beetle management systems" (2006). Theses and Dissertations (Comprehensive). 464.