Date of Award:
Master of Science (MS)
Environment and Society
Department name when degree awarded
Geography and Earth Resources
Geographic Information Systems (GIS) are increasingly used to examine fire activity. This study uses GIS to determine fire likelihood probabilities at an intermediate scale ( I-kilometer) on a daily basis given readily available data. Layers used for the analysis included slope, aspect, elevation, fuel type, proximity to existing fires, maximum temperature, minimum temperature, relative humidity, average vapor pressure deficit, precipitation, 1-hour fuel moisture, and 10-hour fuel moisture.
There were three objectives of this study: 1. Establish a correlation between burn perimeters and readily available topographic and environmental data, and map the spatial distribution of these as fire likelihood areas; 2. Compare each day's fire likelihood areas to fire perimeters from the next day to determine to what extent areas deemed to be high fire likelihood on a given day could be used to identify likelihood areas for the subsequent day; 3. Create a generalized model using the fewest and most frequent significant variables and test this model as a general predictive tool for fire likelihood over a given season.
Redundant variables and variables determined not to be significant at this scale were removed from the model. Variables that best explained the fire activity were identified and used to spatially map fire likelihood for any given day. By comparing subsequent days fire activity to the previous days fire likelihood areas, it was determined that the previous fire likelihood areas can be used as an indication for the subsequent day' s fire likelihood areas with a reasonable level of accuracy.
Although factors changed from day to day, the most significant variables tended to be slope, elevation, fuel type, and 1-hour fuel moisture. These variables were incorporated into a generalized model which, when mapped spatially, provided a method to compare increasing or decreasing levels of fire likelihood on a temporal scale. The results were coarser, but still indicated that a generalized model could be used to identify the next day' s fire likelihood areas given the previous days spatial plots. When compared to new fire starts, fires occurred in areas of moderate fire likelihood probabilities and very few occurred in areas of low probability.
Reading, Russell W., "Using Geographic Information Systems and Remote Sensing to Analyze Fire Likelihood Areas at the Regional Scale in the Western United States" (2003). All Graduate Theses and Dissertations. 7269.
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