SE Modeling Forest Fire Probabilities in the South Central United States Using FIA Data

Yushun Zhai and Ian A. Munn

Mississippi State University Forestry Department

Factors influencing the probability of fire occurrence in the south central United States were investigated using a geographic information system (GIS) and a multinomial logit model. Forest Inventory and Analysis (FIA) data at the plot level were merged with census data at the census-tract level to create a data set containing demographic, geographic, and timber-related characteristics. A multinomial logit model was employed to estimate the relationships between plot characteristics and the probability of wildfires, prescribed fires and fires of unknown origins. Wildfires occurred more frequently on public forests than industrial and non-industrial private forests (NIPFs). The probability of wildfire increased with proximity to urban areas and "built-up" areas of four hectares or more in size. Wildfires occurred more frequently in younger stands and in pine and mixed pine-hardwood types than in hardwood types.  Prescribed fires occurred more frequently on public and industrial forests than on NIPFs. The probability of prescribed fires increased with proximity to roads, urban areas, "built-up" areas of four hectares or more, and on flatter terrain but was inversely related to population density. Fire was prescribed less frequently for pole-sized stands than sawtimber size stands and more frequently for pine and mixed pine-hardwood types than for hardwood types. Education levels and median household incomes of the surrounding census tract had no significant effects on the probability of any type of fire.

corresponding author:

Ian A. Munn
Box 9681
Forestry Department
Mississippi State, MS 39762
662-325-4546
imunn@cfr.msstate.edu