This study uses multivariate regression analysis to gain a better understanding of what factors are influencing deer vehicle accident distributions in Kansas. The study examines an 17 year time span from 1992 to 2008, with the years 1992, 2001, and 2008 chosen to serve as snapshots for the overall time period. Variables associated with roads, land use, human, and deer populations are examined to determine how the influence of these factors affects the distribution of deer vehicle accidents throughout the state. Using multivariate regression analysis, the county level models revealed that the primary factors responsible for deer vehicle accident distributions are human related. Bridge density and human population density were the main factors influencing deer vehicle accident distributions for all the years examined. Additionally, percent of land used for hay, percent of land used for wheat, highway density, and deer harvest density were factors found influential in at least one or more of the yearly models. Overall, the types of factors and their level of influence in each of the models were fairly consistent for all the years, the exception being 1992 which saw the greatest variation in factor influence. From the results it is clear that mitigation techniques aimed at changing driver habits and increasing their awareness to the dangers posed by deer would be the most likely to secede at reducing deer vehicle accident rates in Kansas.Department of Geograph
