Most transportation departments collect information on where animal-vehicle collisions occur. Occasionally the information may identify the wildlife species involved in the collision and geographical location of the incident such as mile markers. Typically, maintenance personnel collect this information opportunistically rather than methodically or systematically, which often results in spatially inaccurate data. These probable errors are inherent in most agency datasets so the types of applications that the data can be used for in transportation planning are limited. To properly mitigate road impacts on wildlife and motorist safety, transportation departments need to be able to identify what specific areas are most susceptible to high road-kill rates. Research on wildlife-vehicle collisions has shown that they do not occur randomly but are spatially clustered. The presence of wildlife tends to be linked to specific habitats and adjacent land-use types. Thus, landscape spatial patterns would be expected to play an important role in determining road-kill locations and rates. This project will use wildlife-vehicle collision data to demonstrate how this information can be used to aid transportation management decision making and mitigation planning for wildlife. Recommendations will be provided to transportation departments regarding road-kill data collection techniques, the value of systematically and accurately recorded information, and how different analytical techniques can aid in identifying and prioritizing problematic areas for highway mitigation projects.