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Aerial assets are often used for missions such as intelligence, surveillance, target acquisition and reconnaissance. The pilot’s search decisions reflect a mental model for the search space, including characteristics such as target prioritization, distance-reward evaluations, and path optimization cri-teria. To investigate differences in these mental models, we examined 23 participants’ paths flown in a synthetic task environment in which they piloted a simulated aircraft to search for targets rep-resenting missing persons. Determining similarity among flight paths is a challenge. To accom-plish this, we used a new tool (Pathmapping, a package in the R statistical computing language; Mueller, Perelman, & Veinott, 2015) to determine area-based path similarities among the test sub-jects’ flight paths, and mixture modeling to analyze those similarities. The results indicate that an area-based measure of path similarity can be used to infer mental models from flight paths pro-duced during a simulated search task.