Nowadays countries provide great resources for the research and development activities to develop Unmanned Air Vehicle technologies. The most important problem encountered in efficient use of these technologically intensive systems is to determine the minimum cost route plan which can observe the maximum number of targets. Unmanned Air Vehicle Route Optimization Problem is considered as the integration of Traveling Salesman Problem and Vehicle Routing Problem in the literature. Unmanned Air Vehicle Route Models can be developed by incorporating the vision capabilities of the sensors into the route plan. In this study, taking into account the sensor capabilities an integrated linear model and a two-phased heuristic routing algorithm are proposed for the route planing process of Unmanned Air Vehicle. A generic scenario related to surveillance and reconnaissance activities on southern borderline of Turkey has been developed in order to test the proposed models. The test results show that integrating sensor vision capabilities on Unmanned Air Vehicle flight route model is effective in minimization of total flight distance and the proposed two-phased heuristic routing algorithm can be effectively used in the Unmanned Air Vehicle route planing process.