Recently, UAVs (Unmanned Aerial Vehicles) gain a wider acceptance from many disciplines. One major application is for monitoring and mapping. Flying beyond eye sight autonomously and collecting data over large areas are their obvious advantages. To support a large scale urban city mapping, we have developed a UAV system which can carry a compact digital camera as well as a navigational grade of a Global Positioning System (GPS) board mounted on the vehicle. Unfortunately, such a navigational system fails to provide sufficient accuracy required to process images become a large scale map. Ubiquitous digital compact cameras, despite their low cost benefits, are widely known to suffer instabilities in their internal lenses and electronics imaging system. Hence these cameras are less suitable for mapping related purposes. However, this paper presents a photogrammetric technique to precisely determine intrinsic and extrinsic camera parameters of photographed images provided that sufficient numbers of surveyed control points are available. A rigorous Mathematical model is derived to compute each image position with respect to the imaging coordinate system as well as a location of the principal point of an image sensor and the focal length of the camera. An iterative Gaussian-Newton least squares adjustment method is utilized to compute those parameters. Finally, surveyed data are processed and elaborated to justify the mathematical models.