This final degree project is focused on the study, development and implementation of a software capable to calculate the coverage of a specific area by using Unmanned Aircraft Vehicles (UAV) during mapping missions. The project has been made in collaboration with the researching group ICARUS. Among other lines of research, this group have designed an architecture software for UAV mission automation which is able to modify the flight, depending on the data received, both if they are received from the ground control station or from different sensors onboard. Moreover, the systems incorporated in the UAV, are able to make series of pictures and to process them, getting at the same time the telemetry and the aircraft's attitude in the place where the images are taken. The main aim of this project consists on getting the coverage of a particular area. When the systems onboard process the taken images, they decide if is needed to dismiss some of these pictures as a result of errors caused by brightness, contrast or synchronization. It's possible that the fact of dismissing images, causes zones out of range in the area in which has to be mapped. Thus, if this happens, we have to optimize the return path of the UAV with the purpose to fill out the coverage. In order to achieve this, it has been made a study, development and implementation of a set of algorithms. Furthermore, a software has been devised to do the task mentioned above. The algorithms treated have been: a geo-referencing algorithm, which gets the coverage of the geo-referenced image, an algorithm appropriated to make Boolean operations above polygons capable to join together coverage belonging to each image getting a full coverage, and finally, an optimization algorithm to obtain a return path through the positions where it should have taken the right picture to cover the whole coverage area, in order to complete the mission. Once all the algorithms have been implemented, the software has been applied to a real case, getting the specific area coverage by a flight performed in the Pla de Vent's airdrome, in which 262 images were taken. Regarding the conclusions, is really important the use of a gimbal to reduce the geo-referencing error caused by the UAV's attitude. In addition, it have been noted the necessity of characterize the behavior of a multi-rotor vehicle and the way to fly of the different automatic pilots, with the purpose of delimiting an optimization distance function. Furthermore, it is presented the possibility of enhancing the software, by adding an algorithm to generate the flight plan when the zones out of range appears in the area to be mapped, which are caused by external errors and consequently, the systems onboard are not able to identify them.