Mission Planning is a complex and critical part of space mission design. Classical techniques do not scale well in large constellations of satellites, because of the level of human involvement required in the process. Most recent constellations can count tens and hundreds of small satellites, making a higher level of automation in planning not only desirable, but necessary. This thesis presents a brief description of modern mission planning problem modelling techniques and their solving algorithms and than studies the development of a Mission Planner capable of scheduling the tasks of a variable number of remote sensing satellites. In order to show the capabilities of the program, a case study with real and realistic satellites is presented.