In this paper, we evaluate the performance of the automated mission planning system which we developed for ocean observation of microsatellite RISESAT. RISESAT is equipped with multiple scientific instruments including Ocean Observation Camera (OOC). OOC is a wide field of view camera system and sweeps the ocean surface to evaluate the amount of Colored Dissolved Organic Matter (CDOM), which influences the carbon cycle in this planet, which is closely related to climate change. Constraint conditions exist mainly in terms of cloud coverage and the elevation angle of the satellite at a targeted point because OOC observation is conducted in the range of the visible light spectrum. Therefore, we developed an automatic mission planning system based on cloud forecasts for efficient ocean observation. In this system, we use Open Weather Map (OWM) to create cloud forecasts, and Two Line Element (TLE) and Simplified General Perturbations Satellite Orbit Model (SGP4) for orbit prediction of the satellite. Then, we propose an algorithm to output an optimised mission plan maximising the total profit. Furthermore, the performance of the system was evaluated by actual images taken by OOC and we confirmed that this system captured targeted regions properly.