As a significant part of spacecraft, earth observation satellites play an important role in space information applications. Recently, user demands and scale of satellite constellations have considerably increased. Multi-satellite earth observation mission scheduling has become a practical problem that needs to be solved urgently in the current satellite application field. Aiming at the problem of heterogeneous satellite earth observation mission scheduling, this paper analyzes the earth observation satellite scheduling resource constraints, establishes an optimized objective function, and proposes a multi-satellite mission scheduling model. On this basis, an adaptive genetic and tabu hybrid search algorithm is proposed, the hybrid algorithm introduces an adaptive trimming strategy in solution space that can effectively overcome the shortcomings of genetic algorithm's weak local search ability and strong initial solution dependence of tabu search, and flexibly respond to different scales of scenarios. The simulation results show that the hybrid algorithm can obtain a global optimal solution in relatively high speed with average task completion rate of 94.6% above, and the scalability, adaptability, efficiency and effectiveness of the model is verified.