EOSs (Earth Observing Satellites) circle the earth to take shots which are requested by customers. To make replete use of resources of EOSs, it is required to deal with the problem of united imaging scheduling of EOSs in a given scheduling horizon, which is a complicated multi-objective combinatorial optimization problem. In this paper, we construct a mathematical model for the problem by abstracting imaging constraints of different EOSs. Then we propose a novel multi-objective EOSs imaging scheduling method, which is based oil the Strength Pareto Evolutionary Algorithm 2. The special encoding technique and imaging constraint, control are applied to guarantee feasibility of solutions. The approach is tested upon four real application problems of CBERS EOSs series. From the results, it is confirmed that the proposed approach is effective in solving multi-objective EOSs imaging scheduling problems.