The overall problem of scheduling and planning in space-borne observations has always been a focused research to enhance the efficiency of agile optical satellites. However, few studies have been conducted on specific problems about time delay integration (TDI) imaging missions. In this article, a novel framework is proposed to solve the coupling scheduling and planning problems of a TDI imaging mission with multiple target strips, in which the primary objective is the average imaging resolution, and the secondary objective is the energy consumption evaluated by torque integrals. The directional reversals in push-scan imaging and TDI accumulating are considered for the first time. With the combined efforts of geometric approximations, dynamic estimations, and neural network fitting, the original problem, which is a mixed-integer nonlinear programming, is split into a series of parameter optimization problems and solved by conventional methods. Thus, details of both the scheduling and planning are studied independently without the loss of the information provided by each other. Extensive numerical simulations, including extreme scenarios with high density and large-scale clusters, indicate that the decoupled framework is reliable in generating optimized profiles for arbitrary TDI imaging missions.