The invention provides an agile satellite task planning and scheduling modeling method based on genetic optimization, which comprises the following steps of: dynamically decomposing a to-be-observed complex observation target task area according to an observation demand of a user and a resource condition of a satellite, and generating a meta-task set with a plurality of time windows; constructinga constraint analysis model according to the task constraint, the resource constraint and the relationship between the task constraint and the resource constraint, wherein the constraint analysis model comprises a satellite energy constraint model, a storage constraint model, a minimum pitch angle constraint model and an attitude maneuver stability constraint model; establishing a single-satellitetask planning mathematical model according to the multi-time window element task set; and utilizing a genetic search algorithm to optimize and solve the single-satellite task planning mathematical model, judging whether the established constraint analysis model is met or not, and generating a final executable observation plan scheme. According to the method, the task observation plan scheme meeting the maximum objective function and different constraint analysis can be generated, satellite resources are effectively utilized, and the task planning efficiency is improved.