In order to equip the heterogeneous multi-UAV collaborative mapping system with decision-making capability in the face of dynamic environments, an improved hierarchical distributed mission planning framework is proposed based on offline mission planning models and results for dynamic scenario algorithm application extension. Among them, the mission valuation method based on pre-planned trajectories considers the global cost, and the valuation results are updated by a local auction algorithm with restricted communication to avoid mission conflicts and local optimality; the joint trajectory correction method based on receding horizon predictive control meets the requirements of dynamic mapping and obstacle avoidance. Finally, the applicability and reliability of the planning algorithm is verified in multiple scenarios through numerical simulations.