Fast computation of the landing footprint of a space-to-ground vehicle is a basic requirement for the deployment of parking orbits,as well as for enabling decision makers to develop real-time programs of transfer trajectories.In order to address the usually slow computational time for the determination of the landing footprint of a space-to-ground vehicle under finite thrust,this work proposes a method that uses polynomial equations to describe the boundaries of the landing footprint and uses back propagation (BP) neural networks to quickly determine the landing footprint of the space-to-ground vehicle.First,given orbital parameters and a manoeuvre moment,the solution model of the landing footprint of a space-to-ground vehicle under finite thrust is established.Second,given arbitrary orbital parameters and an arbitrary manoeuvre moment,a fast computational model for the landing footprint of a space-to-ground vehicle based on BP neural networks is provided.Finally,the simulation results demonstrate that under the premise of ensuring accuracy,the proposed method can quickly determine the landing footprint of a space-to-ground vehicle with arbitrary orbital parameters and arbitrary manoeuvre moments.The proposed fast computational method for determining a landing footprint lays a foundation for the parking-orbit configuration and supports the design of real-time transfer trajectories.