There is a very large variation in the difference between scheduled and actual flight arrival and departure times, which results in a high degree of uncertainty in the airport demand. Consequently, there is a great need for tools that provide awareness of both the current and predicted future situation. The Surface Management System (SMS) developed by NASA Ames has partially addressed this need; but both its display and its modeling currently assume that the locations of aircraft on the airport surface will be provided by surface surveillance. In this SBIR, Metron Aviation will study the prediction of airport demand with varying levels of surface surveillance. The Phase 1 objective is to demonstrate the feasibility of predicting, with limited or no surface surveillance, flight OOOI times accurately enough to enable airport surface automation. In Phase 2, we will investigate decision support display designs appropriate for the lack of surveillance and evaluate them at Atlanta.