In many unmanned aerial vehicle (UAV) applications, flexible trajectory generation algorithms are required to enable high levels of autonomy for critical mission phases, such as take-off, area coverage, and landing. In this paper, we present a guidance approach which uses the improved intrinsic tau guidance theory to create spatio-temporal 4-D trajectories for a desired time-to-contact with a landing platform tracked by a visual sensor. This allows us to perform maneuvers with tunable trajectory profiles, while catering for static or non-static starting and terminating motion states. We validate our method in both simulations and real platform experiments by using rotary-wing UAVs to land on static platforms. Results show that our method achieves smooth landings within 10 cm accuracy, with easily adjustable trajectory parameters.