This paper investigates a boundary tracking problem using multiple quadrotor UAVs to detect and track the boundary of physical events. We set the boundary estimation problem as a classification problem of the region in which the physical events occur, and employ SVL (Support Vector Learning). We also demonstrate a velocity vector field which is globally attractive to a desired closed path with circulation at the desired speed and a virtual phase for stabilizing the collective configuration of the multiple quadrotors. Experimental results with multiple quadrotors show that this study provides good performance of the collective boundary tracking.