Air-ground　coordination　systems　are　usually　composed　of　unmanned　aerial　vehicles　(UAV)　and　unmanned　ground　vehicles　(UGV).　In　such　a　system,　UAVs　can　utilize　their　much　more　perceptive　information　to　plan　the　path　for　UGVs.　However,　the　correctness　and　accuracy　of　the　planned　route　are　often　not　guaranteed,　and　the　communication　and　computation　burdens　increase　with　more　sophisticated　algorithms.　This　paper　proposes　a　new　type　of　air-ground　coordination　framework　to　enable　UAVs　intervention　into　UGVs　tasks.　An　event-triggered　mechanism　in　the　null　space　behavior　control　(NSBC)　framework　is　proposed　to　decide　if　an　intervention　is　necessary　and　the　timing　of　the　intervention.　Then,　the　problem　of　whether　to　accept　the　intervention　is　formulated　as　an　integer　programming　problem　and　is　solved　using　model　predictive　control　(MPC).　Simulation　results　show　that　the　UAV　can　intervene　in　UGVs　accurately　and　on　time,　and　the　UGVs　can　effectively　decide　whether　to　accept　the　intervention　to　get　rid　of　troubles,　thereby　improving　the　intelligence　of　the　air-ground　coordination　system.