With　the　rapid　development　of　space-air-ground　integrated　networks　(SAGIN),　the　synergy　between　the　satellite　and　unmanned　aerial　vehicles　(UAVs)　in　sensing　environmental　status　information　reveals　substantial　potential.　In　SAGIN,　applications　such　as　disaster　response　and　military　operations　require　fresh　status　information　to　respond　effectively.　The　freshness　of　information,　quantified　by　the　age　of　information　(AoI)　metric,　is　crucial　for　an　effective　response.　Therefore,　it　is　urgent　to　investigate　the　AoI　in　real-time　remote　sensing　systems　leveraging　satellite-UAV　synergy.　To　this　end,　we　first　establish　a　comprehensive　system　model,　corresponding　to　the　satellite-UAV　＂multiscale　explanation＂　synergy　remote　sensing　system　in　SAGIN,　in　which　we　focus　on　the　typical　information　transmission　and　fusion　strategies　of　the　system,　the　analysis　framework　of　AoI,　and　the　temporal　evolution　of　AoI.　Subsequently,　the　time-varying　process　of　the　system　model　is　transformed　into　a　corresponding　finite-states　continuous-time　Markov　chain,　enabling　a　precise　analysis　of　its　stochastic　behavior.　By　employing　the　stochastic　hybrid　system　(SHS)　approach,　the　moment　generating　functions　(MGFs)　and　mean　AoI,　offering　quantitative　insights　into　the　freshness　of　status　information,　are　derived.　Following　this,　a　comparative　analysis　of　AoI　under　different　queuing　disciplines,　highlighting　their　respective　performance　characteristics,　is　conducted.　Furthermore,　considering　transmit　power　and　bandwidth　constraints　of　the　system,　the　AoI　performances　under　full　frequency　reuse　(FFR),　and　frequency　division　multiple　access　(FDMA)　strategies　are　analyzed.　The　energy　advantage　and　spectrum　advantage　associated　with　AoI　are　also　examined　to　explore　the　superior　AoI-related　performance　of　the　FFR　strategy　in　SAGIN.