In　order　to　estimate　traffic　densities　in　a　large-scale　urban　freeway　network　in　an　accurate　and　timely　fashion　when　traffic　sensors　do　not　cover　the　freeway　network　completely　and　thus　only　local　measurement　data　can　be　utilized,　this　paper　proposes　a　decentralized　state　observer　approach　based　on　a　macroscopic　traffic　flow　model.　Firstly,　by　using　the　well-known　cell　transmission　model　(CTM),　the　urban　freeway　network　is　modeled　in　the　way　of　distributed　systems.　Secondly,　based　on　the　model,　a　decentralized　observer　is　designed.　With　the　help　of　the　Lyapunov　function　and　S-procedure　theory,　the　observer　gains　are　computed　by　using　linear　matrix　inequality　(LMI)　technique.　So,　the　traffic　densities　of　the　whole　road　network　can　be　estimated　by　the　designed　observer.　Finally,　this　method　is　applied　to　the　outer　ring　of　the　Beijing＇s　second　ring　road　and　experimental　results　demonstrate　the　effectiveness　and　applicability　of　the　proposed　approach.　©　2017　by　the　authors.