This　paper　presents　the　dynamic　identification　of　the　Ostiglia-Revere　railway　bridge,　a　steel　truss　girder　bridge　located　in　Northern　Italy.　The　bridge　is　6.6　m　wide,　about　940　m　long　and　composed　of　12　spans.　The　accelerations　of　a　bridge　span　caused　by　both　ambient　excitation　and　train　passages　have　been　continuously　measured　from　August　to　November.　The　monitoring　system　consists　of　4　temperature　sensors　and　4　biaxial　MEMS　accelerometers,　acquiring　accelerations　with　a　sampling　frequency　of　80　Hz.　Modal　properties　are　estimated　adopting　two　different　identification　approaches,　namely　the　Enhanced　Frequency　Domain　Decomposition　and　the　Stochastic　Subspace　Identification.　Particular　attention　is　paid　to　two　crucial　issues　for　vibration-based　structural　health　monitoring:　the　recognition　of　the　same　structural　mode　from　results　identified　during　different　time　windows　(i.e.;　mode　clustering),　and　the　temperature　effect　on　estimated　modal　properties.　As　the　latter　is　concerned,　two　regressive　models,　namely　a　linear　regression　model　and　an　ARX　model,　are　fitted　to　the　frequency-temperature　data,　strongly　reducing　the　eventuality　of　false　vibration-based　damage　detections　in　the　future.　©　2024　Elsevier　B.V..　All　rights　reserved.