Synthetic　Aperture　Radar　(SAR)　is　anticipated　to　be　the　dominant　high-resolution　remote　sensing　data　source　for　agricultural　applications　in　tropical　and　subtropical　regions　due　to　its　independent　from　cloud　cover.　ENVISAT-1　ASAR　is　the　most　advanced　satellite　radar-imaging　instrument,　its　capabilities　include　beam　steering　for　acquiring　images　with　different　incidence　angles,　duel　polarization　and　wide　swath　coverage.　Agricultural　crop　inventory　based　on　remote　sensed　data　will　be　improved　greatly　by　ASAR＇s　new　capabilities.　In　this　paper,　a　procedure　has　been　developed　using　multi-date　ASAR　data　for　rice　crop　inventory.　The　procedure　comprises　two　parts:　data　preprocessing　and　classification　of　multi-date　data　for　rice　field.　In　order　to　carry　out　the　research,　6　scenes　of　ASAR　images　covering　Fuzhou　area　year　round　of　2004　were　used.　PCI　9.1　is　used　for　data　preprocessing　which　includes　data　calibration,　image　co-registration,　speckle　suppression,　orthorecitification　and　amplitude-to-dB　conversion.　Some　novel　methods　are　applied　in　this　procedure　such　as　correlation　matching　for　image　co-registration　and　multi-channel　filtering　for　speckle　suppression.　Object-oriented　classifier　was　used,　compared　with　K-means　supervised　classifier　and　maximum　likelihood　classifier,　and　higher　classification　accuracy　was　achieved.　By　adopting　the　procedure　presented　in　this　paper,　more　than　90%　classification　accuracy　for　rice　was　achieved　in　Fuzhou　city　with　multi-date　Envisat　ASAR　data.　This　indicates　that　the　procedure　is　feasible　for　rice　crop　inventory　using　multi-date　ASAR　data.