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,　multi-temporal　ASAR　alternative　polarization　data　are　used　for　the　identification　of　rice　crop　in　Fujian　province.　A　procedure　has　been　developed　using　multi-date　ASAR　data　for　rice　crop　identification.　The　procedure　comprises　two　parts:　data　preprocessing　and　classification　of　multi-date　data　for　rice　field.　Some　novel　methods　are　applied　in　image　preprocessing　such　as　correlation　matching　for　image　co-registration　and　multi-channel　filtering　for　speckle　suppression.　Object-oriented　classifier　was　used　for　classification.　By　adopting　the　procedure,　classification　accuracy　of　90%　was　achieved　in　the　test　sites　with　multi-temporal　Envisat　ASAR　data.