With　the　arisen　spaceborne　multi-parameter　Synthetic　Aperture　Radar　(SAR)　systems,　such　as　Envisat　ASAR,　TerraSAR-X,　ALOS　PALSAR,　and　RADARSAT-2,　the　interest　of　crop　mapping　has　been　increasing.　The　present　study　compares　the　capabilities　of　the　multi-parameter　SAR　in　discriminating　the　main　crop　types　by　object-based　classification　in　Haian　county　of　Jiangsu　province,　South　China.　Two　kinds　of　information,　SAR　intensity　based　and　SAR　statistical　properties　based　are　used　for　Maximum　Likelihood　Classification　(MLC)　and　Minimum　Distance　Classification　(MDC)　respectively.　The　results　show　that,　the　L-band　SAR　can　uniquely　identify　mulberry　from　dry-land　crops,　such　as　maize　and　vegetable　and　C-band　SAR　has　some　advantages　in　mapping　rice.　Specifically,　the　polarimetric　RADARASAT-2　data　can　identify　the　rice　with　accuracy　about　75%　similar　to　80%　which　is　similar　as　the　result　from　X-band　TerraSAR-X　Spotlight　data　but　higher　than　that　from　C-band　dual-polarization　Envisat　ASAR　data.　Nevertheless,　both　of　X-and　C-band　can　hardly　separate　the　mulberry　from　the　other　dry-land　crops.