Complex　cropping　patterns　with　crop　diversity　are　an　underexploited　treasure　for　global　food　security.　However,　significant　methodological　and　dataset　gaps　in　fully　characterizing　cropland　cultivated　with　multiple　crops　and　rotation　sequences　hinder　our　ability　to　understand　and　promote　sustainable　agricultural　systems.　Existing　crop　mapping　models　are　challenged　by　the　deficiency　of　ground　reference　data　and　the　limited　transferability　capabilities　across　large　spatial　domains.　This　study　aimed　to　fill　these　gaps　by　proposing　a　robust　Complex　Cropping　Pattern　Mapping　framework　(CCPM)　capable　of　national-scale　automatic　applications　using　the　Sentinel-1　SAR　and　Sentinel-2　MSI　time　series　datasets.　The　CCPM　framework　addresses　these　challenges　by　integrating　knowledge-based　approaches　&　data-driven　algorithms　(Dual-driven　model)　and　Phenological　Normalization.　The　CCPM　framework　was　implemented　over　conterminous　China　with　complex　cropping　systems　dominated　by　smallholder　farms,　and　the　first　national-scale　10-m　Cropping　pattern　map　with　descriptions　of　cropping　intensity　and　10　crops　in　China　(ChinaCP-T10)　in　2020　was　produced.　The　efficiency　of　the　CCPM　framework　was　validated　when　evaluated　by　18,706　ground-truth　reference　datasets,　with　an　overall　accuracy　of　91.47　%.　Comparisons　with　existing　crop　data　products　revealed　that　the　ChinaCP-T10　offered　more　comprehensive　and　consistent　information　on　diverse　cropping　patterns.　Dominant　cropping　patterns　diversified　from　single　maize　in　northern　China,　winter　wheat-maize　in　North　China　Plain,　single　oilseeds　in　Western　China,　to　single　rice　or　double　rice　in　Southern　China.　The　key　cropping　patterns　changed　from　double-grain　cropping,　single　grain　to　single　cash　cropping　with　increasing　altitudes.　There　were　151,744　km2　planted　areas　of　double　grain　cropping　patterns　in　China,　and　multiple　cropping　accounted　for　36.1　%　of　grain　cultivated　area　nationally.　Over　80　%　of　grain　production　was　mainly　implemented　at　lower　altitudes　as　the　Non-Grain　Production　(NGP)　ratio　enhanced　from　32　%　within　elevations　below　200　m　to　over　70　%　among　elevations　above　700　m.　Consistent　datasets　on　complex　cropping　patterns　are　essential,　given　the　significant　roles　of　diversification　and　crop　rotations　in　sustainable　agriculture　and　the　frequently　observed　inconsistencies　in　existing　crop　data　products　based　on　thematic　mapping.