Accurate　and　timely　spatiotemporal　change　information　of　rice　planting　patterns　is　significant　for　effectively　preventing　＂no-　grain＂　and　achieving　carbon　peak　and　carbon　neutrality　goals.　However,　it　is　challenging　to　establish　a　rice　mapping　method　at　large　spatial　domain.　This　study　developed　a　novel　paddy　rice　planting　mapping　method　based　on　dynamic　coupling　optical/radar　features　of　transplanting　period.　The　proposed　algorithm　was　applied　to　paddy　rice　mapping　in　Jiangxi　and　Hunan　province.　The　derived　paddy　rice　planting　map　was　evaluated　using　1402　ground　reference　sites,　and　it　had　an　overall　accuracy　of　92.80%.　The　paddy　rice　planting　area　was　also　highly　consistent　with　the　agricultural　census　data　(R2　>　0.85)　at　the　county　level.　Compared　with　rice　feature　extraction　using　a　fixed　window,　the　proposed　method　has　strong　robustness　and　migration　ability,　and　provides　a　new　idea　and　reference　for　crop　mapping　at　large　spatial　domain.　The　result　showed　that　the　paddy　rice　planting　area　in　Jiangxi　province　decreased　by　3460　km2　(9.47%)　from　2018　to　2021.　The　rice　cropping　intensity　in　Jiangxi　province　had　decreased　by　0.13　due　to　the　change　of　double-cropping　rice　to　medium　rice.　The　double-　cropping　rice　planting　area　decreased　by　21.61%,　with　84%　shifted　to　single　cropping　rice.　©　2023　Journal　of　Geo-Information　Science.　All　rights　reserved.