Abstract China has lost 50% of its mangroves since the 1950s, while the remaining mangroves are exhibiting an increase in fragmentation. While a detailed mangrove map of China derived from remote sensing imagery is crucial for protecting mangroves, fragmented mangrove patches are hardly captured by Landsat-derived 30-m-resolution maps. To overcome this limitation, we proposed 10-m-resolution mangrove maps for 2017 using Sentinel SAR and optical time-series imagery, together with terrain data. We first classified coastal land covers based on quantile synthesis; following this, the mangrove category was refined by applying the tidal flat constraint and manual editing. The proposed approach considered factors that limit the accuracy of mangrove maps, including tidal inundation, intertidal terrain, cloudiness, and phenological variations of vegetation. A pixel-based mangrove map (PXL_Map) and an object-based mangrove map (OBJ_Map) were produced using the Google Earth Engine cloud computing platform. PXL_Map achieved an overall accuracy of 95.3 ± 0.2% based on validation samples, and a 91.6% accuracy based on field sample plots. OBJ_Map had a slightly lower performance than PXL_Map. The maps produced in this study improved the delineation of small mangrove patches along tidal creeks relative to recent Landsat-based maps. The total mangrove area was estimated to be between 21,148 ha (by PXL_Map) and 24,801 ha (by OBJ_Map). Furthermore, the spatial differences among the mangrove maps produced in this study were quantitatively compared with three other existing mangrove maps. The discrepancies among maps could have been due to the size and the location of the mangrove patches. The 10-m-resolution mangrove maps from this study can help manage and protect mangroves in China, especially the small fragmented mangrove patches scattered along the coast.