Seaweed biomass is mainly investigated using quadrat sampling. However, the spatial limitations of quadrat sampling pose significant challenges to the thorough evaluation of seaweed resources at a larger scale. We combined multispectral photography collected using an unmanned aerial vehicle with satellite imagery and in situ hyperspectral reflectance measurement to determine the biomass of Ulva pertusa and Sargassum spp. in the intertidal zone of Gouqi Island, Zhejiang Province, China. The statistical metrics derived from aerial imagery for the biomass estimation of Ulva pertusa and Sargassum spp. achieved coefficients of determination (R2) of 0.81 and 0.74, root mean square errors (RMSE) of 96.54 and 788.64 g/m2, and mean absolute errors (MAE) of 40.71 and 327.12 g/m2, respectively. For satellite imagery, the R2 values were 0.80 and 0.68, RMSE were 97.65 and 910.45 g/m2, and MAE were 71.78 and 719.69 g/m2, respectively. The biomass of U. pertusa and Sargassum spp. fluctuated monthly, reaching their highest values in June and July, respectively. The total biomass of U. pertusa and Sargassum spp. was 1.69×107 and 9.93×107 g, and the organic carbon content was 7.98×105 and 5.04×106 g, respectively. Our research offers a new perspective and methodology, supplying critical data and a scientific rationale for the management of marine assets and the safeguarding of coastal ecologies.