Abstract: The aim is to calculate the aboveground biomass of Robinia pseudoacacia in Gudao forest farm of the Yellow River Delta based on UAV airborne laser radar. Taking the R. pseudoacacia forest in the island forest of the Yellow River Delta as the research object, using the UAV airborne laser radar data, the watershed segmentation algorithm was used to extract the height and the crown diameter of the R. pseudoacacia in the island forest from the single wood scale; then the backpack mobile radar was used to fit eight samples. The DBH was combined with the allometric growth equation to calculate the biomass of 8 plots of R. pseudoacacia forests from the single wood scale. To verify the results, the measured tree height and DBH were used to validate the single wood structure parameters extracted from the radar data. The tree height and crown diameter extracted by UAV LIDAR and the logarithmic form of logarithm and product logarithm of the UAV were used to construct and estimate the aboveground biomass model of R. pseudoacacia and discuss the uncertainties in the model estimation process. Biomass distribution map was obtained, and previous research on the health status of the island-specific R. pseudoacacia was analyzed. The results showed that: (1) based on the watershed segmentation algorithm, the single wood structure parameters of the R. pseudoacacia could be extracted from the UAV LIDAR data accurately; (2) the logarithmic model of the product of crown and tree height (R2=0.82, RMSE=3.66 kg/plant) was superior to the non-logarithmic model (R2=0.58, RMSE=6.73 kg/plant) and was better than the logarithm model (R2=0.76, RMSE=4.52 kg/plant); (3) there was a certain degree of uncertainty in the model construction process, this uncertainty mainly came from the single wood recognition process; (4) there was a strong correlation between the aboveground biomass and its health status.