Abstract: The field monitoring of laver farming rafts is difficult as they have irregular sizes of distribution and large numbers. The satellite images cannot provide accurate area of laver farming rafts due to low resolution. In contrast, UAV plays an important role in raft aquaculture surveys for its strong maneuverability and high image resolution. This paper takes the floating raft aquaculture in Haizhou Bay of Lianyungang as the research object, and studies the distinguishable degree of the visible light spectra of the breeding raft and the water body. The automatic extraction experiments for floating raft aquaculture are performed based on 6 vegetation indexes, and the accuracies of these experiments are analyzed by comparing the automatically extracted estimates with the visual interpretation values. Moreover, the applicability of the methods is analyzed based on UAV images obtained at different phases and regions. Results show that the green light band (Green, G) and vegetation index(Vegetativen，VEG) methods perform well whether in shallow waters or in deep waters with accuracies exceeding 91.00% for both number and area of laver farming rafts. These two methods also perform well in other seas with accuracy for number exceeding 93.02% and for area exceeding 89.37%. The paper reveals that UAV visible image can realize the automatic extraction of laver farming rafts and the accuracy meets the needs for laver farming surveys.