The discrimination of grain size of modern aeolian sands and beach sands is one of the heated argument problems in coastal aeolian research. Based on the data of grain size of 141 modern Aeolian sand samples and 70 beach sand samples from the southern Fujian coast

eastern Guangdong coast

western Guangdong coast and Hainan island coast which are the typical coastal dune distribution places in south China coast

the modern aeolian sands and beach sands are quantitatively discriminated by use of the multivariate linear discriminant analysis method and B-P artificial neural network analysis method. The results show that the B-P artificial neural network analysis method has higher discrimination precision than the multivariate linear discriminant analysis method. Modern aeolian sands and beach sands in Hainan island coast could be discriminated based on the grain size data by use of the B-P artificial neural network analysis method. However

viewing the results as a whole

the modern aeolian sands and beach sands in south China coast could not be significantly discriminated based on grain size by using two quantitative discriminated methods.