A layer-based projective dependency parsing approach is presented.This novel approach works layer by layer in a bottom-up manner,in which the depth of token dependency is allowed no more than one.Inside the layer the dependency graphs are searched exhaustively while between the layers the parser state transfers deterministically.Taking the dependency layer as the parsing unit,the proposed parser has a lower computational complexity than graph-based models which search for a whole dependency graph,alleviating the error propagation in transition-based models to some extent.Furthermore,our parser adopts the sequence labeling models to find the optimal sub-graph of the layer,which demonstrates the sequence labeling techniques qualified for hierarchical structure analysis tasks.Experimental results indicate that the proposed approach offers desirable accuracies and especially a very fast parsing speed,with 2500 words per second for Penn Treebank.