Assessing the Intensity of Urban Land Use Based on Radial Basis Function Network

Urban land intensive use is very important to China.Traditional intensity evalua- tion methods of land use is highly influenced by man´s subjective impact,thus the evaluation result is not accurate enough. In this paper, Radial Basis Function Network (RBFN) was set up to assess the urban land intensive use.Ezhou Municipal in Hubei province was taken as a case study. The results show that urban land use of Ezhou Municipal is on medium intensive level, which is consistent with the actual land use situation. Taking RBFN to assess the urban land intensive use is feasible, which can simplify the evaluation process, avoid man´s subjective impact,and get relatively more accurate results.Compared with Back Propagation artificial neural networks (BPNN),RBFN is more convenient and effective.