Intensity Evaluation of Urban Land Use Based on Back-Propagation Artificial Neural Networks

The traditional intensity evaluation method of land use is highly influenced by man´s subjective impact, thus the evaluation result is not accurate enough. In this paper, a BP artificial neural networks model was set up to evaluate the urban land intensive use. On the basis of that, 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 BP artificial neural networks to evaluate the urban land intensive use is feasible, which can simplify the evaluation process, avoid man´s subjective impact, and get relatively more accurate results.