Abstract: Urban smart growth has become an environmental protection method widely used by urban planners and decision makers to build cities, which has practical significance to measure the level of urban smart growth. In this paper, rational degree (RD) is defined to describe the level of urban smart growth, then RD model is established through principal component regression (PCR) and radial basis function (RBF) neural network. Taking Yumen and Otago as examples, their RD values are 0.04482 and 0.04591 respectively, which indicates that both cities’ smart growth development mode has achieved certain success. The urban development level of Otago is better than that of Yumen. At the same time, this study finds that Yumen should give priority to urban greening and environmental protection, while Otago should give priority to economic development. The proposed model provides a powerful reference for the cities to pursue scientific and smart growth.

Key words: smart growth, rational degree, RBF neural network, principal component regression