Abstract: Abstract: 【Objective】The analysis of urban expansion simulations is an effective way to reveal the characteristics, mechanisms, and evolutionary processes of urban land use systems. 【Method】Nonlinear transformation rules defined by nonlinear classification of Support Vector Machine(SVM)for the Cellular Automata(CA)are used to calculate regional-spatial variables, such as the distance between cellular and the center of Putian City, business centers, different types of roads, and geological and geomorphological control boundaries. The contribution of these variables toward the transformation of each cellular to the urban development is then calculated. A CA-SVM-based urban expansion simulation model is established to reveal the trend of urban land expansion in Putian City. 【Result】The classification hyperplane in the SVM-CA model is defined considering the minimization of structural risk and maximum distance interval. Results indicate that the accuracy of the point-by-point comparison of this model to simulate the urban expansion is up to 83%. Urban expansion is mainly concentrated in the northeast, southeast, and southern coastal regions of Putian City. The city also exhibits a pattern of axial expansion along the main roads. A spatial salutatory layout can be seen at traffic network nodes along the coastal line, harbors and wharfs, etc. 【Conclusion】CA-SVM model can reflect quantitatively the role of each spatial element in the urban pattern of the study area, and further to analyze the major rule of city.