Different vegetation species have different biological quality and produce different ecological functions and greenery effect.Considering the "Vegetation Quality" is difficult to be obtained

the biological quality and ecological effect of urban greenery can be indirectly reflected using urban green-land area and vegetation species.Based on the comparison of the traditional statistic parameter and non-parameter classification methods and the analysis of kernel-function of SVM

SVM decision-making tree model for urban vegetation classification is designed in this paper using the high resolution imagery data of IKONOS.The classification results are compared to other traditional methods and have an average vegetation classification accuracy of about 83.5% and green-land area accuracy nearly 95%.