In order to improve the matching probability and matching accuracy of synthetic aperture radar (SAR) scene matching-suitable area (MSA), a SAR scene MSA selection method based on support vector machine(SVM) is proposed. Firstly, digital elevation modelbased, intensitybased and featurebased measure parameters are selected based on the characteristics of SAR images. Then based on the integrated feature vectors, SVM is employed to training sample data, and decision function which could separate suitable and unsuitable-matching area class is obtained. This method fully considers the impact of SAR image information on the results of the selecting MSA and the correlation between the characteristic parameters. Experimental results show that this method can effectively single out high performance MSA.