Abstract: In order to carry out quantitative monitoring of modern tobacco in plateau mountain area, a new method was proposed in which high resolution synthetic aperture radar (SAR) method was applied to rapidly monitor tobacco, since weather in Guizhou plateau is too rainy to obtain optical data. The results showed that the after scattering feature of different ground objects was extracted by difference, and used classification method of SVM to classify ground objects, the accuracy of total classification was 85.08%, and tobacco identification accuracy was 78.36%. Using of regression analysis, the monitoring model between the tobacco growth parameters and the backscattering coefficient was established. The model which was between the leaf length/leaf width and HH polarization backscatter coefficient or leaf fresh weight and HH, VV polarization backscattering coefficients could reflect the linear regression equation. The high resolution SAR data as the data source of the new remote sensing techniques can provide rich backscatter information of typical objects in plateau mountainous area, and provide technical support for modern tobacco agriculture in large-scale and real-time monitoring by remote sensing.