The salt ion in halophytes is an important index to evaluate the nutritional status of plants, which reflects the adaptive strategies of vegetation to salt stress. In this study, the halophytes of the Ebinur Lake Wetland Nature Reserve are taken as the target area. The salt ion content data and the leaf spectral reflectivity date of seven types of halophytes in October 2016 are used to analyze the correlativity between salt ion Ca 2+, K +, Mg 2+, Na + and ratio vegetation index (RVI), difference vegetation index (DVI) and normalized difference vegetation index (NDSI). The best band combination is selected. The estimation models of 12 salt ions of leaf and spectral reflectivity are built. The best fitting model is selected from accuracy test. The results show that the correlativity between the salt ion content of leaf and the original spectral reflectivity is low. And the significant negative correlation with reflectivity of each band is mainly Na + content. The correlation between Na + content and the vegetation indices of RVI, NDSI and DVI is the best. The correlation is above 0.5, and the band is mainly locating in the region of near infrared and middle infrared. The best estimation models for Na +, Ca 2+, Mg 2+ and K + are VDVI(R1750,R1480), VDVI(R478,R440), VNDSI(R450,R375) and VRVI(R405,R375), which use the independent variables to build the cubic polynomials, respectively. The maximum correction index of the mode is the biggest (R=0.806), and the mode uses VRVI(R1100,R1125) as independent variable to build the cubic polynomial. It shows that the model has high fitting degree and good prediction effect. It can be used to monitor the salt status of halophytic vegetation leaf in real-time and provide a technical approach for the accurate diagnosis of salt content of halophytic vegetation leaf.