Taking the oasis of lake Bosten Lake as the research area，the spectral index was optimized by fractional differential，the characteristic bands of the hyperspectral data were screened，and the estimation model of the soil conductivity hyperspectral data was constructed by partial least square regression(PLSR) and support vector machine(SVM).The results show that:(1)The correlation between the fractional-order differential hyperspectral data and soil conductivity showed that as the fractional-order differential order increased，the number of characteristic bands gradually increased.The second order was the order with the largest number of characteristic bands，the number of characteristic bands is 335(P=0.01)，and the maximum absolute value of the correlation coefficient was 0.64.(2)The hyperspectral data of the fractional differential optimtzation spectral index shows that with the increase of the fractional-order differential order，the spectral matrix chart showed that the correlation coefficient fluctuated greatly between positive and negative values，and the absolute value of the correlation coefficient of the 0.8 order the spectral index DSI was the maximum 0.75.The maximum absolute value of the correlation coefficient of the square root，the logarithm，and the reciprocal was 0.64.(3)The soil conductivity estimation model was constructed based on PLSR and SVM.The estimation model based on characteristic bands selected by the 0.8 order differential and spectral index DSI had a good estimation effect.The estimation model constructed by SVM was the best，and the model accuracy was RSVMc2=0.89，RMSESVMc=0.03，RSVMv2=0.80，RMSESVMv=1.12.The SVM estimation model could be used to quantitatively estimate the soil conductivity in the study area.