Crop nitrogen content estimation by remote sensing technique is a topic research in remote sensing monitoring of agricultural parameters. Monitoring of crop nitrogen content based on multi-spectral satellite data is still at the exploratory stage. Ground-based canopy spectral reflectance and leaf nitrogen content of winter wheat were measured in field, and plot experiments consisted of varied nitrogen fertilization levels and winter wheat varieties across the whole growth stage. Multi-spectral broadband reflectance data of six satellites were simulated using the measured hyper-spectral reflectances and spectral response functions of Landsat 8, SPOT 6, HJ-1A, HJ-1B, GF-1 and ZY-3. Spectral indices derived from simulated broadband spectral reflectance data across the visible and near infrared bands were used to construct the LNC estimation models. The results showed that there were no significant differences between simulated broadband reflectances and spectral indices among six satellite platforms; all the selected spectral indices were significantly related with the LNC in the whole wheat growth period and all the estimation models based on the ten spectral indices passed the significance test respectively; transformed chlorophyll absorption in reflectance index/optimized soil-adjusted vegetation index (TCARI/OSAVI), chlorophyll absorption in reflectance index (TCARI) and ratio vegetation index (RVI) were more sensitivity than the other spectral indices in LNC estimation with the noise equivalent less than 1.6; TCARI/OSAVI was proved to be the best spectral index for LNC estimation with determination coefficient R 2 of 0.62 and noise equivalent of 1.26.