Using space-borne remote sensing information to monitor the crop canopy nitrogen status and crop productivity in a large-scale is of great significance and application prospect i1 modern agriculture. With the hyper-spectral reflectance data from the wheat canopy under different nitrogen fertilization levels, this paper constructed the spectral indices (including the single wavelength, ratio spectral index, and normalized difference spectral index) simulated by satellite channels, and established the nitrogen estimation equations by quantifying the relationships between the simulated channels spectral indices and the leaf nitrogen index. The results indicated that the spectral indices based on NDVI (MSS7, MSS5), NDVI (RBV3, RBV2), TM4, CH2, MODIS1, and MODIS2 could be reliably used for estimating the leaf nitrogen content (LNC), with R2 over 0.60, and the spectral indices based on NDVI (PB4, PB2), NDVI (CH2, CHl1), NDVI (MSS7, MSS5), RVI (MSS7, MSS5), MODIS1, and MODIS2 could be accurately used for predicting the leaf nitrogen accumulation (LNA), with R2 greater than 0.86. Comparatively, NDVI (MSS7, MSS5) and NDVI (PB4, PB2) could be the more suitable spectral indices for predicting the wheat canopy LNC and LNA, respectively.