Remote sensing-based in-season N recommendations have been proposed as a technique to improve N fertilizer use efficiency. Remote sensing estimation of South Dakota hard red spring wheat N requirements needs assessment. Research objectives were: (1) determine the effect of an in-season N application on grain yield, yield loss to nitrogen stress (YLNS), and grain protein; and (2) assess if remote sensing collected at different growth stages may be used to predict yield parameters. Research was conducted at Dakota Lakes Research Farm, Pierre, SD, USA in 2003 and 2004 under irrigated (2003 and 2004) or rainfed (2004 only) conditions. Nitrogen rates were applied pre-emergence or in-season at Haun 5-6. Canopy reflectance was measured at selected intervals from 485 – 1650 nm at Haun 3-4, Haun 6-7, and Haun 10.0-10.2. Normalized vegetation (NDVI, GNDVI, and BNDVI) and chlorophyll indices (CRedEdge, CGreen, MCARI and MTVI2) were developed using canopy reflectance. In the rainfed field, N did not produce a yield response. In the 2003 and 2004 irrigated fields, nitrogen (133 kg ha^-1) applied at Haun 5-6 at had the greatest yield and protein response. Canopy reflectance and indices were best correlated with yield parameters at Haun 6-7 in the irrigated fields. At the Haun 6-7: 1) MTVI2 was most strongly correlated with yield and YLNS; 2) grain protein was correlated with all indices except MCARI; and 3) yield, YLNS, and grain protein were best predicted by regression models based on canopy reflectance from blue, green, and MIR bands. These findings suggest that under adequate moisture conditions in the northern mixed grass prairie ecoregion, canopy reflectance may be used to estimate in-season N applications.