Abstract: Abstract: Remote sensing of crop residue cover is very important because of its significance in agricultural production. Hyperion, Aster, and Landsat-5 TM sensors have been successfully used to estimate crop residue cover. However, Hyperion has extended its active duty, almost no good SWIR data of Aster that are useful for identification of crop residue have been acquired since May 2008, and Landsat-5 TM was officially decommissioned on June 5, 2013. Therefore, it is significant to evaluate the performance of Landsat-8 OLI for predicting crop residue cover, which is the latest member of Landsat series and has several advantages over Landsat-5 TM such as the fine spectral resolution. The study was conducted in Fengqiu, which was an area of conservation tillage., the spectra with varying wheat residue covers on the soil surface were measured by using an ASD spectroradiometer (FieldSpec 4 Hi-Res). The measured spectra were used to simulate the corresponding bands of Landsat-8 OLI, Landsat-5 TM, Aster, and Hyperion, which were then employed to construct spectral indices. The potential of Landsat-8 OLI in the prediction of crop residue cover was evaluated by comparing the correlation coefficients between the wheat residue cover and the simulated band reflectance and spectral indices. Moreover, we used the spectral indices to build the calibration models, which were then validated using the measured values of wheat residue cover. Correlation coefficients between the wheat residue cover and the band reflectance of Landsat-8 OLI and Landsat-5 TM were higher in the shortwave infrared region (1 200～2 400 nm), which should be caused by the fact that wheat residue presents a broad absorption feature near 2100 nm associated with cellulose-lignin. Correlation coefficients between the wheat residue cover and the spectral indices using the Landsat-8 OLI1 band (NDIOLI21, NDIOLI31, and NDIOLI41) were better than those for all spectral indices derived from Landsat-5 TM. The correlation coefficient for NDIOLI21 was highest among all indices derived from Landsat-8 OLI (r=0.78, P<0.01), whereas it was lower than that acquired from SINDRI (r=0.88, P<0.01), LCA (r=0.85, P<0.01) or CAI (r=0.85, P<0.01). NDIOLI42, NDIOLI52, NDIOLI53, NDIOLI54, and BIOLI were better in estimating the wheat residue cover than the corresponding spectral indices derived from Landsat-5 TM; NDIOLI21, NDIOLI31, NDIOLI41, and NDIOLI51 were better than all of the spectral indices from Landsat-5 TM; NDIOLI21 was the best index in estimating the wheat residue cover among all indices derived from Landsat-8 OLI and Landsat-5 TM (R2=0.60, RMSE=9.56%, MRE=9.83%), while it was slightly lower than SINDRI (R2=0.75, RMSE=7.98%, MRE=7.82%), LCA (R2=0.67, RMSE=8.85%, MRE=8.54%), or CAI (R2=0.72, RMSE=8.35%, MRE=8.16%). These results indicate that Landsat-8 OLI is able to effectively estimate wheat residue cover, which will have good application prospects in the prediction of crop residue cover.