Abstract: Maize stalk mulching is a conservation tillage method that has been currently promoted in northeastern China Plain. Remote sensing estimation of regional crop residue cover (CRC) can quickly obtain the information of straw mulching in a large area, which plays an important role in monitoring and popularizing the work of straw mulching. In this study, the normalized difference til-lage index (NDTI), simple tillage index (STI), normalized difference residue index (NDRI), and normalized difference index 7 (NDI7) were extracted from Sentinel-2A image and used to establish a linear regression model for CRC and spectral indices in Lishu County of Jilin Province. The results showed that soils had strong spatial heterogeneity in the study area, which would lead to a significant impact on the spectral index regression model. Using soil texture classification (zoning) to establish regression model could improve the inversion accuracy. Soil spatial heterogeneity would increase the estimation error of the model. The four spectral indices had a strong correlation with CRC, among which the NDTI and STI models performed better. The zonal linear regression model based on NDTI and STI verified that R² was 0.84 and RMSE was 13.3%, which was better than the non-zonal model (R² was 0.75 and RMSE was 16.5%) and thus effectively improved the inversion accuracy.