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Time-series crop growth monitoring at field scales is very important for crop management and yield estimation. However, the spatial resolutions (250~1000 m) of current satellite sensors with high temporal resolutions are too coarse for areas with complex and diverse land-use types, such as the Guanzhong Plain of Shaanxi Province, which causes great uncertainties in crop yield estimation results. To estimate the winter wheat yield at field scales, a study was carried out on the Guanzhong Plain. The enhanced deep convolutional spatiotemporal fusion network (EDCSTFN) model and enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) were used to fuse the leaf area index (LAI) retrieved from Sentinel-1, Sentinel-2 and Sentinel-3 imagery, thereby reconstructing the LAI imagery with a 20m spatial resolution at 12 day interval. Finally, the reconstructed LAI imagery were used for the winter wheat yield estimation at field scales. The results showed that the LAI imagery with a 20m spatial resolution in the winter wheat planting area of Guanzhong Plain can be accurately retrieved based on the backscatter coefficient and coherence derived from Sentinel-1 data, and the coefficient of determination (R2) in March and April were larger than 0.70. Compared with the ESTARFM and EDCSTFN models based on Sentinel-2 and Sentinel-3 (EDCSTFN_S3), the EDCSTFN model based on Sentinel-1 and Sentinel-2 (EDCSTFN_S1) can significantly improve the accuracy of LAI spatiotemporal fusion results on the dates far from the reference dates (R2 values for ESTARFM, EDCSTFN_S3 and EDCSTFN_S1 model in late May were 0.53, 0.71 and 0.76, respectively). The winter wheat yield estimation results based on the spatiotemporal fused LAI had a good correlation with the winter wheat yield data (R2=0.52, P<0.01), the root mean square error of the yield estimation results was 358.25kg/hm2, the normalized root mean square error was 19% and the average relative error was 7.34%. In addition, the yield estimation results showed more spatial distribution details of winter wheat yield at field scales, thereby indicating the potential for accurate winter wheat yield estimation at field scales.