Crop Yield Estimation at Field Scales by Assimilating Time Series of Sentinel-2 Data Into a Modified CASA-WOFOST Coupled Model

Rapidly and accurately estimating yields at field scales are very significant. Each type of currently yield estimation model has been well studied, yet all them have certain limitations. Based on a coupled Carnegie-Ames-Stanford approach (CASA)-World Food Studies (WOFOST) time series Sentinel-2 imagery, we achieved daily crop simulations estimations two adjacent farms in China. The results indicated that the inherited high computing speed light use efficiency (LUE) models mechanistic advantages growth models. ${R}^{2}$ simulation was 0.64 for CASA model, 0.84 0.86 WOFOST root mean square error (RMSE) values were 948.32, 792.11, 623.64 kg/ha, respectively. operating times CASA-WOFOST over growing season wheat 37 min, 48 1 day 5 h 7 Compared with provided much faster running similar accuracy; therefore, proposed can be applied assessments large high-spatial-resolution images to obtain accurate simulations. higher accuracy mountainous areas regions uneven terrain. It concluded improve precision, reliability, stability estimation; provide theoretical support scales; promote development precision agriculture.