TY  - JOUR
VL  - 102
N2  - To estimate regional-scale winter wheat (Triticum aestivum) yield, we developed a data-assimilation scheme that assimilates remotely sensed reflectance into a coupled crop growth?radiative transfer model. We generated a time series of 8-day, 30-m-resolution synthetic Kalman Smoothed reflectance by combining MODIS surface reflectance products with Landsat surface reflectance using a KS algorithm. We evaluated the assimilation performance using datasets with different spatial and temporal scales (e.g., three dates for the 30-m Landsat reflectance, 8-day and 1-km MODIS surface reflectance, and 8-day and 30-m synthetic KS reflectance) into the coupled WOFOST?PROSAIL model. Then we constructed a four-dimensional variational data assimilation (4DVar) cost function to account for differences between the observed and simulated reflectance. We used the shuffled complex evolution?University of Arizona (SCE-UA) algorithm to minimize the 4DVar cost function and optimize important input parameters of the coupled model. The optimized parameters were used to drive WOFOST and estimate county-level winter wheat yield in a region of China. By assimilating the synthetic KS reflectance data, we achieved the most accurate yield estimates (R2?=?0.44, 0.39, and 0.30; RMSE?=?598, 1288, and 595?kg/ha for 2009, 2013, and 2014, respectively), followed by Landsat reflectance (R2?=?0.21, 0.22, and 0.33; RMSE?=?915, 1422, and 637?kg/ha for 2009, 2013, and 2014, respectively) and MODIS reflectance (R2?=?0.49, 0.05, and 0.22; RMSE?=?1136, 1468, and 700?kg/ha for 2009, 2013, and 2014, respectively) at the county level. Thus, our method improves the reliability of regional-scale crop yield estimates.
JF  - European Journal of Agronomy
EP  - 13
AV  - public
ID  - discovery10066675
SN  - 1873-7331
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
TI  - Evaluation of regional estimates of winter wheat yield by assimilating three remotely sensed reflectance datasets into the coupled WOFOST-PROSAIL model
KW  - WOFOST
KW  -  PROSAIL
KW  -  Canopy reflectance
KW  -  Data assimilation
KW  -  Winter wheat yield estimation
SP  - 1
UR  - https://doi.org/10.1016/j.eja.2018.10.008
Y1  - 2019/01//
A1  - Huang, J
A1  - Ma, H
A1  - Sedano, F
A1  - Lewis, P
A1  - Liang, S
A1  - Wu, Q
A1  - Su, W
A1  - Zhang, X
A1  - Zhu, D
PB  - ELSEVIER SCIENCE BV
ER  -