干旱区生态环境知识资源中心(Arid): Estimation of Winter Wheat Yield in Arid and Semiarid Regions Based on Assimilated Multi-Source Sentinel Data and the CERES-Wheat Model

Arid

DOI	10.3390/s21041247
	Estimation of Winter Wheat Yield in Arid and Semiarid Regions Based on Assimilated Multi-Source Sentinel Data and the CERES-Wheat Model
	Liu, Zhengchun; Xu, Zhanjun; Bi, Rutian; Wang, Chao; He, Peng; Jing, Yaodong; Yang, Wude
通讯作者	Bi, R (corresponding author), Shanxi Agr Univ, Coll Resource & Environm, Taigu 030801, Peoples R China. ; Bi, R (corresponding author), Shanxi Agr Univ, Natl Expt Teaching Demonstrat Ctr Agr Resources &, Taigu 030801, Peoples R China.
来源期刊	SENSORS
EISSN	1424-8220
出版年	2021
卷号	21 期号:4
英文摘要	The farmland area in arid and semiarid regions accounts for about 40% of the total area of farmland in the world, and it continues to increase. It is critical for global food security to predict the crop yield in arid and semiarid regions. To improve the prediction of crop yields in arid and semiarid regions, we explored data assimilation-crop modeling strategies for estimating the yield of winter wheat under different water stress conditions across different growing areas. We incorporated leaf area index (LAI) and soil moisture derived from multi-source Sentinel data with the CERES-Wheat model using ensemble Kalman filter data assimilation. According to different water stress conditions, different data assimilation strategies were applied to estimate winter wheat yields in arid and semiarid areas. Sentinel data provided LAI and soil moisture data with higher frequency (<14 d) and higher precision, with root mean square errors (RMSE) of 0.9955 m(2) m(-2) and 0.0305 cm(3) cm(-3), respectively, for data assimilation-crop modeling. The temporal continuity of the CERES-Wheat model and the spatial continuity of the remote sensing images obtained from the Sentinel data were integrated using the assimilation method. The RMSE of LAI and soil water obtained by the assimilation method were lower than those simulated by the CERES-Wheat model, which were reduced by 0.4458 m(2) m(-2) and 0.0244 cm(3) cm(-3), respectively. Assimilation of LAI independently estimated yield with high precision and efficiency in irrigated areas for winter wheat, with RMSE and absolute relative error (ARE) of 427.57 kg ha(-1) and 6.07%, respectively. However, in rain-fed areas of winter wheat under water stress, assimilating both LAI and soil moisture achieved the highest accuracy in estimating yield (RMSE = 424.75 kg ha(-1), ARE = 9.55%) by modifying the growth and development of the canopy simultaneously and by promoting soil water balance. Sentinel data can provide high temporal and spatial resolution data for deriving LAI and soil moisture in the study area, thereby improving the estimation accuracy of the assimilation model at a regional scale. In the arid and semiarid region of the southeastern Loess Plateau, assimilation of LAI independently can obtain high-precision yield estimation of winter wheat in irrigated area, while it requires assimilating both LAI and soil moisture to achieve high-precision yield estimation in the rain-fed area.
英文关键词	multi-source Sentinel data CERES-Wheat model data assimilation water stress yield estimation
类型	Article
语种	英语
开放获取类型	gold, Green Published
收录类别	SCI-E
WOS记录号	WOS:000624659200001
WOS类目	Chemistry, Analytical ; Engineering, Electrical & Electronic ; Instruments & Instrumentation
WOS研究方向	Chemistry ; Engineering ; Instruments & Instrumentation
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/369027
作者单位	[Liu, Zhengchun; Xu, Zhanjun; Bi, Rutian; He, Peng; Jing, Yaodong] Shanxi Agr Univ, Coll Resource & Environm, Taigu 030801, Peoples R China; [Liu, Zhengchun; Xu, Zhanjun; Bi, Rutian; He, Peng; Jing, Yaodong] Shanxi Agr Univ, Natl Expt Teaching Demonstrat Ctr Agr Resources &, Taigu 030801, Peoples R China; [Wang, Chao; Jing, Yaodong; Yang, Wude] Shanxi Agr Univ, Coll Agr, Taigu 030801, Peoples R China
推荐引用方式 GB/T 7714	Liu, Zhengchun,Xu, Zhanjun,Bi, Rutian,et al. Estimation of Winter Wheat Yield in Arid and Semiarid Regions Based on Assimilated Multi-Source Sentinel Data and the CERES-Wheat Model[J],2021,21(4).
APA	Liu, Zhengchun.,Xu, Zhanjun.,Bi, Rutian.,Wang, Chao.,He, Peng.,...&Yang, Wude.(2021).Estimation of Winter Wheat Yield in Arid and Semiarid Regions Based on Assimilated Multi-Source Sentinel Data and the CERES-Wheat Model.SENSORS,21(4).
MLA	Liu, Zhengchun,et al."Estimation of Winter Wheat Yield in Arid and Semiarid Regions Based on Assimilated Multi-Source Sentinel Data and the CERES-Wheat Model".SENSORS 21.4(2021).