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Regional winter wheat yield estimation based on the WOFOST model and a novel VW-4DEnSRF assimilation algorithm (Institute of Agricultural Resources and Regional Planning; first author: Wu Shangrong; corresponding author: Chen Zhongxin) (Remote Sensing of Environment, IF 10.164, ranking 1/29)

In order to improve the accuracy of regional crop yield estimation based on data assimilation, this study proposed a novel EnSRF assimilation algorithm based on a variable time window and four-dimensional extension (VW-4DEnSRF) and constructed a new crop yield estimation system based on crop growth model and VW-4DEnSRF algorithm. This study conducted the quantitative simulation and yield estimation of regional winter wheat, which proved the feasibility and effectiveness of the proposed algorithm of the large-area crop yield simulation. The proposal of the new assimilation algorithm provides a new feasible method for large-area crop yield estimation, which is of great significance for ensuring national food security.

Ground sampling and data collection

Simulated results of dynamic change of leaf area index and yield of winter wheat by VW4DEnSRF

Major Achievements

Regional winter wheat yield estimation based on the WOFOST model and a novel VW-4DEnSRF assimilation algorithm (Institute of Agricultural Resources and Regional Planning; first author: Wu Shangrong; corresponding author: Chen Zhongxin) (Remote Sensing of Environment, IF 10.164, ranking 1/29)