Research progress on crop yield prediction based on data assimilation system
Data assimilation system integrates the advantages of remote sensing data and crop growth models,providing a powerful means for real-time monitoring of agricultural production conditions.This paper,built upon a brief introduction to remote sensing methods for crop yield estimation,specifically focused on four aspects:the development of data assimilation algorithms,the application potential of multi-source remote sensing data for data assimilation,the uncertainty of data assimilation system,and the scale effects of data assimilation system.In addition,to address the current state of agricultural applications,future efforts should thoroughly explore the advantages of multi-source remote sensing data,multi-crop growth model ensembles,and data algorithms.The ultimate goal is to establish a crop yield estimation model centered around mechanism model,thereby providing robust data and technical support for the formulation of sound field management strategies,the planning of cereal industry layouts,and the establishment of import and export trade policies.
yielddata assimilation systemmulti-crop growth model ensemblesmulti-source remote sensing data
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