A review of data assimilation of remote sensing and crop models

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Assimilation of remote sensing into crop growth models: Current status and perspectives (2019, result): “Different from previous data assimilation reviews (Maas, 1988; Delécolle et al., 1992; Liang, 2004; Dorigo et al., 2007; Lewis et al., 2012; Kasampalis et al., 2018; Jin et al., 2018), this review focuses on the techniques in DA and explaining what approach should be used in which circumstances and ”
High-Throughput Estimation of Crop Traits: A Review of Ground and Aerial Phenotyping Platforms (2020, background): “How to combine the outputs of these sensors to increase the estimation accuracy of crop phenotyping traits is still a challenge for crop phenotyping traits [7], [59].”
A hierarchical interannual wheat yield and grain protein prediction model using spectral vegetative indices and meteorological data (2020, background): “If these complex yield-quality-management-environment interactions are to be considered, then data assimilation methods are needed that combine the advantages of remote sensing with the physiological knowledge captured in process-oriented crop growth models (CGM) (Moulin et al., 1998; Dorigo et al.,”