Research on Dynamic Monitoring of Grain Filling Process of Winter Wheat from Time-Series Planet Imageries

Abstract

Remote sensing has been used as an important means of monitoring crop growth, especially for the monitoring of the formation of crop yield in the middle and late growth period. The information acquisition on the yield formation period of winter wheat is of great significance for winter wheat growth monitoring, yield estimation and scientific management. Hence, the main goal of this study was to verify the possibility of monitoring the grain-filling process of winter wheat and its in-field variability using an alternative non-destructive method based on orbital remote sensing. High-resolution satellite imageries (3 m) were obtained from the PlanetScope platform for three commercial winter wheat fields in Jiangsu Province, China during the reproductive stage of the winter wheat (185–215/193–223/194–224 days after sowing (DAS)). Based on the quantitative analysis of vegetation indices (VIs) obtained from high-resolution satellite imageries and three indicators of the winter wheat grain-filling process, linear, polynomial and logistic growth models were used to establish the relationship between VIs and the three indicators. The research showed a high Pearson correlation (p < 0.001) between winter wheat maturity and most VIs. In the overall model, the remote sensing inversion of the dry thousand-grain weight has the highest accuracy and its R2 reaches more than 0.8, which is followed by fresh thousand-grain weight and water content, the accuracies of which are also considerable. The results indicated a great potential to use high-resolution satellite imageries to monitor winter wheat maturity variability in fields and subfields. In addition, the proposed method contributes to monitoring the dynamic spatio-temporality of the grain-filling progression, allowing for more accurate management strategies in regard to winter wheat.