Estimation of Winter Wheat Yield from UAV-Based Multi-Temporal Imagery Using Crop Allometric Relationship and SAFY Model
نویسندگان
چکیده
Crop yield prediction and estimation play essential roles in the precision crop management system. The Simple Algorithm for Yield Estimation (SAFY) has been applied to Unmanned Aerial Vehicle (UAV)-based data provide high spatial winter wheat. However, this model relies on relationship between leaf weight biomass, which only considers contribution of leaves final biomass calculation. This study developed modified SAFY-height by incorporating an allometric ground-based measured height biomass. A piecewise linear regression is used establish parameters are calibrated using ground measurements. Then, UAV-based photogrammetric point cloud derived effective area index (LAIe) maps predict wheat yield. growing accumulated temperature turning points 712 °C. model, relative traditional SAFY, provided more accurate areas with LAI higher than 1.01 m2/m2. RMSE RRMSE improved 3.3% 0.5%, respectively.
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ژورنال
عنوان ژورنال: Drones
سال: 2021
ISSN: ['2504-446X']
DOI: https://doi.org/10.3390/drones5030078