scholarly journals Improving Winter Wheat Yield Estimation from the CERES-Wheat Model to Assimilate Leaf Area Index with Different Assimilation Methods and Spatio-Temporal Scales

2017 ◽  
Vol 9 (3) ◽  
pp. 190 ◽  
Author(s):  
He Li ◽  
Zhongxin Chen ◽  
Gaohuan Liu ◽  
Zhiwei Jiang ◽  
Chong Huang
Keyword(s):  
Winter Wheat ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Wheat Yield ◽  
Yield Estimation ◽  
Temporal Scales ◽  
Area Index ◽  
Winter Wheat Yield ◽  
Spatio Temporal

scholarly journals Improving winter wheat yield estimation by assimilation of the leaf area index from Landsat TM and MODIS data into the WOFOST model

2015 ◽  
Vol 204 ◽  
pp. 106-121 ◽  
Author(s):  
Jianxi Huang ◽  
Liyan Tian ◽  
Shunlin Liang ◽  
Hongyuan Ma ◽  
Inbal Becker-Reshef ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Wheat Yield ◽  
Landsat Tm ◽  
Yield Estimation ◽  
Area Index ◽  
Modis Data ◽  
Winter Wheat Yield

scholarly journals Using UAV-Based SOPC Derived LAI and SAFY Model for Biomass and Yield Estimation of Winter Wheat

2020 ◽  
Vol 12 (15) ◽  
pp. 2378
Author(s):  
Yang Song ◽  
Jinfei Wang ◽  
Jiali Shang ◽  
Chunhua Liao
Keyword(s):  
Winter Wheat ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Point Cloud ◽  
Low Cost ◽  
Simple Algorithm ◽  
Yield Potential ◽  
Yield Estimation ◽  
Area Index ◽  
Cloud Data

Knowledge of sub-field yield potential is critical for guiding precision farming. The recently developed simulated observation of point cloud (SOPC) method can generate high spatial resolution winter wheat effective leaf area index (SOPC-LAIe) maps from the unmanned aerial vehicle (UAV)-based point cloud data without ground-based measurements. In this study, the SOPC-LAIe maps, for the first time, were applied to the simple algorithm for yield estimation (SAFY) to generate the sub-field biomass and yield maps. First, the dry aboveground biomass (DAM) measurements were used to determine the crop cultivar-specific parameters and simulated green leaf area index (LAI) in the SAFY model. Then, the SOPC-LAIe maps were converted to green LAI using a normalization approach. Finally, the multiple SOPC-LAIe maps were applied to the SAFY model to generate the final DAM and yield maps. The root mean square error (RMSE) between the estimated and measured yield is 88 g/m2, and the relative root mean squire error (RRMSE) is 15.2%. The pixel-based DAM and yield map generated in this study revealed clearly the within-field yield variation. This framework using the UAV-based SOPC-LAIe maps and SAFY model could be a simple and low-cost alternative for final yield estimation at the sub-field scale.

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