Timely monitoring of crop lands is important in order to make agricultural activities more
sustainable, as well as ensuring food security. The use of Earth Observation (EO) data …

Timely and accurate estimation of crop yield before harvest to allow crop yields
management decision-making at a regional scale is crucial for national food policy and …

To predict regional-scale winter wheat yield, we developed a crop model and data
assimilation framework that assimilated leaf area index (LAI) derived from Landsat TM and …

Timely and reliable in-season forecasting of crop yield is crucial for regional and national
agricultural management. To improve the winter wheat yield prediction accuracy at the …

The scale mismatch between remote sensing observations and state variables simulated by
crop growth models decreases the reliability of crop yield estimates. To overcome this …

To estimate regional-scale winter wheat (Triticum aestivum) yield, we developed a data-
assimilation scheme that assimilates remotely sensed reflectance into a coupled crop …

Crop yield estimation at regional scale using crop model is generally subjected to large
uncertainties from insufficient spatial information on heterogeneous growth environment and …

Crop growth monitoring and yield estimate information can be obtained via appropriate
metrics such as the leaf area index (LAI) and biomass. Such information is crucial for guiding …

Leaf area index (LAI) and evapotranspiration (ET) are two crucial biophysical variables
related to crop growth and grain yield. This study presents a crop model-data assimilation …

To improve the accuracy of regional winter wheat yield estimation in the Guanzhong Plain,
China, the field-measured leaf area index (LAI) and soil moisture at the depth of 0–20 cm (θ) …