Assimilation of remotely sensed soil moisture and vegetation with a crop simulation model for maize yield prediction
To improve the prediction of crop yields at an aggregate scale, we developed a data assimilation-crop modeling framework that incorporates remotely sensed soil moisture and leaf area index (LAI) into a crop model using sequential data assimilation. The core of the framework is an Ensemble Kalman Fil...
| Autores principales: | , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2013
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/33838 |
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