D2.3 Report on Alternative and improved data assimilation and estimation methods

Birger Andersen, Bhupjit Singh, Maryamsadat Tahavori, Tomasz Blaszczyk, Per Lynggaard, Emma Gaitán Fernández

Research output: Book/ReportReportCommissioned


This report discusses improvements to the software and hardware system developed throughout the last year of the project. A data validation framework was developed to be able to precisely validate sensor data and data from other sources before using them in simulation process.
To improve N‐content prediction for a whole season, a seasonal weather forecast was developed, that is able to forecast temperature and precipitation up to 6 months ahead. Estimation of LAI (Leave Area Index) values from RGB (Red Green Blue coded) drone images was explored and concluded to be a possible inexpensive alternative to use Sentinel satellite images as the source.
Finally, an improved soil moisture sensor has been explored and evaluated. It is able to deliver more precise results than traditional inexpensive capacitive soil moisture sensors.
Original languageEnglish
Number of pages146
Publication statusPublished - 2021


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