Field level crop yield monitoring using remote sensing data and crop growth model
Date: 2015 - 2019
Chercheur impliqué: Abdoul-Hamid MOHAMED SALLAH, doctorant, assistant
Projet de recherche: BELCAM
Financement: BELSPO
Partenaires: UCLouvain, Vito, CRA-W, INRA (France)
The main objective of the BELCAM project is to develop remote sensing methods and processing chains able to ingest crowd sourcing data provided by farmers or associated partners either on voluntary basis or through information service exchange to deliver relevant and up-to-date information at the field and district level.
The research question aims to address the change of paradigm in crop modelling. Indeed, most of the existing crop growth models have been developed in data poor contexts, referring to the ‘80s and ‘90s. The emphasis was on a mechanistic approach to reproduce the physiological processes leading to the potential yield only. This research question is to identify the mechanistic relationships between crop yield and the available EO observations and to design a new (semi) mechanistic model ingesting the remotely sensed variables or metrics.
For such a purpose we coupled high temporal and spatial resolution remote sensing data and an agrometeorological crop model, AquaCrop, to estimate crop growth, yield and total above ground dry biomass at parcel level in Belgium. The standalone AquaCrop plug-in was embedded in an R-environment to semi-automatically run field simulations.
