Intelligent system to improve the sustainability of oil palm crops through the construction of forecasting maps integrating adaptive vegetation indices from multispectral aerial views.
The Oil Palm is considered by de Colombian Government as one of the main agricultural
products to promote the substitution of illegal crops and for job creation in the
countryside for a sustainable peace process evolution.
To improve the sustainability of this crop, the RSPO (Roundtable on Sustainable Palm Oil) has stablished principles to reduce the use of pesticides, fertilizers and fires, as well as fair treatment of land and workers according to local and international labor rights (Oil, 2017).
This project aims to development an intelligent system to improve the sustainability of this crop in Colombia, using a novel adaptive vegetation indices obtained from multispectral aerial views. This will be integrated into a forecasting map using Computational Intelligence concepts, to achieve international standards that support the development of oil palm crops in Colombia, both at small and medium scale.
Further to this, an additional goal of the agreement between universities and industry is the creation of a novel service to improve the sustainability of oil palm crops in a study zone based in information systems and technologies in precision agriculture, which can further be extended to improve the sustainability of this crop in other places where it is grown as an alternative to existing crops.
The role of the partners neatly complement each other. In this way, the industry partner, Unipalma of the Llanos will validate the model in a real environment. The Center for Computational Intelligence (CCI) located in De Montfort University, is the academic partner that provides advice regarding the implementation of the system and the intelligent system as a service. The EIA University will execute the field research activities related to image capture and processing, the implementation and validation of the intelligence system in a simulated and real environment.
You can see the Research Gate project Research Gate project entry.
This project is partially funded by the Royal Academy of engineering - Newton Fund
Industry Academia Partnership Programme