Decision-making and Modelling with Agri-environmental data

This team works on spatial and temporal agricultural data processing methods for operational decision support for the management and characterisation of agroecosystems. The work is largely applied to the field of precision agriculture, and increasingly to digital agriculture applications.

Agricultural data is of little use if it cannot be effectively translated into a good decision. The strength and uniqueness of the DeMo team lies in its expertise in methods for processing and analysing a wide variety of agricultural data types, including the intrinsic knowledge base of the producer and in the ability to take this analysis all the way to an operational decision.

Modern agriculture is data-rich, including spatial and temporal data collected from a wide variety of platforms (satellites, drones, tractors, robots, smartphones, etc.) and available on a wide variety of agricultural and environmental factors (crop, soil, weather, etc.). The heterogeneous nature and specificity of these new data require the development of new approaches built around spatial and temporal statistics. It also requires these data to be integrated with local grower/agronomist knowledge to enable real, local, site-specific decision-making that addresses each grower's unique situation and needs. The objective of the DeMo team is to provide agricultural industry with the necessary tools to achieve this. As developments progress, the methods developed by the DeMo team are integrated into a free software platform, GeoFIS, in order to facilitate their distribution to professionals.

Historically, these new approaches have been based on geostatistics and fuzzy logic systems, and rooted in agronomy. However, with the rise of digital agriculture, machine learning and artificial intelligence approaches are becoming more accessible and it is critical that these approaches are linked to the end-user, particularly their knowledge and objectives, and the local soil and climate context. The research group is currently focusing on linking these elements.

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Figure: From data to information to producer-specific decision making. The DeMo team works on all aspects of data processing and analysis along this chain.

To support our research, the Agrotic Chair was initiated to facilitate interactions with service companies in precision agriculture and digital agriculture. This allows us to take into account the main problems and obstacles to the adoption of agri-technologies in French agriculture and to answer the research questions that arise from the problems of the sector.

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Modification date: 17 July 2023 | Publication date: 14 April 2021 | By: AD