Analysis of methods for integrating modeling techniques and satellite multi-sensor data in decision support systems.
Nowadays Walloon agriculture, as in other European countries, is faced to several constraints. It must, in the same time, maximize its production, respect the environment, ensure a balanced regional and sustainable development but also cope with the markets globalisation. The rural society is also subjected to many pressures, most of time contradictory, requiring multidisciplinary approaches, especially the adaptation of practices based on observed changes.
In the particular case of permanent meadows and farming practices, the challenge for the agriculture of the future is to facilitate the access to decision support tools allowing the establishment of good agricultural practices at farm or territory levels. These new tools should be ideally based on efficient information management technologies including information from satellite imagery.
The development of many crop growth and development models estimating yields in a more reliable way are also part of these new technological advances. To make these systems more operational, models and satellite information should be combined with methodologies tailored to the different situations encountered in the agricultural fields, in particular in the Walloon Region.
In order to exploit the recent technical and methodological developments in the field of earth observation systems for quantitative and qualitative monitoring of crop growth, three main objectives has been defined in the MIMOSA project:
• the development of an integrated approach aiming to improve the monitoring capacity of forage areas in the Walloon Region. This approach should be based on a methodology integrating grassland growth data provided by multi-sensor remote sensing observations and multi-model estimations in the decision support systems.
• the definition of relationships, during the growing season, between remote sensing information and the crop nitrogen status and the integration of these data into the decision support system developed by the CRA-W for the management of nitrogen fertilization of potato and winter wheat in the Walloon Region.
• the identification of decision rules, in terms of fodder resources management used by farmers for the main types of grassland farms in areas Jurassic and Ardenne regions and the implementation of these decision rules in a decision support system .
1) A methodology for the integration of grassland growth data provided by a multi-sensor and multi-models in a decision support system developed by CRA-W in order to allow farmers to analyze the technico - economic and environmental consequences of their grassland management techniques.
2) The integration into a decision support system for potato and winter wheat fertilization of a series of relevant indicators estimating the nitrogen status of crops.
3) A model of decision rules used by farmers to be implemented in the decision support systems to identify fodder and feeding management strategies corresponding to the changing expectations of society with regards to agriculture.
• Environmetrics and Geomatics unit (UCL)
• Applied Biology and Agricultural Production unit(UCL)
CRAW off coordinator
Biométrie, Gestion des données et Agrométéorologie
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- CRA-W - Walloon Agricultural Research Centre