Agritrop
Accueil

From plot to regional scale, spatial modelling of crop systems using interaction graphs. [P35]

Jahel Camille, Baron Christian, Vall Eric, Bégué Agnès, Dupuy Stéphane, Lo Seen Danny. 2015. From plot to regional scale, spatial modelling of crop systems using interaction graphs. [P35]. In : Building tomorrow’s research agenda and bridging the science-policy gap. CIRAD, INRA, IRD, Agropolis International, Wageningen UR, CGIAR, UCDAVIS, FAO, Agreenium, GFAR. Montpellier : CIRAD, Résumé, 124. Climate-Smart Agriculture 2015 : Global Science Conference. 3, Montpellier, France, 16 Mars 2015/18 Mars 2015.

Communication avec actes
[img]
Prévisualisation
Version publiée - Anglais
Utilisation soumise à autorisation de l'auteur ou du Cirad.
ID576747.pdf

Télécharger (421kB) | Prévisualisation

Résumé : Developing a climate-smart agriculture towards the " triple win " (food security, adaptation and mitigation) objective requires drawing-up policies that take into account the evolution of agrarian systems. To do so, it is necessary to develop tools to analyse the agricultural production trends from plot to regional scale. In developing countries, monitoring tools are facing the issue of heterogeneous and sparse information available: limited information networks, small average area of cultivated plots, fragmented plot organisation and diverse management modes. Moreover, the agrarian dynamics are the result of many processes occurring at different scales, which raises the issue of documenting the main trends without distorting the information when trying to upscale or downscale it. We propose a methodology to estimate the spatial variability and the time dynamics of agrarian systems at scales appropriate for seasonal risk monitoring and land policy planning. To do so, we use a mixed scaling approach based on the modelling of spatial dynamics which combines various information sources coming from ground networks, expert knowledge, thematic maps, crop models and remote sensing images. The novelty of the proposed approach is to use a spatial dynamics modelling language, Ocelet, based on interaction graphs: the graphs allow us to link information at different scales, and to integrate the spatial constraints and variability, central to the understanding of agrarian dynamics. The 1500 km² studied area is located in the cotton region of West Burkina Faso. This region displays high spatial climatic variability and has undergone notable transformations these last two decades due to high population growth and cultivated area reaching its saturation point. The main result presented is the simulation of the expansion of cultivated areas at the expense of forests, and also the evolution of cropping systems, taking account farmers strategies, climatic variability and spatial heterogeneities. (Texte intégral)

Classification Agris : U10 - Informatique, mathématiques et statistiques
P40 - Météorologie et climatologie
F08 - Systèmes et modes de culture
A01 - Agriculture - Considérations générales

Auteurs et affiliations

Source : Cirad-Agritrop (https://agritrop.cirad.fr/576747/)

Voir la notice (accès réservé à Agritrop) Voir la notice (accès réservé à Agritrop)

[ Page générée et mise en cache le 2024-11-08 ]