COUPLING CELLULAR AUTOMATA WITH MEDALUS ASSESSMENT FOR THE DESERTIFICATION ISSUE
Alassane Koné1*, Allyx Fontaine2 and Samira El Yacoubi3
1,2UMR Espace-Dev, Université de Guyane, France
3UMR Espace-Dev, IMAGES, Université de Perpignan, France
1Email: alassane.kone@etu.univ-guyane.fr *(Corresponding author)
2Email: allyx.fontaine@univ-guyane.fr 3Email: yacoubi@univ-perp.fr
Abstract:
Desertification is one of the major problems affecting our environment in the 21st century. Indeed, it threatens more than 1.5 million people worldwide and affects a quarter of the land in less than 100 countries, it spreads over half a billion hectares per year and reduces the surface water and groundwater. Thus, according to a report by the Food and Agriculture Organisation written in 1993, the direct and visible impacts of desertification are the damage on crops, on livestock, on the electricity productivity, etc. Indirect impacts are lack of food production, poverty, social upheaval, rural exodus to cities. In this paper, our work consists in modelling the degradation process of land whose advanced level leads to the desertification. The first step consists in assessing the degradation of land with the MEDALUS model developed by the MEDALUS project of the commission of the European Union. This model assesses desertification by its sensitivity index which is the geometric mean of four quality factor indexes of soil, vegetation, climate and management (land use). This assessment method uses the major part of the parameters influencing the land degradation process. The second step is to model the land degradation process using cellular automata (CA) approach. For that purpose, the study area will be divided into a regular grid of cells. Initially, each cell has a state (desertification sensitivity index) whose evolution at each discrete time step depends on the states of its neighbours through a built transition function. As a result, this study allows to introduce a dynamical process in MEDALUS model. Indeed, from an initial configuration of an area, the model can predict its evolution over time and space according to a continuous state transition function that extend the classical CA approach and fit to the MEDALUS model parameters.
Keywords: Cellular Automata, MEDALUS model, Desertification sensitivity index.
https://doi.org/10.47412/VQGH6804
