Abstract
The desertification process including natural resources degradation is a major obstacle to development in tropical and Mediterranean zones with strong drought constraints, leading to a wide range of possibly irreversible catastrophes: famine, land neglecting and migration. This process comes from a combination of different modes of resource management from different actors at different scales, interacting with strong climatic constraints in arid and semi-arid zones. In Africa and particularly in the circum-Saharian zone it is urgent to deliver useful information for decision making focused on improving the natural resource management at a local level in order to slow down the desertification process. For that purpose within the ROSELT/OSS program [1], has been developed the LEIS (Local Environmental Information System), an original tool coupling GIS and models to be able to establish a complete diagnostic of natural resource use allowing prediction of future evolutions. The aim of the LEIS is to model the functioning of an observatory territory at local scale taking into account both biophysical data and socioeconomic data together using an integrated spatial approach. Acknowledging the dynamic interactions of these two set of factors the integrated spatial approach is the core of the tool and the conceptual models derive from it. Using minimum kit dataset the modeling of the functioning establishes a diagnostic: spatial description of the uses and resources interactions into spatial references units (SRU) and quantitative estimation of vegetation pressure spatialised on these SRU. The modeling structure allows some prevision to be made when setting a scenario of evolution of parameters. The forecated diagnostics can be compared for different scenarios while succession of diagnostics in a long term monitoring helps to analyse vegetation pressure evolution and to build realistic scenarii. Before being communicated to local or national authorities, as useful information for a better evaluation of desertification risks, balances maps can then be aggregated according to administrative units or to some biophysics units depending on a specific interest. Implemented under the same GIS software platform, the LEIS tool couples a geographic database and spatialisation models. In this article we will describe especially the integrated spatial approach which is the core of the tool and the conceptual model deriving from it. Aiming at expressing the prospective potential of the tool, the spatialisation models implemented will be explained.