Développement d'un indice de vulnérabilité à l'érosion éolienne à partir d'images satellitales, dans le Bassin arachidier du Sénégal : cas de la région de Thiès

Wind erosion is an environmental issue among the most critical one in arid, semi-arid and dry sub-humid regions of the planet. Soil erosion accelerated by the wind action causes damages both locally and regionally. Locally, wind erosion decreases the soil nutrients by the mobilization of finer particles and organic matter. This mobilization is one of the causes of lost of soil fertility with lead to the drop in agricultural productivity and to the reduction of the topsoil depth. Regionally, dust storms raised by the wind have a significant impact on population health and infrastructure because of particles deposition.  In areas where soils are frequently submitted to wind aggressions, studies are urgently required in order to spatially characterize the soils according to their degree of vulnerability. Such characterization is important for many reasons, especially for administrative authorities who must decide what action to undertake in order to preserve and conserve the agricultural potentialities of soils, often with limited financial resources available. However, in some regions, as in our study area, the region of Thiès in Senegal, such studies are lacking. In fact, in regions where soil erosion is active, the studies undertaken are much localized because of their approaches (soil erosion models) which require a substantial amount of data for short intervals of time to "capture" the spatial variability of the dynamics of the factors involved in the process of wind erosion. The availability of these data at a regional level is particularly problematic in developing countries because infrastructures and resources to support continuous monitoring of environmental variables are not always available.  The approach in this research aims to fill this gap, mainly through satellite imagery and more particularly those provided by Landsat-5 and Landsat-7. Landsat images cover almost the entire optical spectrum (visible, near/mid/thermal infrared) at resolutions which allow to characterize spatially the soils, according to their vulnerability at a finer level (decametric resolution) than what is possible with satellite imagery often used in environmental studies (AVHRR images from the NOAA satellite series) with a kilometric resolution. In addition, the full archive of Landsat-5 and -7 covering more than 20 years is now easily accessible. This is an undeniable asset in order to study the dynamics of the process affecting soils vulnerability to wind erosion.   Taking into account the parameters used in wind erosion models (climate, soil, vegetation), we have identified those we can estimate from satellite imagery either directly (e.g. fractional vegetation cover) or indirectly (e.g. characterization of soils by their degree of degradation). Using Landsat images acquired during to the two seasons of the region (rainy and dry season) as well as climatic data and the existing low scale soil map of the region, we developed a database describing the environmental conditions from 1988 to 2002. These data were then considered as inputs (criteria) in an empirical model we made, by modulating the impact of each criterion (weight and score). By this model, we created maps showing the degree of vulnerability (vulnerability index) of the region by date according to Landsat image acquisition date. Several tests are done to validate the internal consistency of the model. To evaluate the dynamic of the erosion process for the period we studied, we have compared our maps.  Our principal conclusions are as follows: 1) the proposed model has a good internal consistency and is sensitive to spatial and temporal variation of the factors taken into consideration; 2) as expected, among the factors used to explain soil vulnerability, erodibility and fractional green vegetation cover are the most important; 3) these two factors present a high intra and inter-season variation so that it is difficult to bring out long term trends even if some parts of the territory (North and East) have high vulnerability indices regardless of season; 4) the diachronic analysis of vulnerability index maps shows seasonal trend because areas with low vulnerability indices are increasing in rainy season, when the surface moisture is higher and vegetation is particularly active, and significantly decrease in dry season; 5) as expected, susceptibility, or the impact of wind on vulnerability, is stronger when the wind speed is high and vulnerability is high. In areas where vulnerability is low, an increase in wind speed has less impact.  In our study we have also included a comparative analysis of some factors derived from Landsat images and from the hyperspectral sensor of the experimental satellite HYPERION. Even if spatial resolution of the images provided by both sensors is similar, the accuracy of factors extracted from the hyperspectral images is definitely higher. This is due to the spectral resolution of the sensor which permits the selection of appropriate bands with the highest level of interaction with the factor of interest. This comparative study shows that in the near future, the accessibility to this type of images will improve the calculation of the index of vulnerability by our model. For now, Landsat imagery provides very interesting information to monitor the process of soil erosion by wind.

Keyphrases: Wind erosion, Satellite imagery, Multicriteria modeling, Soils vulnerability index