Land cover change prediction with a new theory of plausible and paradoxical reasoning

The spatial prediction of land cover at the field scale in winter appears useful for the issue of bare soils reduction in agricultural intensive regions. High variability of the factors that motivate the land cover changes between each winter involves integration of uncertainty in the modelling process. Fusion process with Dempster-Shafer Theory (DST) presents some limits in generating errors in decision making when the degree of conflict, between the sources of evidence that support land cover hypotheses, becomes important. This paper focuses on the application of Dezert-Smarandache Theory (DSmT) method to the fusion of multiple land-use attributes for land cover prediction purpose. Results are discussed and compared with prediction levels achieved with DST. Through this first application of the Dezert-Smarandache Theory, we show an example of this new approach ability to solve some of practical problems where the Dempster-Shafer Theory usually fails