Inferring land use dynamics by semi-Markov model

International audienceWe propose land use dynamics models corresponding to parcels located on the edge of the forest corridor, Madagascar. We use semi-Markov chain to infer the land-use dynamics. In addition to the empirical and maximum likelihood methods, we estimate the semi-Markov kernel by a Bayesian approach. In the latter case, we use Jeffreys' non-informative prior and we approximate the posterior distribution by Monte Carlo Markov Chain (MCMC) approximation. These three estimation methods lead to three different models, two are absorbing and one is regular. We study the asymptotic behavior of these models. We have determined the time scales of the considered land-use dynamics