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Inferring land use dynamics by semi-Markov model

Angelo Raherinirina 1, * Dominique Hervé 2 Fabien Campillo 3 
* Corresponding author
3 MODEMIC - Modelling and Optimisation of the Dynamics of Ecosystems with MICro-organisme
CRISAM - Inria Sophia Antipolis - Méditerranée , MISTEA - Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie
Abstract : We 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.
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Submitted on : Friday, January 9, 2015 - 2:49:29 PM
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  • HAL Id : hal-01100087, version 1
  • PRODINRA : 313540


Angelo Raherinirina, Dominique Hervé, Fabien Campillo. Inferring land use dynamics by semi-Markov model. 12th African Conference on Research in Computer Science and Applied Mathematics, Institut National de Recherche en Informatique et en Automatique (INRIA). Sophia Antipolis, FRA., Oct 2014, Université Gaston Berger Saint-Louis, Sénégal, Senegal. pp.1-8. ⟨hal-01100087⟩



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