title: Two chaotic global models for cereal crops cycles observed from satellite in northern Morocco.
abstract: The dynamics underlying cereal crops in the northern region of Morocco is investigated using a global modelling technique applied to a vegetation index time series derived from satellite measurements, namely, the normalized difference vegetation index from 1982 to 2008. Two three-dimensional chaotic global models of reduced size (14-term and 15-term models) are obtained. The model validation is performed by comparing their horizons of predictability with those provided in previous studies. The attractors produced by the two global models have a complex foliated structure-evidenced in a Poincaré section-rending a topological characterization difficult to perform. Thus, the Kaplan-Yorke dimension is estimated from the synthetic data produced by our global models. Our results suggest that cereal crops in the northern Morocco are governed by a weakly dissipative three-dimensional chaotic dynamics.
authors.affiliation: Centre d'Études Spatiales de la Biosphère, CNRS-UPS-CNES-IRD, Observatoire Midi-Pyrénées, 18 avenue Édouard Belin, 31401 Toulouse, France.
authors.forename: Sylvain
authors.initials: S
authors.lastname: Mangiarotti
authors.affiliation: Centre d'Études Spatiales de la Biosphère, CNRS-UPS-CNES-IRD, Observatoire Midi-Pyrénées, 18 avenue Édouard Belin, 31401 Toulouse, France.
authors.forename: Laurent
authors.initials: L
authors.lastname: Drapeau
authors.affiliation: Complexe de Recherche Interprofessionnel en Aérothermochimie-Normandie Université, CNRS-Université et INSA de Rouen, Campus Universitaire du Madrillet, 76801 Saint-Etienne du Rouvray cedex, France.
authors.forename: Christophe
authors.initials: C
authors.lastname: Letellier
mesh_terms: D000465:Algorithms; D018556:Crops, Agricultural / Q000254:growth & development*; D002523:Edible Grain / Q000254:growth & development*; D008962:Models, Theoretical; D009018:Morocco; D017711:Nonlinear Dynamics; D017215:Satellite Communications; D013997:Time Factors