Time-Space Dependencies in Land-Use Successions at Agricultural Landscape Scales

El-Ghali Lazrak 1 Marc Benoît 1 Jean-Francois Mari 2
2 ORPAILLEUR - Knowledge representation, reasonning
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : The agricultural landscape can be seen as an assemblage of farm territories. The way farmers organize these territories is a time AND spatial process. Understanding how a land-use succession (LUS) in a parcel depends on LUS of the neighbouring parcels is a milestone to understand the time-spatial organization of the landscape mosaic. In this work, we analyse these time-space dependencies at agricultural landscape scales. We have performed a data mining process based on hidden Markov models (HMM) to identify spatial clusters of similar distributions of LUS in 2 neighbouring parcels, furthermore called cliques. We applied this data mining process to a land-use data set covering the period from 1996 to 2007 of a 350 km² agricultural landscape located within the Niort Plain (France). To take into account the irregular neighbour system of the parcel mosaic, we used a variable depth Hilbert-Peano scan of the area covering the landscape. Through illustrative examples of two contrasted spatial stochastic clusters, we show that considering temporal cliques gives valuable information on the neighbour system in terms of attraction between LUS.
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Communication dans un congrès
www.symposcience.org. International Conference on Integrative Landscape Modelling, Feb 2010, Montpellier, France. 2010
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Dernière modification le : jeudi 11 janvier 2018 - 06:19:54
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El-Ghali Lazrak, Marc Benoît, Jean-Francois Mari. Time-Space Dependencies in Land-Use Successions at Agricultural Landscape Scales. www.symposcience.org. International Conference on Integrative Landscape Modelling, Feb 2010, Montpellier, France. 2010. 〈inria-00482890〉

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