Caractérisation d'un parcellaire agricole : comparaison des sacs de noeuds obtenus par un chemin de Hilbert adaptatif et un graphe de voisinage

Thomas Guyet 1, 2 Sébastien da Silva 3, 4 Claire Lavigne 4 Florence Le Ber 5
2 DREAM - Diagnosing, Recommending Actions and Modelling
Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
3 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : This article focuses on the comparison of approaches for spatial patterns mining. It deals with agricultural fields, which are mined in two ways, 1) by a fractal linearization method of space which provides a sequence of fields and 2) by the construction of a neighborhood graph. These representations are then used by enumeration algorithms to extract "bags of nodes" (BoN). A BoN is a vector representing the presence or absence of node types in the sub-structures of sequences or graph. BoNs are compared to highlight the ability of the two proposed methods to characterize the neighborhood of agricultural fields. The results suggest that the linearization of space captures most of the information – except some rare elements – about the organization of agricultural fields. Thus, data mining algorithms using these linear representations can be used instead of less efficient tools such as graphs mining algorithms.
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Thomas Guyet, Sébastien da Silva, Claire Lavigne, Florence Le Ber. Caractérisation d'un parcellaire agricole : comparaison des sacs de noeuds obtenus par un chemin de Hilbert adaptatif et un graphe de voisinage. 2014, pp.13. ⟨hal-01100583⟩

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