A spatial Poisson Point Process to classify coconut fields on Ikonos pansharpened images - Archive ouverte HAL
Communication Dans Un Congrès Année : 2008

A spatial Poisson Point Process to classify coconut fields on Ikonos pansharpened images

Résumé

The goal of this study is to classify the coconut fields, observed on remote sensing images, according to their spatial distribution. For that purpose, we use a technique of point pattern analysis to characterize spatially a set of points. These points are obtained after a coconut trees segmentation process on Ikonos images. Coconuts' fields not following a Poisson Point Process are identified as maintained, otherwise other fields are characterized as wild. A spatial analysis is then used to establish locally the Poisson intensity and therefore to characterize the degree of wildness.
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Dates et versions

inria-00582390 , version 1 (01-04-2011)

Identifiants

Citer

Raimana Teina, Dominique Béréziat, Benoît Stoll. A spatial Poisson Point Process to classify coconut fields on Ikonos pansharpened images. SPIE Asia Pacific Remote Sensing, Nov 2008, Nouméa, New Caledonia. pp.71491E, ⟨10.1117/12.806422⟩. ⟨inria-00582390⟩
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