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Spatial variability in classification accuracy of agricultural crops in the Dutch national land-cover database / A.J.W. Van Oort in International journal of geographical information science IJGIS, vol 18 n° 6 (october 2004)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 18 n° 6 (october 2004) . - pp 611 - 626 Titre : Spatial variability in classification accuracy of agricultural crops in the Dutch national land-cover database Type de document : Article/Communication Auteurs : A.J.W. Van Oort, Auteur ; Arnold K. Bregt, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 611 - 626 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie numérique [Termes IGN] base de données d'occupation du sol [Termes IGN] base de données localisées [Termes IGN] classe d'objets [Termes IGN] cultures [Termes IGN] données maillées [Termes IGN] occupation du sol [Termes IGN] Pays-Bas [Termes IGN] paysage [Termes IGN] pixel [Termes IGN] précision de la classification Résumé : (Auteur) Variability in per cell classification accuracy is predominantly modelled with landcover class as the explanatory variable, i.e. with users' accuracies from the error matrix. Logistic regression models were developed to include other explanatory variables: heterogeneity in the 3 x 3 window around a cell, the size of the patch and the complexity of the landscape in which a cell is located. It was found that per cell, the probability of correct classification was significantly (a = 0.05) higher for cells with a less heterogeneous neighbourhood, for cells part of larger patches and for cells in regions with a less heterogeneous landscape. To validate the models, a leave-one-out procedure was applied in which the absolute difference between the actual and the model-estimated number of cells correctly classified was summarized over 55 regions in the Netherlands. The sum of differences reduced from 60.9 to 48.1 after adding the variables 'patch size' and 'landscape dominance' to the land-cover class model. Spatial variability thus modelled therefore led to a substantial improvement in the estimation of the per cell classification accuracy. Numéro de notice : A2004-353 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810410001701969 En ligne : https://doi.org/10.1080/13658810410001701969 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26880 [article]

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