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Spatial data mining for enhanced soil map modelling / C.J. Moran in International journal of geographical information science IJGIS, vol 16 n° 6 (september 2002)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 16 n° 6 (september 2002) . - pp 533 - 549 Titre : Spatial data mining for enhanced soil map modelling Type de document : Article/Communication Auteurs : C.J. Moran, Auteur ; E. Bui, Auteur Année de publication : 2002 Article en page(s) : pp 533 - 549 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Information géographique [Termes IGN] base de données localisées [Termes IGN] cartographie thématique [Termes IGN] classification [Termes IGN] exploration de données [Termes IGN] modèle conceptuel de données [Termes IGN] occupation du sol Résumé : (Auteur) The principle of using induction rules based on spatial environmental data to model a soil map has previously been demonstrated. Whilst the general pattern of classes of large spatial extent and those with close association with geology were delineated, small classes and the detailed spatial pattern of the map were less well rendered. Here we examine several strategies to improve the quality of the soil map models generated by rule induction. Terrain attributes that are bettersuited to landscape description at a resolution of 250m are introduced as predictors of soil type. A map sampling strategy is developed. Classification error is reduced by using boosting rather than crossvalidation to improve the model. Further, the benefit of incorporating the local spatial context for each environmental variable into the rule induction is examined. The best model was achieved by sampling in proportion to the spatial extent of the mapped classes, boosting the decision trees, and using spatial contextual information extracted from the environmental variables. Numéro de notice : A2002-194 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810210138715 En ligne : https://doi.org/10.1080/13658810210138715 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22109 [article]

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