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Résumé

Cet ouvrage est issu de l'atelier organisé par le GDR Cassini. Il présente les contributions originales d'une vingtaine de spécialistes mondiaux de la qualité dans l'information géographique

Sommaire

Error propagation in spatial analysis for the evaluation of the traffic noise - Mounir Azouzi A fuzzy constraint approach for handling uncertainty in regional soil maps - D. Cazemier, P. Lagacherie and R. Martin-Clouaire The propagation of boundary uncertainty from maps to models - Geoffrey Edwards, Michelle Fortin, Keith P.B. Thomson, Eric Aubert and Kim E. Lowell Applying Data Mining Techniques to Generate Quality Information from Geographical Databases - Sami Faiz, Karim Abbassi, Patrice Boursier Improving Error Models for Digital Elevation Models - Peter Fisher Metamodels for data quality description - Andrew U. Frank Building a geospatial data framework - finding the best available data - Stephen C. Guptill Quality needs more than Standards - Francis Harvey Geometric Quality Issues In Cadastral Map Renovation - Martin Salzmann and Auke Hoekstra Using spatial constraints as redundancy information to improve geographical knowledge - Robert Jeansoulin A 3-Part Approach to Geographic Data Quality Assurance - David Lanter Using GIS-Based Sensitivity Analysis to Study the Affects of Data Quality and Model Specification on Environmental Decision-Making - Susanna McMaster The fuzzy spatial extent of objects identified with remote sensing and photointerpretation - Martien Molenaar Spatial Database Inconsistency Checking and Correcting - A. Puricelli, S. Servigne, T. Ubeda, R. Laurini Statistical representation of relative positional uncertaintly for geographical linear features - François Vauglin Activating Scale-based Uncertainty in Digital Elevation Models - Joseph Wood Is there still a need to improve address quality ? - António Morais Arnaud

Caractéristiques

Editeur : Hermes Science

Auteur(s) : Michael GOODCHILD, Robert Jeansoulin

Publication : 15 décembre 1997

Edition : 1ère édition

Intérieur : Couleur, Noir & blanc

Support(s) : eBook [PDF], Contenu téléchargeable [PDF], Text (eye-readable) [PDF]

Contenu(s) : PDF

Protection(s) : Marquage social (PDF)

Taille(s) : 9,9 Mo (PDF), 15 Mo (PDF)

Langue(s) : Français

Code(s) CLIL : 3080, 3051

EAN13 eBook [PDF] : 9782746233416

EAN13 (papier) : 9782866016579