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Couverture
 
Analysis and modelling of spatial environmental data
Auteur(s): Mikhail Kanevski, Michel Maignan
Domaine(s): Environmental Sciences
Collection: EPFL-Press  
Table des matières
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Informations
ISBN: 2-940222-02-9
2004, 304 pages, 207 fig., CD-included, hardcover.
 
Prix pour la Suisse:
113.00 CHF
Commander
Prix à l'exportation:
78.80 euros

This book describes the fundamental methodological aspects for the analysis of spatially distributed data and the steps and instructions to follow for an effective case study. It relates mainly the software " Geostat Office " which has been developed by the author’s team since several years, and also to newly available softwares for advanced geostatistics which were most recently completed, like Winfaik, Multigeo, Baykrig and SVM-CTI. The book is intended for users, so to enable the scientists who face the problem of pollution cartography to solve step by step, following the different modules, the problems which arise when completing spatial data analysis. Several case studies are presented in order to guide the practitioners while tackling real problems with distribution of heavy metals, of radionuclides, and of radon in the soil. In order to avoid incorrect applications, a rigorous presentation of methodology and theory is first presented in each chapter, before showing how it applies to the real phenomenon.

::This book may be ordered by customers located in Switzerland, France,
Belgium and North Africa only. For other countries, please contact
Dekker Ltd. at www.dekker.com::
The book consists in a paper-text (analysis of network monitoring, geostatistical method and the most advanced effective application of Artificial Neural Networks for mapping) and in a CD-ROM (paper-text in pdf format, with coloured display of all maps and graphs, “Geostat Office” software for Ms-Windows and user’s manual).
The book used with Geostat Office is useful for teaching as a tutorial text as well as for modelling real case studies.
Introduction to environmental data analysis and modelling - Exploratory spatial data analysis. Analysis of monitoring networks. Declustering - Spatial data analysis: deterministic interpolations - Introduction to Geostatistics. Variography - Geostatistical spatial predictions - Estimation of local probability density functions - Conditional stochastic simulations - Artificial neural networks and spatial data analysis - Support Vector Machines for environmental spatial data - Geographical Information Systems and spatial data analysis - Conclusions - Glossaries - References.
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