Advanced mapping of environmental data : geostatistics, machine learning and Bayesian maximum entropy / edited by Mikhail Kanevski.

Contributor(s): Kanevski, Mikhail
Language: English Series: Geographical information systems series: Publisher: Hoboken, N. J. : Wiley-ISTE 2008Description: xiii, 313 pages : illustrations, maps ; 24 cmContent type: text Media type: computer Carrier type: online resourceISBN: 9781848210608; 1848210604Subject(s): Geology -- Statistical methods | Machine learning | Bayesian statistical decision theoryGenre/Form: Electronic books.DDC classification: 550.1/519542 LOC classification: QE33.2.S82 | A35 2008Online resources: Full text available at Wiley Online Library Click here to view.
Contents:
Advanced mapping of environmental data: introduction / M. Kanevski -- Environmental monitoring network characterization and clustering / D. Tuia and M. Kanevski -- Geostatistics: spatial predictions and simulations / E. Savelieva, V. Demyanov and M. Maignan -- Spatial data analysis and mapping using machine learning algorithms / F. Ratle [and others] -- Advanced mapping of environmental spatial data: case studies / L. Foresti [and others] -- Bayesian maximum entropy -- BME / G. Christakos.
Review: "This title, brings together three topics normally covered separately: geostatistical methods and models, machine learning algorithms and the Bayesian maximum entropy approach. An introduction to environmental data mapping is provided before these areas, their features and applications are discussed in more depth. The approach is designed to assist the reader in easily expanding their knowledge of the fields covered, and will be useful for both students and professionals involved in environmental data analysis and mapping."--BOOK JACKET.
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Includes bibliographical references and index.

Advanced mapping of environmental data: introduction / M. Kanevski -- Environmental monitoring network characterization and clustering / D. Tuia and M. Kanevski -- Geostatistics: spatial predictions and simulations / E. Savelieva, V. Demyanov and M. Maignan -- Spatial data analysis and mapping using machine learning algorithms / F. Ratle [and others] -- Advanced mapping of environmental spatial data: case studies / L. Foresti [and others] -- Bayesian maximum entropy -- BME / G. Christakos.

"This title, brings together three topics normally covered separately: geostatistical methods and models, machine learning algorithms and the Bayesian maximum entropy approach. An introduction to environmental data mapping is provided before these areas, their features and applications are discussed in more depth. The approach is designed to assist the reader in easily expanding their knowledge of the fields covered, and will be useful for both students and professionals involved in environmental data analysis and mapping."--BOOK JACKET.

Mikhail Kanevski, Institute of Geomatics and Analysis of Risk, University of Lausanne, Switzerland.

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