1.

Record Nr.

UNINA990003286750403321

Autore

Vanni, Manfredo <1890-1976>

Titolo

Panama : Condizioni Naturali ed Economiche / Manfredo Vanni

Pubbl/distr/stampa

Roma : Fratelli Treves, [192.]

Descrizione fisica

148 p., [6] c. : ill. ; 24 cm

Collana

Pubblicazioni dell'Istituto Cristoforo Colombo ; 34

Disciplina

021.042

Locazione

DECGE

ILFGE

Collocazione

021.042.PAN

K-05-009

Lingua di pubblicazione

Italiano

Formato

Materiale a stampa

Livello bibliografico

Monografia



2.

Record Nr.

UNINA9910139505003321

Titolo

Advanced mapping of environmental data [[electronic resource] ] : geostatistics, machine learning, and Bayesian maximum entropy / / edited by Mikhail Kanevski

Pubbl/distr/stampa

London, : ISTE

Hoboken, N.J., : Wiley, 2008

ISBN

9780470611463 (e-book)

9781848210608 (hbk.)

Descrizione fisica

1 online resource (xiii, 313 p.) : ill

Collana

ISTE ; ; v.62

Altri autori (Persone)

KanevskiMikhail

Disciplina

550.1519542

Soggetti

Geology - Statistical methods

Machine learning

Bayesian statistical decision theory

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Chapter 1. Advanced Mapping of Environmental Data: Introduction -- Chapter 2. Environmental Monitoring Network Characterization and Clustering -- Chapter 3. Geostatistics: Spatial Predictions and Simulations -- Chapter 4. Spatial Data Analysis and Mapping Using Machine Learning Algorithms -- Chapter 5. Advanced Mapping of Environmental Spatial Data: Case Studies -- Chapter 6. Bayesian Maximum Entropy – BME -- Index.

Sommario/riassunto

This book combines geostatistics and global mapping systems to present an up-to-the-minute study of environmental data. Featuring numerous case studies, the reference covers model dependent (geostatistics) and data driven (machine learning algorithms) analysis techniques such as risk mapping, conditional stochastic simulations, descriptions of spatial uncertainty and variability, artificial neural networks (ANN) for spatial data, Bayesian maximum entropy (BME), and more.