Paperback. Condizione: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
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Aggiungi al carrelloCondizione: New.
Da: BargainBookStores, Grand Rapids, MI, U.S.A.
Condizione: New. Learning R for Geospatial Analysis (Paperback or Softback).
Lingua: Inglese
Editore: Packt Publishing - Ebooks Account, 2014
ISBN 10: 1783984368 ISBN 13: 9781783984367
Da: Anybook.com, Lincoln, Regno Unito
EUR 44,77
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Aggiungi al carrelloCondizione: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In fair condition, suitable as a study copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,850grams, ISBN:9781783984367.
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Aggiungi al carrelloCondizione: Used: Good. Occasion - Bon Etat - Learning R for geospatial analysis (2014) - Grand Format.
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
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Aggiungi al carrelloUNK. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: Majestic Books, Hounslow, Regno Unito
EUR 69,58
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Aggiungi al carrelloCondizione: New. Print on Demand 364.
Da: Biblios, Frankfurt am main, HESSE, Germania
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND 364.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
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Aggiungi al carrelloPaperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Da: moluna, Greven, Germania
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Über den AutorrnrnMichael Dorman is currently a PhD candidate at the Department of Geography and Environmental Development, Ben-Gurion University of the Negev. His research explores the response of planted pine forests to changing climate t.
Da: preigu, Osnabrück, Germania
EUR 71,45
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Learning R for Geospatial Analysis | Leverage the power of R to elegantly manage crucial geospatial analysis tasks | Michael Dorman | Taschenbuch | Kartoniert / Broschiert | Englisch | 2014 | Packt Publishing | EAN 9781783984367 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 78,94
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Leverage the power of R to elegantly manage crucial geospatial analysis tasks Key Features Write powerful R scripts to manipulate your spatial data Gain insight from spatial patterns utilizing R's advanced computation and visualization capabilities Work within a single spatial analysis environment from start to finish Book Description R is a simple, effective, and comprehensive programming language and environment that is gaining ever-increasing popularity among data analysts. This book provides you with the necessary skills to successfully carry out complete geospatial data analyses, from data import to presentation of results. Learning R for Geospatial Analysis is composed of step-by-step tutorials, starting with the language basics before proceeding to cover the main GIS operations and data types. Visualization of spatial data is vital either during the various analysis steps and/or as the final product, and this book shows you how to get the most out of R's visualization capabilities. The book culminates with examples of cutting-edge applications utilizing R's strengths as a statistical and graphical tool. What you will learn Make inferences from tables by joining, reshaping, and aggregating Familiarize yourself with the R geospatial data analysis ecosystem Prepare reproducible, publication-quality plots and maps Efficiently process numeric data, characters, and dates Reshape tabular data into the necessary form for the specific task at hand Write R scripts to automate the handling of raster and vector spatial layers Process elevation rasters and time series visualizations of satellite images Perform GIS operations such as overlays and spatial queries between layers Spatially interpolate meteorological data to produce climate maps.