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Spatial Autocorrelation and Spatial Filtering - Gaining Understanding Through Theory and Scientific Visualization (Paperback, Softcover reprint of hardcover 1st ed. 2003) Loot Price: R4,340
Discovery Miles 43 400
Spatial Autocorrelation and Spatial Filtering - Gaining Understanding Through Theory and Scientific Visualization (Paperback,...

Spatial Autocorrelation and Spatial Filtering - Gaining Understanding Through Theory and Scientific Visualization (Paperback, Softcover reprint of hardcover 1st ed. 2003)

Daniel A. Griffith

Series: Advances in Spatial Science

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Loot Price R4,340 Discovery Miles 43 400 | Repayment Terms: R407 pm x 12*

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Scientific visualization may be defined as the transformation of numerical scientific data into informative graphical displays. The text introduces a nonverbal model to subdisciplines that until now has mostly employed mathematical or verbal-conceptual models. The focus is on how scientific visualization can help revolutionize the manner in which the tendencies for (dis)similar numerical values to cluster together in location on a map are explored and analyzed. In doing so, the concept known as spatial autocorrelation - which characterizes these tendencies - is further demystified.

General

Imprint: Springer-Verlag
Country of origin: Germany
Series: Advances in Spatial Science
Release date: December 2010
First published: 2003
Authors: Daniel A. Griffith
Dimensions: 235 x 155 x 22mm (L x W x T)
Format: Paperback
Pages: 250
Edition: Softcover reprint of hardcover 1st ed. 2003
ISBN-13: 978-3-642-05666-6
Categories: Books > Science & Mathematics > Mathematics > Probability & statistics
Books > Professional & Technical > Environmental engineering & technology > Environmental monitoring
Books > Business & Economics > Economics > Econometrics > General
Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Geographical information systems (GIS)
Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Remote sensing
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LSN: 3-642-05666-0
Barcode: 9783642056666

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