Spatial Statistics and Geostatistics: Theory and Applications for Geographic Information Science and Technology

Chun, Yongwan/ Griffith, Daniel A.

ISBN 10: 1446201740 / ISBN 13: 9781446201749

Published by Sage Pubns Ltd, 2013

About this Item

1st edition. 200 pages. 10.00x7.25x0.50 inches. In Stock.

Seller Inventory # x-1446201740

Bibliographic Details

• Title: Spatial Statistics and Geostatistics: Theory and Applications for Geographic Information Science and Technology
• Publisher: Sage Pubns Ltd
• Publication Date: 2013
• Language: English
• ISBN 10: 1446201740
• ISBN 13: 9781446201749
• Binding: Paperback
• Condition: Brand New
• Weight: 0.33 kilograms

About this title

Synopsis

"Ideal for anyone who wishes to gain a practical understanding of spatial statistics and geostatistics. Difficult concepts are well explained and supported by excellent examples in R code, allowing readers to see how each of the methods is implemented in practice"
- Professor Tao Cheng, University College London

Focusing specifically on spatial statistics and including components for ArcGIS, R, SAS and WinBUGS, this book illustrates the use of basic spatial statistics and geostatistics, as well as the spatial filtering techniques used in all relevant programs and software. It explains and demonstrates techniques in:

• spatial sampling
• spatial autocorrelation
• local statistics
• spatial interpolation in two-dimensions
• advanced topics including Bayesian methods, Monte Carlo simulation, error and uncertainty.

It is a systematic overview of the fundamental spatial statistical methods used by applied researchers in geography, environmental science, health and epidemiology, population and demography, and planning.

A companion website includes digital R code for implementing the analyses in specific chapters and relevant data sets to run the R codes.

From the Back Cover

The definitive text on spatial statistics, from two key figures in the field. A systematic overview of everything an upper level student or researcher needs to know about spatial statistical and geostatistical methods.