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Hands-On Geospatial Analysis with R and QGIS

You're reading from   Hands-On Geospatial Analysis with R and QGIS A beginner's guide to manipulating, managing, and analyzing spatial data using R and QGIS 3.2.2

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788991674
Length 354 pages
Edition 1st Edition
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Authors (2):
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Brad Hamson Brad Hamson
Author Profile Icon Brad Hamson
Brad Hamson
Shammunul Islam Shammunul Islam
Author Profile Icon Shammunul Islam
Shammunul Islam
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Table of Contents (12) Chapters Close

Preface 1. Setting Up R and QGIS Environments for Geospatial Tasks FREE CHAPTER 2. Fundamentals of GIS Using R and QGIS 3. Creating Geospatial Data 4. Working with Geospatial Data 5. Remote Sensing Using R and QGIS 6. Point Pattern Analysis 7. Spatial Analysis 8. GRASS, Graphical Modelers, and Web Mapping 9. Classification of Remote Sensing Images 10. Landslide Susceptibility Mapping 11. Other Books You May Enjoy

Geostatistics

In geostatistics, observed variables are random, with the assumption that we observe them as outcomes of random processes. Usually, the data is observed in discrete locations of a spatially continuous regions, and we are interested in the prediction of values in non-observed locations in the given region. For example, soil salinity is measured in certain points in an area, and we are interested in predicting or interpolating soil salinity in every point under this area. Now, soil salinity in a point could depend on multiple factors: it could be due to its proximity to the saline-affected area, its spatial autocorrelation, the climate, or a random process. Other examples of geostatistical data include rainfall data, air quality, and measurements of chemical components at multiple locations in an area.

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