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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

Summary

In this chapter, we have learned about the basics of point pattern processes, including what points, events, marks, and windows are, as well as the ppp object. Using the spatstat package of R, we have learned how to create a ppp object both with and without marks by importing a CSV file. Using density, we can easily visualize these points. After that, we saw how to use the quadrat test for checking CSR in a point pattern process. For checking clustering, we learned about three more functions: G, K, and L. We can test the null hypothesis of CSR using maximum absolute deviation and the sum of the squared distance between different simulated functions. We also learned how to use the spatialkernel package of R for spatial segregation of bivariate marked point pattern data. In the next chapter, we'll learn how to use geostatistics using different functionalities of R.

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