Hands-On Geospatial Analysis with R and QGIS

By : Hamson, Islam

3.3 (3)

Buy this Book

Hands-On Geospatial Analysis with R and QGIS

3.3 (3)

By: Hamson, Islam

Buy this Book

Overview of this book

Managing spatial data has always been challenging and it's getting more complex as the size of data increases. Spatial data is actually big data and you need different tools and techniques to work your way around to model and create different workflows. R and QGIS have powerful features that can make this job easier. This book is your companion for applying machine learning algorithms on GIS and remote sensing data. You’ll start by gaining an understanding of the nature of spatial data and installing R and QGIS. Then, you’ll learn how to use different R packages to import, export, and visualize data, before doing the same in QGIS. Screenshots are included to ease your understanding. Moving on, you’ll learn about different aspects of managing and analyzing spatial data, before diving into advanced topics. You’ll create powerful data visualizations using ggplot2, ggmap, raster, and other packages of R. You’ll learn how to use QGIS 3.2.2 to visualize and manage (create, edit, and format) spatial data. Different types of spatial analysis are also covered using R. Finally, you’ll work with landslide data from Bangladesh to create a landslide susceptibility map using different machine learning algorithms. By reading this book, you’ll transition from being a beginner to an intermediate user of GIS and remote sensing data in no time.

Preface

Who this book is for

What this book covers

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Free Chapter

Setting Up R and QGIS Environments for Geospatial Tasks

Installing R

Basic data types and data structures in R

Looping, functions, and apply family in R

Plotting in R

Installing QGIS

Getting to know the QGIS environment

Summary

Questions

Further reading

Working with Geospatial Data

Working with vector data in R

Working with vector data in QGIS

Summary

Remote Sensing Using R and QGIS

Basics of remote sensing

Working with raster data in R

Working with raster data in QGIS

Summary

Questions

Point Pattern Analysis

Introduction to point pattern analysis

Analysis of point patterns

Summary

Spatial Analysis

Testing autocorrelation

Modeling autocorrelation

Generalized linear model

Spatial interpolation

Geostatistics

Summary

GRASS, Graphical Modelers, and Web Mapping

GRASS GIS

Web mapping

Summary

Classification of Remote Sensing Images

Classification of raster data

Supervised classification

Unsupervised classification

Summary

Landslide Susceptibility Mapping

Landslides in Bangladesh

Landslide susceptibility modeling

Summary

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Fundamentals of GIS Using R and QGIS

In this chapter, we will learn the basics of how geographic information system (GIS) data is handled in R and QGIS and we will also learn about the different facilities provided by these two software for spatial data visualization. The focus will be on understanding the basics of vector data in the light of R and QGIS. Starting with the basics of GIS, projection systems, and the loading and visualization of these data in R and QGIS, we will be covering all of these with hands-on examples. We will start with the basics of spatial (here, vector) data, which will be followed by basic vector data loading and visualization in R, and lastly cover basic vector data loading and visualization again, but this time using QGIS.

Completing this chapter, you will learn about the following topics: