Book Image

Hands-On Geospatial Analysis with R and QGIS

By : Shammunul Islam, Brad Hamson
Book Image

Hands-On Geospatial Analysis with R and QGIS

By: Shammunul Islam, Brad Hamson

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.
Table of Contents (12 chapters)
GRASS, Graphical Modelers, and Web Mapping

Landslides in Bangladesh

Bangladesh is prone to different types of geological, hydrological, and meteorological hazards – landslides are just one of them. Landslides mainly occur in the southeastern part of Bangladesh, which is also called the Chittagong Hill Tracts (CHT). Landslides mainly occur in monsoon time, and are primarily due to factors such as cutting hills, high slopes, certain degrees of elevation from the sea level, and slope saturation. As people also live in these hilly areas, landslides can be incredibly deadly, as was the case in 2017, when many people died due to multiple landslide events. As such, it is important that we have the ability to model and predict the highly susceptible zones so that lives can be saved and injuries can be prevented.

The Institute of Remote Sensing, Jahangirnagar University (IRS-JU), arranged a field trip to the CHT in November...