This is the code repository for [Hands-On Geospatial Analysis with R and QGIS](packt UTM URL for the book), published by Packt.
A beginner’s guide to manipulating, managing, and analyzing spatial data using R and QGIS 3.2.2
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 covers the following exciting features:
- Install R and QGIS
- Get familiar with the basics of R programming and QGIS
- Visualize quantitative and qualitative data to create maps
- Find out the basics of raster data and how to use them in R and QGIS
- Perform geoprocessing tasks and automate them using the graphical modeler of QGIS
If you feel this book is for you, get your copy today!
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
jan_price = c(10, 20, 30)
increase = c(1, 2, 3)
mar_price = jan_price + increase
Following is what you need for this book: This book is great for geographers, environmental scientists, statisticians, and every professional who deals with spatial data. If you want to learn how to handle GIS and remote sensing data, then this book is for you. Basic knowledge of R and QGIS would be helpful but is not necessary.
With the following software and hardware list you can run all code files present in the book (Chapter 1-10).
| Chapter | Software required | OS required |
|---|---|---|
| 1-10 | R, QGIS 3.2.2, GRASS QGIS | Windows, Mac OS X, and Linux (Any) |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Shammunul Islam is a consulting spatial data scientist at the Institute of Remote Sensing, Jahangirnagar University. His guidance is being applied toward the development of an adaptation tracking mechanism for a UNDP project in Bangladesh. He has provided data science training to the executives of Shwapno, the largest retail brand in Bangladesh. Mr. Islam has developed applications for automating statistical and econometric analysis for a variety of data sources, ranging from weather stations to socio-economic surveys. He has also consulted as a statistician for a number of surveys. He completed his MA in Climate and Society from Columbia University, New York, in 2014 on a full scholarship, before which he completed an honors degree in statistics and a master's degree in development studies.
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Simply click on the link to claim your free PDF.