Introduction to spatial data analysis in R

Abstract

R serves as an excellent open-source platform to perform various spatial analyses. With recent developments in packages that can handle large data sets in little time like sf and terra, spatial data wrangling and modeling have also become simple.

This tutorial is for R users who are familiar with basic data wrangling in R but are new to spatial analysis. We will introduce various spatial data types, and a few basic R packages used to download and analyze spatial data, such as sf and raster, using tidyverse style. Participants will learn how to transform spatial data (focusing on raster and vector data) to different projections, create buffers of different radii and extract information. We will extract points from a raster, calculate distance and area, perform spatial joins, and derive a summary of raster images. We will explore the conversion of raster to vector data and vice-versa. Finally, we will create static and interactive maps. We will also share other resources that will help participants continue their learning journey.