Intro to Geospatial with R

...actually, with R but powered by Quarto

Why R or Quarto ?

"If the only tool you have is a hammer, it is tempting to treat everything as if it were a nail" (Abraham Maslow, 1966)

• The idea here is to add more tools to your toolbox

• Some tasks can be done much more efficiently using one tool or the other

• R is useful for much more stuff than statistical computing, e.g., for geospatial and for data science - from data mining, cleaning/wrangling, exploration, ML, to visualization

• R was designed to handle tabular data (by the way, geospatial data is also tabular!)

• RStudio IDE is ever evolving (and it's free!), but what's an IDE ?

• Quarto is where you bring R, Python, and even Jupyter notebooks all together

• Quarto makes reproducible analysis easy, e.g., enables you to weave together content and executable code into a finished document (as a html, or a presentation, or pdf, or even a Shiny app)

Objective for this tutorial

• Show you how to setup your R / Quarto environment so that it's ready to go when you need it

• Show you some useful packages (i.e., libraries)

• Show you some basic codes and some spatial stuff that R does nicely

• Show you how to find the help you need

Let's get started

• Install R and RStudio

• If you run on Win, it's good to install RTools

• Install Quarto

• Use Git to have version control (see here for some quick instructions or here for some more detail)

• Create a new Rproj

• Create a new Quarto document

• Welcome to tidyverse and the %>% (i.e., pipe operator)

• Get familiar with RStudio, e.g., Help > Cheat Sheets as well as the Help > Keyboard Shortcuts Help

On this tutorial

• Load different data formats into spatial objects

• Skim quickly through your data

• Manipulate data's attribute table

• Spatial join two polygon shapefiles

• Merge but faster

• Rasterize but faster

• Iterate your stuff

• Manipulate NetCDF