Last updated: 2018-09-05

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👋 Hello and welcome

me: Dr Anna Krystalli

  • Research Software Engineer, University of Sheffield
    • twitter @annakrystalli
    • github @annakrystalli
    • email a.krystalli[at]sheffield.ac.uk
  • Not a GIS expert! but
    • have used a lot of GIS in my work
    • ❤️ GIS in R!

Workshop materials

Data

On github: https://github.com/annakrystalli/gis-workshop + click on Clone or download + click on Download ZIP + Unzip the file

Workshop approach

Rstudio

We will be working in an Rstudio project. I recommend this workflow for all your projects because it keeps your work portable and self contained

We will also be using Rmd notebooks. I like them because you can see the outputs of code as you write. You can also make notes around your code using markdown. See further resources for more details.

Live coding

The majority of the workshop I will be live coding 😨 so that you can follow along. You will get a lot more out of the workshop if you do.

Workshop aims and objectives

  • Understand the basics of GIS
  • Understand spatial data types and formats
  • Be able to work with, manipulate, combine and extract spatial data in R
  • Be able to plot spatial

Why GIS in R

  1. It’s free
  2. It’s powerful especially in terms of spatial analysis and statistics
  3. It’s a scripted language so encourages reusable, reproducible workflows
  4. Recent additions to the R geospatial ecosystem (in particular package sf) have drastically simplified spatial data classes and workflows.

Let’s dive in!

Session information

sessionInfo()
R version 3.4.4 (2018-03-15)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.3

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.18      rstudioapi_0.7    knitr_1.20       
 [4] whisker_0.3-2     magrittr_1.5      workflowr_1.0.1  
 [7] rlang_0.2.1       stringr_1.3.1     tools_3.4.4      
[10] R.oo_1.21.0       git2r_0.21.0      htmltools_0.3.6  
[13] yaml_2.1.19       rprojroot_1.3-2   digest_0.6.15    
[16] assertthat_0.2.0  crayon_1.3.4      purrr_0.2.5      
[19] R.utils_2.6.0     glue_1.2.0.9000   evaluate_0.11    
[22] rmarkdown_1.10    emo_0.0.0.9000    stringi_1.2.4    
[25] compiler_3.4.4    backports_1.1.2   R.methodsS3_1.7.1
[28] lubridate_1.7.4

This reproducible R Markdown analysis was created with workflowr 1.0.1