Before you start

The primary objective of this chapter is to showcase the power of R as GIS through demonstrations using mock-up econometric research projects7. Each project consists of a project overview (objective, datasets used, econometric model, and GIS tasks involved) and demonstration. This is really NOT a place you learn the nuts and bolts of how R does spatial operations. Indeed, we intentionally do not explain all the details of how the R codes work. We reiterate that the main purpose of the demonstrations is to get you a better idea of how R can be used to process spatial data to help your research projects involving spatial datasets. Finally, note that these mock-up projects use extremely simple econometric models that completely lacks careful thoughts you would need in real research projects. So, don’t waste your time judging the econometric models, and just focus on GIS tasks. If you are not familiar with html documents generated by rmarkdown, you might benefit from reading the conventions of the book in the Preface. Finally, for those who are interested in replicating the demonstrations, directions for replication are provided below. However, I would suggest focusing on the narratives for the first time around, learn the nuts and bolts of spatial operations from Chapters 2 through 5, and then come back to replicate them.

Target Audience

The target audience of this chapter is those who are not very familiar with R as GIS. Knowledge of R certainly helps. But, I tried to write in a way that R beginners can still understand the power of R as GIS8. Do not get bogged down by all the complex-looking R codes. Just focus on the narratives and figures to get a sense of what R can do.

Direction for replication

Datasets

Running the codes in this chapter involves reading datasets from a disk. All the datasets that will be imported are available here. In this chapter, the path to files is set relative to my own working directory (which is hidden). To run the codes without having to mess with paths to the files, follow these steps:9

  • set a folder (any folder) as the working directory using setwd()
  • create a folder called “Data” inside the folder designated as the working directory
  • download the pertinent datasets from here
  • place all the files in the downloaded folder in the “Data” folder

  1. Note that this lecture does not deal with spatial econometrics at all. This lecture is about spatial data processing, not spatial econometrics. This is a great resource for spatial econometrics in R.↩︎

  2. I welcome any suggestions to improve the reading experience of inexperienced R users.↩︎

  3. I thought about using the here package, but I found it a bit confusing for inexperienced R users.↩︎