Topics covered in this book

The book starts with the very basics of spatial data handling (e.g., importing and exporting spatial datasets) and moves on to more practical spatial data operations (e.g., spatial data join) that are useful for research projects. Some parts of this books are still under development. Right now, Chapters 1 through 8, parts of Chapter 9, and Appendix A are available.

  • Chapter 1: Demonstrations of R as GIS
    • groundwater pumping and groundwater level
    • precision agriculture
    • land use and weather
    • corn planted acreage and railroads
    • groundwater pumping and weather
  • Chapter 2: The basics of vector data handling using sf package
    • spatial data structure in sf
    • import and export vector data
    • (re)projection of spatial datasets
    • single-layer geometrical operations (e.g., create buffers, find centroids)
    • other miscellaneous basic operations
  • Chapter 3: Spatial interactions of vector datasets
    • understand topological relations of multiple sf objects
    • spatially subset a layer based on another layer
    • extracting values from one layer to another layer
  • Chapter 4: The basics of raster data handling using the raster and terra packages
    • understand object classes by the terra and raster packages
    • import and export raster data
    • stack raster data
    • quick plotting
  • Chapter 5: Spatial interactions of vector and raster datasets
    • cropping a raster layer to the geographic extent of a vector layer
    • extracting values from a raster layer to a vector layer
  • Chapter 6: Speed things up
    • make raster data extraction faster by parallelization
  • Chapter 7: Spatiotemporal raster data handling with the stars package
  • Chapter 8: Creating Maps using the ggplot2 package
    • use the ggplot2 packages to create maps
  • Chapter 9: Download and process publicly available spatial datasets (partially available)
    • USDA NASS QuickStat (tidyUSDA) - available
    • PRISM (prism) - available
    • Daymet (daymetr) - available
    • gridMET - available
    • Cropland Data Layer (CropScapeR) - available
    • USGS (dataRetrieval) - under construction
    • Sentinel 2 (sen2r) - under construction
    • Census (tidycensus) - under construction
  • Appendix A: Loop and parallel computation (available)
  • Appendix B: Cheatsheet - under construction

As you can see above, this book does not spend any time on the very basics of GIS concepts. Before you start reading the book, you should know the followings at least (it’s not much):

  • What Geographic Coordinate System (GCS), Coordinate Reference System (CRS), and projection are (this is a good resource)
  • Distinctions between vector and raster data (this is a simple summary of the difference)

This book is about spatial data processing and does not provide detailed explanations on non-spatial R operations, assuming some basic knowledge of R. In particular, the dplyr and data.table packages are extensively used for data wrangling. For data wrangling using tidyverse (a collection of packages including dplyr), see R for Data Science. For data.table, this is a good resource.

Finally, this book does not cover spatial statistics or spatial econometrics at all. This book is about spatial data processing. Spatial analysis is something you do after you have processed spatial data.