Instructor notes
Lesson motivation and learning objectives
This lesson is designed to introduce learners to the fundamental principles and skills for working with raster and vector geospatial data in R. It begins by introducing the structure of and simple plotting of raster data. It then covers re-projection of raster data, performing raster math, and working with multi-band raster data. After introducing raster data, the lesson moves into working with vector data. Line, point, and polygon shapefiles are included in the data. Learners will plot multiple raster and/or vector layers in a single plot, and learn how to customize plot elements such as legends and titles. They will also learn how to read data in from a csv formatted file and re-format it to a shapefile. Lastly, learners will work with multi-layered raster data set representing time series data and extract summary statistics from this data.
Lesson design
Overall comments
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As of initial release of this lesson (August 2018), the timing is set to be the same for each episode. This is very likely incorrect and will need to be updated as these lessons are taught. If you teach this lesson, please put in an issue or PR to suggest an updating timing scheme!!
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The code examples presented in each episode assume that the learners still have all of the data and packages loaded from all previous episodes in this lesson. If learners close out of their R session during the breaks or at the end of the first day, they will need to either save the workspace or reload the data and packages. Because of this, it is essential that learners save their code to a script throughout the lesson.
Intro to Raster Data in R
- Be sure to introduce the datasets that will be used in this lesson. There are many data files. It may be helpful to draw a diagram on the board showing the types of data that will be plotted and analyzed throughout the lesson.
- If the Introduction to Geospatial Concepts lesson was included in your workshop, learners will have been introduced to the GDAL library. It will be useful to make the connection back to that lesson explicitly.
- If the Introduction to R for Geospatial Data lesson was included in your workshop, learners will be familiar with the idea of packages and with most of the functions used in this lesson.
- The Dealing with Missing Data and Bad Data Values in Rasters sections have several plots showing alternative ways of displaying missing data. The code for generating these plots is not shared with the learners, as it relies on many functions they have not yet learned. For these and other plots with hidden demonstration code, show the images in the lesson page while discussing those examples.
- Be sure to draw a distinction between the DTM and the DSM files, as these two datasets will be used throughout the lesson.
Open and Plot Shapefiles in R
- Learners may have heard of the
sppackage. If it comes up, explain thatsfis a more modern update ofsp. - There is a known bug in the
geom_sf()function that leads to an intermittent error on some platforms. If you see the following error message, try to re-run your plotting command and it should work. Theggplotdevelopment team is working on fixing this bug.
Error message
Error in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : polygon edge not found
Convert from .csv to a Shapefile in R
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Concluding remarks
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Technical tips and tricks
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Leave about 30 minutes at the start of each workshop and another 15 mins at the start of each session for technical difficulties like WiFi and installing things (even if you asked students to install in advance, longer if not).
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Don’t worry about being correct or knowing the material back-to-front. Use mistakes as teaching moments: the most vital skill you can impart is how to debug and recover from unexpected errors.
Common problems
TBA - Instructors please add situations you encounter here.