References – Introduction to Geospatial Raster and Vector Data with R

Key Points

Intro to Raster Data	The GeoTIFF file format includes metadata about the raster data. To plot raster data with the `ggplot2` package, we need to convert it to a dataframe. Be careful when dealing with missing or bad data values.
Plot Raster Data	Continuous data ranges can be grouped into categories using `mutate()` and `cut()`. Use built-in `terrain.colors()` or set your preferred color scheme manually. Layer rasters on top of one another by using the `alpha` aesthetic.
Reproject Raster Data	In order to plot two raster data sets together, they must be in the same CRS. Use the `projectRaster()` function to convert between CRSs.
Raster Calculations	Rasters can be computed on using mathematical functions. The `overlay()` function provides an efficient way to do raster math. The `writeRaster()` function can be used to write raster data to a file.
Work With Multi-Band Rasters	A single raster file can contain multiple bands or layers. Use the `stack()` function to load all bands in a multi-layer raster file into R. Individual bands within a stack can be accessed, analyzed, and visualized using the same functions as single bands.
Open and Plot Shapefiles	Shapefile metadata include geometry type, CRS, and extent. Load spatial objects into R with the `st_read()` function. Spatial objects can be plotted directly with `ggplot` using the `geom_sf()` function. No need to convert to a dataframe.
Explore and Plot by Vector Layer Attributes	Spatial objects in `sf` are similar to standard data frames and can be manipulated using the same functions. Almost any feature of a plot can be customized using the various functions and options in the `ggplot2` package.
Plot Multiple Shapefiles	Use the `+` operator to add multiple layers to a ggplot. Multi-layered plots can combine raster and vector datasets. Use the `show.legend` argument to set legend symbol types. Use the `scale_fill_manual()` function to set legend colors.
Handling Spatial Projection & CRS	`ggplot2` automatically converts all objects in a plot to the same CRS. Still be aware of the CRS and extent for each object.
Convert from .csv to a Shapefile	Know the projection (if any) of your point data prior to converting to a spatial object. Convert a data frame to an `sf` object using the `st_as_sf()` function. Export an `sf` object as text using the `st_write()` function.
Manipulate Raster Data	Use the `crop()` function to crop a raster object. Use the `extract()` function to extract pixels from a raster object that fall within a particular extent boundary. Use the `extent()` function to define an extent.
Raster Time Series Data	Use the `list.files()` function to get a list of filenames matching a specific pattern. Use the `facet_wrap()` function to create multi-paneled plots with `ggplot2`. Use the `as.Date()` function to convert data to date format.
Create Publication-quality Graphics	Use the `theme_void()` function for a clean background to your plot. Use the `element_text()` function to adjust text size, font, and position. Use the `brewer.pal()` function to create a custom color palette. Use `cowplot` to create paneled figures. Use the `ggsave()` function to save our masterpiece.
Derive Values from Raster Time Series	Use the `cellStats()` function to calculate summary statistics for cells in a raster object. The pipe (`\|`) operator means `or`. Use the `rbind()` function to combine data frames that have the same column names.