Summary

In this chapter, we learned how to load, manipulate, and analyze raster data. The things we have learned here will work as the cornerstone for doing complicated raster analysis tasks, such as applying machine learning algorithms, as we'll be discussing in later chapters. We learned how to read and load raster data using the raster() function from the raster package in R. For multispectral images, such as Landsat images, we have learned how to use stack() and how to use plotRGB() for false color composite, which gives us colored images. Using the terrain() function with different arguments, such as slope and aspect, we can derive the slope and aspect from DEM data. We can use the hillShade() function to generate hillshade in R. Furthermore, if we want to do raster computation, we can just load different bands as variables and then compute these different raster calculations...